Air & missile defense with spatial grasp technology

A high-level technology is revealed which can effectively convert any distributed system into a globally programmable spatial machine capable of operating without any central resources and self-recovering from indiscriminate damages. Integral mission scenarios in Distributed Scenario Language (DSL)...

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Veröffentlicht in:	Математичні машини і системи
Datum:	2011
1. Verfasser:	Sapaty, P.S.
Format:	Artikel
Sprache:	Englisch
Veröffentlicht:	Інститут проблем математичних машин і систем НАН України 2011
Schlagworte:	Нові інформаційні і телекомунікаційні технології
Online Zugang:	https://nasplib.isofts.kiev.ua/handle/123456789/83509
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Назва журналу:	Digital Library of Periodicals of National Academy of Sciences of Ukraine
Zitieren:	Air & missile defense with spatial grasp technology / P.S. Sapaty // Мат. машини і системи. — 2011. — № 2. — С. 19-34. — Бібліогр.: 38 назв. — англ.

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Digital Library of Periodicals of National Academy of Sciences of Ukraine

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author	Sapaty, P.S.
author_facet	Sapaty, P.S.
citation_txt	Air & missile defense with spatial grasp technology / P.S. Sapaty // Мат. машини і системи. — 2011. — № 2. — С. 19-34. — Бібліогр.: 38 назв. — англ.
collection	DSpace DC
container_title	Математичні машини і системи
description	A high-level technology is revealed which can effectively convert any distributed system into a globally programmable spatial machine capable of operating without any central resources and self-recovering from indiscriminate damages. Integral mission scenarios in Distributed Scenario Language (DSL) can be injected from any point, runtime covering & grasping the whole system or its parts, setting operational infrastructures and orienting local and global behavior in the way needed. Distributed DSL interpreter organization and benefits of using this technology for integrated air and missile defense are discussed along with programming examples in this and other fields. Зображена високорівнева технологія, яка ефективно перетворює довільну розподілену систему на універсальну, глобально програмовану просторову машину, спроможну вирішувати складні задачі без центральних засобів та самовідновлюватись від пошкоджень у реальному часі. Системні місії задаються на спеціальній Мові Розподілених Сценаріїв (МРС), яка інтерпретується в високопаралельному та повністю розподіленому режимі. Структура мережевого інтерпретатора з МРС і заплановане використання технології для інтелектуальних розподілених систем протиповітряної та протиракетної оборони викладені разом з прикладами вирішення практичних задач у цій та інших областях. Описана высокоуровневая технология, эффективно превращающая любую распределенную систему в универсальную, глобально программируемую пространственную машину, способную решать сложные задачи без центральных устройств и самовосстанавливаться от повреждений в реальном времени. Системные миссии задаются на специальном Языке Распределенных Сценариев (ЯРС), который интепретируется в высокопараллельном и полностью распределенном режиме. Структура сетевого интерпретатора с ЯРС и планируемое применение технологии для интеллектуальных распределенных систем противовоздушной и противоракетной обороны изложены вместе с примерами решения практических задач в этой и других областях.
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fulltext	© Sapaty P.S., 2011 ISSN 1028-9763. �� Fig. 1. Some snapshots of air & missile defense systems �� UDC 623.764 P.S. SAPATY AIR& MISSILE DEFENSE WITH �� . �� , �� !� �� " �� : �� . #� �� $�� $� �� " �� . � ��$� �$� �� (%!� ), ��$" �� . �� $� ��$� ��$ ��$ �� : $�� Abstract. A high-level technology is revealed that can effectively convert any distributed system into a globally programmable machine capable of operating without central resources and self indiscriminate damages. Integral mission scenarios in Distributed Scenario Language (DSL) can be i jected from any point, runtime covering & grasping the whole system or its parts, setting operational i frastructures, and orienting local and global behavior in the way needed. Many op be simultaneously injected into this spatial machine from different points, cooperating or competing over the shared distributed knowledge as overlapping fields of solutions. Distributed DSL interpreter organiz tion and benefits of using this technology for integrated air and missile defense are discussed along with programming examples in this and other fields. Keywords: high-level control technology, distributed scenario language, integrated air & missile defense �� , 2011, � 2 Fig. 1. Some snapshots of air & missile �� WITH SPATIAL GRASP TECHNOLOGY �� , �� (�� , �� " � !�� . �� . �� , �� . $�� , &((�� '��'�� , �� $� ��"�� . � ��$� � �� $" �� $�� %!� �� $� � �� " �� " �� &��" �� $�� '�� , ��$� ��$� �� . level technology is revealed that can effectively convert any distributed system into a globally programmable machine capable of operating without central resources and self gral mission scenarios in Distributed Scenario Language (DSL) can be i jected from any point, runtime covering & grasping the whole system or its parts, setting operational i frastructures, and orienting local and global behavior in the way needed. Many operational scenarios can be simultaneously injected into this spatial machine from different points, cooperating or competing over the shared distributed knowledge as overlapping fields of solutions. Distributed DSL interpreter organiz using this technology for integrated air and missile defense are discussed along with mples in this and other fields. level control technology, distributed scenario language, integrated air & missile defense 1. Introduction 1.1. Air & Missile Defense as Large Distributed Systems Air and missile defense capabilities are growing globally and at a fast rate [1, ported by novel technologies ing, interception and destruction of attacking mi siles. These systems are usually distributed on large territories, consist of many interacting ments (from sensors to shooters, see some re snapshots in fig. 1), and are expected 19 �� . �� ( !� ), �� . �� - �� - � �� - �� , �� '��'�� - �� , �� - �� - �� %�$�� !�� - �� - �� - �� " �� - �� . ��$� �� , � - level technology is revealed that can effectively convert any distributed system into a globally programmable machine capable of operating without central resources and self-recovering from gral mission scenarios in Distributed Scenario Language (DSL) can be in- jected from any point, runtime covering & grasping the whole system or its parts, setting operational in- erational scenarios can be simultaneously injected into this spatial machine from different points, cooperating or competing over the shared distributed knowledge as overlapping fields of solutions. Distributed DSL interpreter organiza- using this technology for integrated air and missile defense are discussed along with level control technology, distributed scenario language, integrated air & missile defense. Air & Missile Defense as Large Distributed Air and missile defense capabilities are growing globally and at a fast rate [1, 2]. They are sup- ported by novel technologies for detection, track- ing, interception and destruction of attacking mis- siles. These systems are usually distributed on large territories, consist of many interacting ments (from sensors to shooters, see some related ig. 1), and are expected to work in 20 Fig. 2. Traditional approach in system design and ma agement: (a) original idea; (b) breaking into pieces; (c) system formalization, distribution, and implementation complex conditions to effectively protect national and international infrastructures and withstand unpredictable events. 1.2. Traditional Path in System Development Originally a new system or campaign idea (related to air & missile defense incl.) emerges in a shown in fig. 2c). For a military area, fig. 2 adversary or defending a critical infrastructure; f resources needed for this; and f within a workable system (command and control including) f The original idea (fig. 2a) and even its log in the minds of creators and planners only (possibly also being verbally or graphically recorded in an informal manner), whereas already partitioned, distributed and interlinked stage ( tom up, parts-to-whole strategy in actual system design, in hope that the system developed will ultimately capable of performing the initially formul 1.3. Existing System Design & Implementation Problems • Within the philosophy mentioned above it may be difficult to put the resultant distributed sy tem with many interacting parts into • The resultant system may have side effects, including unwanted ones, like unpredictable beh viors. • The resultant solution may be predominantly system may have to be partially or even completely redesigned and reassembled. • Adjusting the already existing multi new one may result in a considerable 1.4. The Alternative Approach Offered In this paper, we propose formaliza way that can be easily updated or even fully changed, with shifting most of stage b and ly stage c to an automated up to fully automatic implementation (incl. robotization). This can r sult in high flexibility, productivity, and self vanced campaigns, military ones including, where local an can change at runtime. The developed (prototyped and tested in different countries) Spatial Grasp Technology (SGT) and its underlying Distributed Scenario Language (DSL) with details of their distributed ISSN 1028-9763. �� 2. Traditional approach in system design and man- original idea; (b) breaking into pieces; (c) system formalization, distribution, and implementation complex conditions to effectively protect national and international infrastructures and withstand Traditional Path in System Development Originally a new system or campaign idea (related to air & missile defense incl.) emerges in a very general, integral symbolically in fig. tally decomposed into parts, each su sequently detailed, extended, a fied (fig. 2b). Next step is materializ tion of the clarified parts and their di tribution in physical or virtual spaces. To make these parts work together as a whole within the original idea, a good deal of their communication, synchr nization, and sophisticated command and control are usually required (as 2a may correspond to the general idea of winning a battle over an ing a critical infrastructure; fig. 1b additionally clarifies technical and human resources needed for this; and fig. 1c depicts how these resources should be organized together within a workable system (command and control including) fulfilling the global objectives. a) and even its logically partitioned stage (fig. in the minds of creators and planners only (possibly also being verbally or graphically recorded in an informal manner), whereas actual system formalization and implementation begin from the already partitioned, distributed and interlinked stage (fig. 2c). So in reality we have mostly bo whole strategy in actual system design, in hope that the system developed will ultimately capable of performing the initially formulated global task (i.e. of f Existing System Design & Implementation Problems Within the philosophy mentioned above it may be difficult to put the resultant distributed sy tem with many interacting parts into compliance with the initial idea. The resultant system may have side effects, including unwanted ones, like unpredictable beh The resultant solution may be predominantly static, i.e. if the initial idea cha tem may have to be partially or even completely redesigned and reassembled. Adjusting the already existing multi-component system designed for one idea to an essentially result in a considerable loss of the system’s integrity and performance The Alternative Approach Offered In this paper, we propose formalization of the initial stage a of fig. 2 (and if needed, stage b) in a way that can be easily updated or even fully changed, with shifting most of stage b and ly stage c to an automated up to fully automatic implementation (incl. robotization). This can r sult in high flexibility, productivity, and self-recoverability from damages in conducting a vanced campaigns, military ones including, where local and global goals as well as environments The developed (prototyped and tested in different countries) Spatial Grasp Technology (SGT) and its underlying Distributed Scenario Language (DSL) with details of their distributed �� , 2011, � 2 complex conditions to effectively protect national and international infrastructures and withstand Originally a new system or campaign idea (related to air & missile defense incl.) emerges in a very general, integral form (as shown ig. 2a). Then it is men- tally decomposed into parts, each sub- sequently detailed, extended, and clari- ). Next step is materializa- tion of the clarified parts and their dis- tribution in physical or virtual spaces. To make these parts work together as a ole within the original idea, a good deal of their communication, synchro- nization, and sophisticated command usually required (as a may correspond to the general idea of winning a battle over an ig. 1b additionally clarifies technical and human ig. 1c depicts how these resources should be organized together lfilling the global objectives. ig. 2b) usually remain in the minds of creators and planners only (possibly also being verbally or graphically recorded in actual system formalization and implementation begin from the c). So in reality we have mostly bot- whole strategy in actual system design, in hope that the system developed will be . of fig. 2a). Within the philosophy mentioned above it may be difficult to put the resultant distributed sys- The resultant system may have side effects, including unwanted ones, like unpredictable beha- , i.e. if the initial idea changes, the whole tem may have to be partially or even completely redesigned and reassembled. component system designed for one idea to an essentially integrity and performance. ig. 2 (and if needed, stage b) in a way that can be easily updated or even fully changed, with shifting most of stage b and complete- ly stage c to an automated up to fully automatic implementation (incl. robotization). This can re- recoverability from damages in conducting ad- d global goals as well as environments The developed (prototyped and tested in different countries) Spatial Grasp Technology (SGT) and its underlying Distributed Scenario Language (DSL) with details of their distributed ISSN 1028-9763. �� Fig. 3. The waves paradigm: (a) controlled grasping of distributed worlds with spatial waves; (b) self high-level wave-like mission scenarios in distributed networked environment implementation in networked systems are briefed, along with application examples related to di tributed air and missile defense (for existing basic publications on this paradigm see also [3 2. Grasping Solutions with Spatial Waves The model described here reflects higher distributed systems by human brain in the form of parallel mental waves cover the space [7–9] (fig. 3a) rather than traditional collection and interaction of parts or agents [10] definition of systems and operations in them while omitting tra details (such as in fig. 2c), thus effectively concentrating on global goals and behaviors instead. Materialization of this approach is carried out by the modules (U) embedded into important scenarios expressed in the waves formalism system at runtime, as in fig. 3b and can cooperate or compete in the networked space as overlapping The compact spreading scenarios, which can be much (up to a hundred times) shorter than, say, in Java, structures arbitrarily distributed between system components (humans, robots, sensors). gated by same or other scenarios, they can effectively support command and control, also provide overall 3. Distributed Scenario Language DSL is quite different from traditional programming languages. Rather than describing data processing in a computer memory, as usual, it allows us to directly move through, observe, and make any actions in fully distributed environments 3.1. The Worlds DSL Operates with DSL directly operates with: • Virtual World (VW), which is finite and discrete, consisting of nodes and semantic links between them. • Physical World (PW), an infinite and continuous, where each point can be i with physical coordinates (with a certain precision). • Virtual-Physical World (VPW), being finite and discrete similar to VW, but associating some or all virtual nodes with PW coordinates. 3.2. Main DSL features Other DSL features can be summarized as follows: �� , 2011, � 2 Fig. 3. The waves paradigm: (a) controlled grasping of distributed worlds with spatial waves; (b) self-evolving like mission scenarios in distributed networked environment n in networked systems are briefed, along with application examples related to di tributed air and missile defense (for existing basic publications on this paradigm see also [3 Grasping Solutions with Spatial Waves The model described here reflects higher-level, holistic, gestalt-like vision and comprehension of distributed systems by human brain in the form of parallel mental waves cover ) rather than traditional collection and interaction of parts or agents [10] on which most of existing tems are based. The original system idea (of f 2a) is represented in an integral non atomistic but at the same time fully fo mal way, reflecting how a human co mander mentally observes the space where a problem is to be solved. Trad tional atomism emerges only during i terpretation of this formally represented idea (which may be automatic, and only when really required). This allows us to get flexible and easily changeable formal definition of systems and operations in them while omitting traditional numerous orga effectively concentrating on global goals and behaviors instead. Materialization of this approach is carried out by the network of universal intelligent embedded into important system points, which collectively interpret integral in the waves formalism (starting from any point and covering the distributed . 3b). Different scenarios can start from the same or different point and can cooperate or compete in the networked space as overlapping fields of solutions The compact spreading scenarios, which can be created and modified on the fly, being much (up to a hundred times) shorter than, say, in Java, are forming dynamic arbitrarily distributed between system components (humans, robots, sensors). gated by same or other scenarios, they can effectively support distributed databases , also provide overall situation awareness and autonomous decisions Distributed Scenario Language DSL is quite different from traditional programming languages. Rather than describing data processing in a computer memory, as usual, it allows us to directly move through, observe, and make any actions in fully distributed environments (whether physical or virtual). The Worlds DSL Operates with Virtual World (VW), which is finite and discrete, consisting of nodes and semantic links Physical World (PW), an infinite and continuous, where each point can be i tes (with a certain precision). Physical World (VPW), being finite and discrete similar to VW, but associating tual nodes with PW coordinates. summarized as follows: 21 n in networked systems are briefed, along with application examples related to dis- tributed air and missile defense (for existing basic publications on this paradigm see also [3–6]). ike vision and comprehension of distributed systems by human brain in the form of parallel mental waves covering and grasping ) rather than traditional collection and interaction of parts or agents [10] on which most of existing software sys- The original system idea (of fig. ) is represented in an integral non- atomistic but at the same time fully for- mal way, reflecting how a human com- mander mentally observes the space where a problem is to be solved. Tradi- tomism emerges only during in- terpretation of this formally represented idea (which may be automatic, and only when really required). This allows us to get flexible and easily changeable formal ditional numerous organizational effectively concentrating on global goals and behaviors instead. network of universal intelligent system points, which collectively interpret integral mission (starting from any point and covering the distributed ). Different scenarios can start from the same or different points, fields of solutions. created and modified on the fly, being are forming dynamic knowledge infra- arbitrarily distributed between system components (humans, robots, sensors). Navi- distributed databases, advanced autonomous decisions. DSL is quite different from traditional programming languages. Rather than describing data processing in a computer memory, as usual, it allows us to directly move through, observe, and r virtual). Virtual World (VW), which is finite and discrete, consisting of nodes and semantic links Physical World (PW), an infinite and continuous, where each point can be identified Physical World (VPW), being finite and discrete similar to VW, but associating 22 Fig. 4. DSL recursive syntax and main constructs • A scenario expressed in it develops as a transition between sets of progress points (or props) in the form of parallel waves. • Starting from a prop, an action may result in one or more new props. • Each prop has a resulting value the four: thru (full success allowing us to proceed further from this point), done (success with termination of the activity in this point), fail (regular failure with local termination), and abort (emergency failure, terminating the whole distributed process, associated with other points too). • Different actions may evolve independently or interdependently from the same prop, contributing to (and forming altogether) the resultant set of props. • Actions may also spatially succeed each other, with new ones applied in parallel from props reached by the preceding actions. • Elementary operations can directly use local or remote values of props obtained from other actions (the whole scenarios includin operations. These resultant values can be used as operands by other operations in an expression or by the next operations in a sequence (the latter can be multiple, if processes split). • These values can also be directly assigned to local or remote variables (for the latter case, an access to these variables may invoke scenarios of any complexity). • Any prop can associate with a node in VW or a position in PW, or both (when dealing with VPW); it can also refer to both worlds separately and independently. • Any number of props can be simultaneously associated with the same points of the worlds (physical, virtual, or combined). • Staying with the world points, it is possible to directly access and upda them. • Moving in physical, virtual or combined worlds, with their possible modification or even creation from scratch, are as routine operations as, say, arithmetic, logical, or control flow of tr ditional programming languages. • DSL can also be used as a universal programming language (similar to C, Java or FO TRAN). • hop in a physical, virtual, or combined space; • hierarchical fusion and return of (remote) data; • distributed control, both sequential and parallel; • a variety of special contexts for navigation in space, influencing operations and decisions; • type or sense of a value, or its chosen usage, guiding automatic interpretation. 3.4. DSL Spatial Variables There are different types of variables in DSL: ISSN 1028-9763. �� Fig. 4. DSL recursive syntax and main constructs A scenario expressed in it develops as a transition between sets of progress points (or props) in the form of parallel waves. Starting from a prop, an action may result in one or more new props. Each prop has a resulting value (which can be multiple) and resulting state, being one of the four: thru (full success allowing us to proceed further from this point), done (success with termination of the activity in this point), fail (regular failure with local termination), and abort (emergency failure, terminating the whole distributed process, associated with other points too). Different actions may evolve independently or interdependently from the same prop, contributing to (and forming altogether) the resultant set of props. Actions may also spatially succeed each other, with new ones applied in parallel from props reached by the preceding actions. Elementary operations can directly use local or remote values of props obtained from other actions (the whole scenarios including), resulting in value(s) of prop(s) produced by these These resultant values can be used as operands by other operations in an expression or by the next operations in a sequence (the latter can be multiple, if processes split). can also be directly assigned to local or remote variables (for the latter case, an access to these variables may invoke scenarios of any complexity). Any prop can associate with a node in VW or a position in PW, or both (when dealing also refer to both worlds separately and independently. Any number of props can be simultaneously associated with the same points of the worlds (physical, virtual, or combined). Staying with the world points, it is possible to directly access and upda Moving in physical, virtual or combined worlds, with their possible modification or even creation from scratch, are as routine operations as, say, arithmetic, logical, or control flow of tr ditional programming languages. also be used as a universal programming language (similar to C, Java or FO 3.3. DSL Syntax and Main Constructs DSL has recursive syntax, level as in fig. 4 (programs are reflecting their main semantics as gasping and integrating distributed resources into goal-driven systems). The basic construct rule can represent any definition, action or decision, for example: • elementary arithmetic, string or logic ope tion; , or combined space; hierarchical fusion and return of (remote) data; distributed control, both sequential and parallel; a variety of special contexts for navigation in space, influencing operations and decisions; type or sense of a value, or its chosen usage, guiding automatic interpretation. There are different types of variables in DSL: �� , 2011, � 2 A scenario expressed in it develops as a transition between sets of progress points (or Starting from a prop, an action may result in one or more new props. (which can be multiple) and resulting state, being one of the four: thru (full success allowing us to proceed further from this point), done (success with termination of the activity in this point), fail (regular failure with local termination), and abort (emergency failure, terminating the whole distributed process, associated with other points too). Different actions may evolve independently or interdependently from the same prop, Actions may also spatially succeed each other, with new ones applied in parallel from Elementary operations can directly use local or remote values of props obtained from g), resulting in value(s) of prop(s) produced by these These resultant values can be used as operands by other operations in an expression or by the next operations in a sequence (the latter can be multiple, if processes split). can also be directly assigned to local or remote variables (for the latter Any prop can associate with a node in VW or a position in PW, or both (when dealing Any number of props can be simultaneously associated with the same points of the Staying with the world points, it is possible to directly access and update local data in Moving in physical, virtual or combined worlds, with their possible modification or even creation from scratch, are as routine operations as, say, arithmetic, logical, or control flow of tra- also be used as a universal programming language (similar to C, Java or FOR- DSL Syntax and Main Constructs DSL has recursive syntax, represented on top ig. 4 (programs are called grasps, reflecting their main semantics as gasping and integrating distributed resources into The basic construct rule can represent any definition, action or decision, for example: elementary arithmetic, string or logic opera- a variety of special contexts for navigation in space, influencing operations and decisions; type or sense of a value, or its chosen usage, guiding automatic interpretation. ISSN 1028-9763. �� Fig. 5. Organization of DSL interpreter Fig. 6. Distributed track system: a) forward oper tions; b) backward operations with tracks optimization • Heritable variables – these are starting in a prop and serving all subsequent props, which can share them in both read & write operations. • Frontal variables – are an individual and exclusive prop’s property (not shared with ot er props), being transferred between the consecutive props, and replicated if from a single prop a number of props emerge. • Environmental variables when navigating them, also a variety of parameters of the internal world of DSL interpreter. • Nodal variables – allow us to attach an individual temporary propert nodes, accessed and shared by pro These variables, especially when used together, allow us to create efficient spatial alg rithms not associated with particular processing resources, working in between compone distributed systems rather than in them. These algorithms can also freely move in distributed processing environment (partially or as a whole), always preserving integrity and overall control. DSL also permits the use of traditional operational sym and shorten programs, if this proves useful. cation structure between them. • Copies of the interpreter can be concealed, as for acting in hostile systems, allowing us to impact the latter overwhelmingly (finding & elimin sources. • The dynamically crated track trees spanning the systems in which DSL scenarios evolve are used for supporting spatial variables and echoing and merging different types of control states and remote data, being self-optimized in the echo processes. • They also route further waves to the positions in physical, virtual or combined spaces reached by the previous waves, uniting them with the frontal variables left there by preceding waves. �� , 2011, � 2 rganization of DSL interpreter Fig. 6. Distributed track system: a) forward opera- tions; b) backward operations with tracks these are starting in a prop and serving all subsequent props, which share them in both read & write operations. are an individual and exclusive prop’s property (not shared with ot er props), being transferred between the consecutive props, and replicated if from a single prop a Environmental variables – are accessing different elements of physical and virtual words them, also a variety of parameters of the internal world of DSL interpreter. allow us to attach an individual temporary propert nodes, accessed and shared by props associated with these nodes. These variables, especially when used together, allow us to create efficient spatial alg rithms not associated with particular processing resources, working in between compone distributed systems rather than in them. These algorithms can also freely move in distributed processing environment (partially or as a whole), always preserving integrity and overall control. DSL also permits the use of traditional operational symbols and delimiters, to simplify and shorten programs, if this proves useful. 4. Distributed DSL Interpreter 4.1. Structure of the Interpreter The DSL interpreter [4-6] (see f following key features: • It consists of a lized modules working in parallel and ha dling and sharing specific data structures supporting persistent virtual worlds and te porary hierarchical control mechanisms. • The whole network of the interpr ters can be mobile and open runtime the number of nodes and commun Copies of the interpreter can be concealed, as for acting in hostile systems, allowing us to impact the latter overwhelmingly (finding & eliminating unwanted infrastructures including). 4.2. Distributed Track System • The heart of the distributed interpreter is its spatial track system (fig. 6) with its parts kept in the Track Forest memory of local interpr ters; these being logically interlinked with such parts in other interpreter copies, forming altogether indivisible space coverage. • This enables hierarchical command and control and remote data and code access, with high integrity of emerging parallel and distr buted solutions, without any centralized r The dynamically crated track trees spanning the systems in which DSL scenarios evolve are ariables and echoing and merging different types of control states ptimized in the echo processes. They also route further waves to the positions in physical, virtual or combined spaces reached them with the frontal variables left there by preceding waves. 23 these are starting in a prop and serving all subsequent props, which are an individual and exclusive prop’s property (not shared with oth- er props), being transferred between the consecutive props, and replicated if from a single prop a are accessing different elements of physical and virtual words them, also a variety of parameters of the internal world of DSL interpreter. allow us to attach an individual temporary property to VW and VPW These variables, especially when used together, allow us to create efficient spatial algo- rithms not associated with particular processing resources, working in between components of distributed systems rather than in them. These algorithms can also freely move in distributed processing environment (partially or as a whole), always preserving integrity and overall control. bols and delimiters, to simplify Distributed DSL Interpreter Structure of the Interpreter 6] (see fig. 5) has the It consists of a number of specia- working in parallel and han- dling and sharing specific data structures supporting persistent virtual worlds and tem- porary hierarchical control mechanisms. The whole network of the interpre- mobile and open, changing at time the number of nodes and communi- Copies of the interpreter can be concealed, as for acting in hostile systems, allowing us ating unwanted infrastructures including). Distributed Track System The heart of the distributed interpreter is its ig. 6) with its parts kept in the Track Forest memory of local interpre- ters; these being logically interlinked with such parts in other interpreter copies, forming altogether indivisible space coverage. This enables hierarchical command and nd remote data and code access, with high integrity of emerging parallel and distri- buted solutions, without any centralized re- The dynamically crated track trees spanning the systems in which DSL scenarios evolve are ariables and echoing and merging different types of control states They also route further waves to the positions in physical, virtual or combined spaces reached them with the frontal variables left there by preceding waves. 24 Fig. 7. DSL interpretation network as a universal parallel spatial machine Fig. 8. Finding shortest path in parallel distributed mode solution in DSL of some important problems on distributed structures in a parallel and fully di tributed way, where each node may reside in (or associate with) a may well relate to the general orientation of this 5.1. Finding Shortest Path in Parallel The solution for finding shortest path between two nodes (let them be a and e) ca by DSL scenario that follows. frontal(Far, Path); sequence( (hop(‘a’); Distance = 0; repeat(hop(alllinks); Far += LINK; or(Distance == nil, Distance > Far); Distance = Far; Before = BACK)), (hop(‘e’); repeat(Path = NAME & Path; hop(Before)); output(Path))) col [11] capable of organizing any communication, and especially if other means fail during and after indiscriminate damages to infrastructures. 5.2. Analyzing Distributed Structures Another important problems in distributed systems may be finding weak (or weakest) and strong (strongest) parts in them, whether these are civil or military organizations (say, battlefields in the latter case), and friendly or of adversaries. In the examples below we for lems on general graphs where any node may To find the weakest nodes in a graph, li split it into disjoint parts, the following program suffi ISSN 1028-9763. �� Fig. 7. DSL interpretation network as a universal parallel spatial machine Fig. 8. Finding shortest path in parallel 4.3. DSL Interpreter as a Universal Sp tial Machine The (dynamically) networked DSL interpr ters (fig. 7) are effectively forming parallel spatial machine (“machine” rather than computer as it operates with physical matter too and move partially or as a whole in physical space), capable of solving any problems in a fully distributed mode, wit out any special central resources. 5. Elementary Programming Examples We will show here elementary examples of solution in DSL of some important problems on distributed structures in a parallel and fully di tributed way, where each node may reside in (or associate with) a different computer. These tasks general orientation of this paper on air and missile defense (see also [4, Finding Shortest Path in Parallel The solution for finding shortest path between two nodes (let them be a and e) ca (hop(‘a’); Distance = 0; repeat(hop(alllinks); Far += LINK; or(Distance == nil, Distance > Far); Distance = Far; Before = BACK)), Path; hop(Before)); The result obtained in node a for the network in fig. 8 will be been found by navigating the network of weighed links in parallel and mode, without any central resources. Many important problems of optimiz tion and control (from battlefields to infr structure protection) may be expressed as finding shortest paths in distributed spaces. SGT, on the example of this task, a higher level universal communication prot col [11] capable of organizing any communication, and especially if other means fail during and after indiscriminate damages to infrastructures. Analyzing Distributed Structures nt problems in distributed systems may be finding weak (or weakest) and strong (strongest) parts in them, whether these are civil or military organizations (say, battlefields in the latter case), and friendly or of adversaries. In the examples below we formulate these two pro lems on general graphs where any node may be with a different computer (fig. 9). To find the weakest nodes in a graph, like articulation points (see fig. 9a), which when removed split it into disjoint parts, the following program suffices (resulting in node d). �� , 2011, � 2 DSL Interpreter as a Universal Spa- The (dynamically) networked DSL interpre- effectively forming parallel spatial machine (“machine” rather than computer as it operates with physical matter too and move partially or as a whole in physical space), capable of solving any problems in a fully distributed mode, with- al resources. Programming Examples We will show here elementary examples of solution in DSL of some important problems on distributed structures in a parallel and fully dis- different computer. These tasks paper on air and missile defense (see also [4, 5]). The solution for finding shortest path between two nodes (let them be a and e) can be expressed The result obtained in node a for the ig. 8 will be (a, b, d, e). It has been found by navigating the network of weighed links in parallel and fully distributed without any central resources. Many important problems of optimiza- tion and control (from battlefields to infra- structure protection) may be expressed as ing shortest paths in distributed spaces. SGT, on the example of this task, can serve as a higher level universal communication proto- col [11] capable of organizing any communication, and especially if other means fail during and nt problems in distributed systems may be finding weak (or weakest) and strong (strongest) parts in them, whether these are civil or military organizations (say, battlefields in the mulate these two prob- ig. 9). ig. 9a), which when removed ces (resulting in node d). ISSN 1028-9763. �� Fig. 9. Solving topological problems: a) articulation points; b) finding cliques Fig. 10. Integration of ground and aerial robots in SGT in: (a, b, c, d), (c, d, e), (d, e, f): hop(allnodes); Fclique = CONTENT; repeat( hop(alllinks); notbelong(CONTENT, Fclique); and(andparallel(hop(anylink, Fclique)!, or(BACK > NAME!, Fclique & NAME))); output(Fclique) where only global task is formulated (like in f delegated to the distributed DSL interpreter), and also expressing some sort of explicit collect behavior (corresponding to fig. delegated to automation). 6.1. Semantic, Task Level For this case, a group of mobile robots can be tasked at a highest possible level, just telling what they should do together but without detailing may not be known in advance. An exemplary task: Go to physical locations of the disaster zone with coordinates (50.433, and (50.467, 30.517). Evaluate damage in each location, tion value, together with exact coordinates of the corresponding location, to a management ce ter. The DSL program will be as follows: transmit(max( move((50.433, 30.633), (50.417, 30.490), (50.467, 30.517)); evaluate(destruction) & WHERE)) �� , 2011, � 2 Fig. 9. Solving topological problems: a) discovering articulation points; b) finding cliques Fig. 10. Integration of ground and aerial robots hop(allnodes); IDENTITY = NAME; mark; and((hop(random, alllinks); repeat(unmarked; mark; hop(alllinks))), (hop(alllinks); unmarked), output(NAME)) Cliques (or maximum fully connected sub-graphs of a graph), on the contrary, may be considered as strongest parts of a system. They all can be found in parallel by the fo lowing simple program resulting for hop(allnodes); Fclique = CONTENT; hop(alllinks); notbelong(CONTENT, Fclique); and(andparallel(hop(anylink, Fclique)!, or(BACK > NAME!, Fclique & NAME))); 6. Collective Robotics Examples in DSL Installing DSL interpreter into mobile robots (ground, aerial, surface, underwater, space, etc., as in Figure 10 for the first two) allows us to organize effective group solutions (incl. any swarming) of complex problems in distributed physical spaces in a clear and concise way, shifting traditional manag ment routines to automatic levels. We will consider two levels: org nizing robotic swarms on top. sema formulated (like in fig. 2a, and all internal system organization is fully delegated to the distributed DSL interpreter), and also expressing some sort of explicit collect ig. 2b and partially fig. 2c, while the rest of organization of For this case, a group of mobile robots can be tasked at a highest possible level, just telling what they should do together but without detailing how, and what are the duties of every unit, which may not be known in advance. An exemplary task: Go to physical locations of the disaster zone with coordinates (50.433, 30.633), (50.417, 30.490), 30.517). Evaluate damage in each location, find and transmit the maximum destru tion value, together with exact coordinates of the corresponding location, to a management ce The DSL program will be as follows: move((50.433, 30.633), (50.417, 30.490), (50.467, 30.517)); evaluate(destruction) & WHERE)) 25 hop(allnodes); IDENTITY = NAME; and((hop(random, alllinks); repeat(unmarked; mark; (hop(alllinks); unmarked), Cliques (or maximum fully connected graphs of a graph), on the contrary, may be considered as strongest parts of a system. They all can be found in parallel by the fol- ogram resulting for fig. 9b Collective Robotics Examples in DSL Installing DSL interpreter into mobile robots (ground, aerial, surface, underwater, space, etc., as in Figure 10 for the first two) allows effective group solutions (incl. any swarming) of complex problems in distributed physical spaces in a clear and concise way, shifting traditional manage- ment routines to automatic levels. We will consider two levels: orga- nizing robotic swarms on top. semantic level a, and all internal system organization is fully delegated to the distributed DSL interpreter), and also expressing some sort of explicit collective while the rest of organization of fig. 2c For this case, a group of mobile robots can be tasked at a highest possible level, just telling what how, and what are the duties of every unit, which 30.633), (50.417, 30.490), find and transmit the maximum destruc- tion value, together with exact coordinates of the corresponding location, to a management cen- 26 ISSN 1028-9763. �� , 2011, � 2 Details of automatic implementation of this scenario by different and possibly runtime varying numbers of mobile robots are discussed elsewhere [12, 13]. 6.2. Explicit Behavior Level After embedding DSL interpreters into robotic vehicles, we can also provide any needed detailed collective behavior of them (at a lower than top task level, as before) – from loose swarms to a strictly controlled integral unit obeying external orders. Any mixture of different behaviors within the same scenario can be easily programmed too. Expressing different simple scenarios in DSL and their integration into a more complex combined one may be as follows. • Swarm movement scenario, starting from any unit (swarm_move): hop(allnodes); Limits = (dx(0,8), dy(-2,5)); Range = 500; repeat(Shift = random(Limits); if(empty(hop(Shift, Range), move(Shift))) • Finding topologically central unit and hopping into it, starting from any unit (find_hop_center): frontal(Avr)= average(hop(allnodes); WHERE); hop(min(hop(allnodes); distance(Avr, WHERE) & ADDRESS) : 2) • Creating runtime infrastructure, starting from the central unit found (infra_build): stay(repeat(linkup(+infra, first, Depth))) • Targets collection & distribution & impact, starting from the central unit found (col- lect_distribute_impact): loop(nonempty(frontal(Seen) = repeat(detect(targets), hop(+infra))); repeat(select_move_shoot(Seen),hop(+infra))) • Removing previous infrastructures (for subsequently creating a new one), starting from any unit (infra_remove): stay(hop(allnodes); remove(alllinks)) Resultant combined solution (integration previous DSL programs named in bold), starting from any unit: parallel( swarm_move, repeat(find_hop_center; infra_remove; infra_build; orparallel( collect_distribute_impact, sleep(delay)))) The obtained resultant scenario combines loose, oriented-random swarm movement in a distributed space with periodic finding and updating topologically central unit, and setting- ISSN 1028-9763. �� Fig. 11. Collecting, disseminating, and attac ing targets by an unmanned aerial te dynamically created and updated 2 structure, while moving altogether as a loose swarm Fig. 12. Tracking moving objects by mobile intelligence updating runtime hierarchical infrastructure between the units. The latter controls observation of vating the whole region around in parallel to physical move). frontal(Object, Threshold = visibility); hop(all_nodes); split(search_colect(aerial, Threshold)); Object = VALUE; repeat( cycle(visibility(Object) > Threshhold); max_destination( ho p(all_neighbors); visibility(Object))) By this mobile intelligence techniques, each discovered target (aerial, ground, space, etc.) can always be kept in view individually, in parallel with other ones, its behavior can gradually analyzed and accumulated, and optimal (possibly, scarce and scattered) impact facilities act vated, if needed. (More on this task, say, in [15].) 7.2. Directed Energy Systems Directed energy systems and weapons (DEW) are of rapidly growing importance in many areas and especially in critical infrastructure protection, at adva and, of course, for advanced air and missile defense, as potential capabilities for shooting down unwanted aerial and space objects with DEW are beyond comparison with ot isting and being developed. �� , 2011, � 2 Fig. 11. Collecting, disseminating, and attack- ing targets by an unmanned aerial team using dynamically created and updated 2� infra- structure, while moving altogether as a Fig. 12. Tracking moving objects by mobile updating runtime hierarchical infrastructure between the units. The latter controls observation of distributed territory, collecting potential targets, distributing them back to the vehicles, and then selecting and impacting potential targets by them individually (a related snapshot, say, for aerial vehicles, is shown in this integral scenario can be found in [14]. 7. Air & Missile Defense with SGT WE will be considering here different scenarios related to distributed integrated air defense and their expression in DSL. 7.1. Distributed Tracking In a vast distributed environment, each embe ded (or moving) sensor can usually observe o ly a limited part of space, so to keep the whole observation continuous and integral, each n ticed mobile object should be tween neighboring sensors during its mov ment, along with the data acc in fig. 12). The following program, sensors, catches the object it sees (splitting itself if more than one) and follows goes, if not observable from the current point any more (via the virtual networked space, act vating the whole region around in parallel to define the next tracing move matching the object’s frontal(Object, Threshold = visibility); split(search_colect(aerial, Threshold)); cycle(visibility(Object) > Threshhold); p(all_neighbors); visibility(Object))) By this mobile intelligence techniques, each discovered target (aerial, ground, space, etc.) can always be kept in view individually, in parallel with other ones, its behavior can gradually and optimal (possibly, scarce and scattered) impact facilities act vated, if needed. (More on this task, say, in [15].) Directed energy systems and weapons (DEW) are of rapidly growing importance in many areas in critical infrastructure protection, at advanced battlefields (as shown in f and, of course, for advanced air and missile defense, as potential capabilities for shooting down unwanted aerial and space objects with DEW are beyond comparison with ot 27 updating runtime hierarchical infrastructure between the units. The latter controls observation of distributed territory, collecting potential targets, distributing them back to the vehicles, and then selecting and impacting potential targets by dividually (a related snapshot, say, for aerial vehicles, is shown in fig. 11). More on this integral scenario can be found in [14]. Air & Missile Defense with SGT WE will be considering here different scenarios related to distributed integrated air and missile defense and their expression in DSL. of Moving Objects In a vast distributed environment, each embed- ded (or moving) sensor can usually observe on- , so to keep the whole observation continuous and integral, each no- ticed mobile object should be handed over be- tween neighboring sensors during its move- ment, along with the data accumulated on it (as The following program, starting in all it sees (splitting itself follows it wherever it goes, if not observable from the current point any more (via the virtual networked space, acti- define the next tracing move matching the object’s By this mobile intelligence techniques, each discovered target (aerial, ground, space, etc.) can always be kept in view individually, in parallel with other ones, its behavior can gradually and optimal (possibly, scarce and scattered) impact facilities acti- Directed energy systems and weapons (DEW) are of rapidly growing importance in many areas nced battlefields (as shown in fig. 13) and, of course, for advanced air and missile defense, as potential capabilities for shooting down unwanted aerial and space objects with DEW are beyond comparison with other means, both ex- 28 � ) b) Fig. 13. DEW on an advanced battlespace: a) Oper tional picture; b) DE-RM-target runtime control; c) DE delivery via network of relay mirrors Fig. 14. Integration of DEW with conventional forces With hardware equipment operating with the speed of light, traditional manned C2 may become a bottleneck for these advanced technical capabilities, especially in crisis events. With the SGT technology installed, we may organize any runtime (even on the fly) C2 infrastructures operating automatically, with the “speed of light” too, fitting hardware capabilities and possibly even e cluding men from the loop in time critical situations. 24/7 coverage of every corner of the globe. When activated, this would enable a directed energy response to critical trouble spots anywhere. obtaining advanced rapid reaction forces for most diverse applications, air and missile defense including [17]. 7.3. Global Awareness & Parallel Impact of Targets In fig. 15 (see also [18]), a possible conflict where global awareness and coordinated actions may be crucial to withstand it. Having installed DSL interpreter in different units (both manned and unmanned) it will become possible to coo dinate and manage the global reactio ISSN 1028-9763. �� c) Fig. 13. DEW on an advanced battlespace: a) Opera- target runtime control; c) DE delivery via network of relay mirrors Fig. 14. Integration of DEW with conventional With hardware equipment operating with the speed of light, traditional manned C2 may become a bottleneck for these advanced technical capabilities, especially in crisis events. With the SGT , we may organize any runtime (even on the fly) C2 infrastructures operating automatically, with the “speed of light” too, fitting hardware capabilities and possibly even e cluding men from the loop in time critical situations. The following is an ting an automatic runtime C2 in a system with direct energy (DE) source, relay mi ror (RM), and the Target discovered, with an operational snapshot shown in f frontal(DE = coordinates1; RM = coordintes2; Target = coordinates3); sequence( parallel((hop(DE); adjust(RM)), (hop(RM); adjust(DE, Target))), (hop(DE); activate)) There also exist advanced projects of global dominance with transference of directed energy, like the Relay Mirror System (ARMS) concept plans to entail a constellation of as many as two dozen orbiting mirrors that would allow 24/7 coverage of every corner of the globe. When activated, this would enable a directed energy response to critical trouble spots anywhere. We can use the distributed shortest path solution shown in section 5.1 for providing a runtime path in a worldwide ic set of relay mirrors (as some of which may themselves happen to be on the move or out of order) – between DE source and the destination needed. This will provide optimal directed ene gy transfer, as shown in fig. 13 17]). Embedding DSL interpreter into both DEW facilities and conventional force units (as in fig. 14), we can effectively integrate rapidly developing DEW into the force mix, which may also include multiple unmanned vehicles, thus obtaining advanced rapid reaction forces for most diverse applications, air and missile defense Global Awareness & Parallel Impact of Targets ig. 15 (see also [18]), a possible conflict situation is shown on a supposedly large territory, where global awareness and coordinated actions may be crucial to withstand it. Having installed DSL interpreter in different units (both manned and unmanned) it will become possible to coo age the global reaction needed. �� , 2011, � 2 With hardware equipment operating with the speed of light, traditional manned C2 may become a bottleneck for these advanced technical capabilities, especially in crisis events. With the SGT , we may organize any runtime (even on the fly) C2 infrastructures operating automatically, with the “speed of light” too, fitting hardware capabilities and possibly even ex- The following is an example of set- ting an automatic runtime C2 in a system with direct energy (DE) source, relay mir- ror (RM), and the Target discovered, with operational snapshot shown in fig. 13b. frontal(DE = coordinates1; RM = Target = coordinates3); parallel((hop(DE); adjust(RM)), (hop(RM); adjust(DE, Target))), (hop(DE); activate)) There also exist advanced projects of global dominance with transference of directed energy, like the Boeing’s Advanced Relay Mirror System (ARMS) concept. It nstellation of as many as two dozen orbiting mirrors that would allow 24/7 coverage of every corner of the globe. When activated, this would enable a directed energy We can use the distributed shortest path ution shown in section 5.1 for providing a time path in a worldwide distributed dynam- ic set of relay mirrors (as some of which may themselves happen to be on the move or out of between DE source and the destination optimal directed ener- ig. 13c (see also [16, Embedding DSL interpreter into both onventional force units (as ig. 14), we can effectively integrate rapidly developing DEW into the force mix, which may lso include multiple unmanned vehicles, thus obtaining advanced rapid reaction forces for most diverse applications, air and missile defense situation is shown on a supposedly large territory, where global awareness and coordinated actions may be crucial to withstand it. Having installed DSL interpreter in different units (both manned and unmanned) it will become possible to coor- ISSN 1028-9763. �� Fig. 15. Distributed targets collection and dissemination launched ahead or even during the conflict): loop(nonempty(frontal(Targets) = repeat(discover(local), hop(infra))); repeat(select_attack(Targets), hop(infra))) No central resources (C2 able in crisis-prone and asymmetric situations, especially those related to infrastructure prote tion, battlefield management, and air & missile defense. 7.4. Europe-Related Missile Defense Scenarios Let us consider here some scenarios relevant to the currently being discussed European missile defense plans, widely available [19] and copied in f � ) c) Fig. 16. Possible European missile defense scenarios. a) 1: Infrared satellite system picks up heat signatures of hostile mi siles launched towards target. 2: Information transmitted to ground stations for processing. 3: Processed information sent to C2 network; b) The C2 network relays information to sensor and weapons systems in the region; c) 1: Long continue to track the missile to help command system calculate options for destroying them. 2: Information is constantly shared among the sensors and weapons systems; d) Command system has the option of shooting down the hostile missiles while in the upper or lower layers of the atmosphere �� , 2011, � 2 15. Distributed targets collection and Similar to the solutions in Section 6.2 for explicit robotic swarm behavior, we can launch global awareness, collection and di semination of targets throughout territory and their impact by available distr buted resources from any component with the interpreter installed in it, as in f The self-navigating and self scenario, allowing us to cover the whole sy tem at runtime and set vior, is extremely simple (can be created and launched ahead or even during the conflict): loop(nonempty(frontal(Targets) = repeat(discover(local), hop(infra))); repeat(select_attack(Targets), hop(infra))) No central resources (C2 including) are needed for this, which may be particularly vulne prone and asymmetric situations, especially those related to infrastructure prote tion, battlefield management, and air & missile defense. Related Missile Defense Scenarios Let us consider here some scenarios relevant to the currently being discussed European missile y available [19] and copied in fig. 16. b) d) Fig. 16. Possible European missile defense scenarios. a) 1: satellite system picks up heat signatures of hostile mis- siles launched towards target. 2: Information transmitted to ground stations for processing. 3: Processed information sent to C2 network; b) The C2 network relays information to sensor tems in the region; c) 1: Long-range sensors continue to track the missile to help command system calculate options for destroying them. 2: Information is constantly shared among the sensors and weapons systems; d) Command system down the hostile missiles while in the upper or lower layers of the atmosphere Having extended these with advanced capabilities like DEW (high power lasers) located in space or on airborne (manned or UAV) platforms (synchronized with infrared satellite sensors and also capable of using relay mi rors, as in fig. 13), the following very simple DSL scenario integrating infrared lites, DEW facilities, long range sensors and upper and lower layer shooters into a dynamic distr buted system capable of discove ing hostile objects, tracing them at different stages of flight, and (re)launching target impact facil ties with verifica cess or failure, until the targets are destroyed. hop(infrared_satellite_se nsors); loop( nonempty(New = infr red(new_targets)); release( 29 Similar to the solutions in Section 6.2 for explicit robotic swarm behavior, we can launch global awareness, collection and dis- semination of targets throughout the whole territory and their impact by available distri- buted resources from any component with rpreter installed in it, as in fig. 15. navigating and self-replicating DSL scenario, allowing us to cover the whole sys- up its needed beha- vior, is extremely simple (can be created and including) are needed for this, which may be particularly vulner- prone and asymmetric situations, especially those related to infrastructure protec- Let us consider here some scenarios relevant to the currently being discussed European missile Having extended these with advanced capabilities like W (high power lasers) located in space or on airborne (manned or UAV) platforms (synchronized with infrared satellite sensors and also capable of using relay mir- rors, as in fig. 13), we can write the following very simple DSL scenario integrating infrared satel- lites, DEW facilities, long range sensors and upper and lower layer shooters into a dynamic distri- buted system capable of discover- ing hostile objects, tracing them at different stages of flight, and (re)launching target impact facili- ties with verification of their suc- cess or failure, until the targets are hop(infrared_satellite_se nonempty(New = infr a- red(new_targets)); release( 30 Fig. 17. Launch on the remote concept split(New); frontal(Target) = VALUE; cycle( visible(Target); update(Target); hop(DE); if(try_shoot_verify(Target), done)); hop(long_range_sensors); cycle( visible(Target); update(Target); if(distsance(Target) > threshold, hop(upper_layer_shooters), hop(lower_layer_shooters)) if(try_shoot_verify(Target), done)))); The advantages of this program are that it can be initially applied to any component, automatically creating distributed command and control infrastructure particularly oriented on the currently discovered targets and dynamic situations. This automatically created distributed system organization can also self any system components mentioned above (due to fully interpreted, mobile, virus tation of DSL in distributed networked spaces). 8. Other Missile Defense-Related Tasks We will mention here some other known in the past projects related to missi currently under theoretical investigation for a possible use of SGT for their management and s mulation (if similar ones happen to emerge in the future). 8.1. Brilliant Pebbles Brilliant Pebbles [20], the top anti tions, was an attempt to deploy a 4,000 high-velocity, watermelon-sized projectiles at long where in the world. Although the program was eliminated by the Clinton Administration, the concept of Brilliant Pebbles remains among the most effective means of ballistic missile defense. Massively used distributed projectiles with DSL interpreter installed in each of them woul almost ideal test bed for the virus form and control goal-directed self vidual and collective (incl. other swarm) targets, withou 8.2. Multiple Kill Vehicles The Multiple Kill Vehicle (MKV) [21] was a planned missile defense program whose goal was to design, develop, and deploy multiple small kinetic destroy multiple ballistic missiles, including possible decoy targets (the project was canceled, same as the previous one, but its possible rebirth in the future not excluded too). The MKV co ISSN 1028-9763. �� Fig. 17. Launch on the remote concept� split(New); frontal(Target) = VALUE; visible(Target); update(Target); hop(DE); if(try_shoot_verify(Target), done)); hop(long_range_sensors); visible(Target); update(Target); if(distsance(Target) > threshold, hop(upper_layer_shooters), hop(lower_layer_shooters)) if(try_shoot_verify(Target), done)))); The advantages of this program are that it can be initially applied to any creating distributed command and control infrastructure particularly oriented on the currently discovered targets and dynamic situations. This automatically created distributed system organization can also self-recover at runtime after indiscriminate damages to any system components mentioned above (due to fully interpreted, mobile, virus etworked spaces). Any other centralized or scenarios, with different levels of detailing (like the one of “launch on r [1] depicted in fig. 17) can also be effe tively described in DSL, as experimental programming shows. (The figure shows transmission of tracking inform interceptor’s flight computer and launching the interceptor earlier and farther dow range than the ship’s own radar would a low.) Related Tasks We will mention here some other known in the past projects related to missi currently under theoretical investigation for a possible use of SGT for their management and s mulation (if similar ones happen to emerge in the future). Brilliant Pebbles [20], the top anti-missile program of the Reagan and the first Bush administr tions, was an attempt to deploy a 4,000-satellite constellation in low-Earth orbit that would fire sized projectiles at long-range ballistic missiles launched from an hough the program was eliminated by the Clinton Administration, the concept of Brilliant Pebbles remains among the most effective means of ballistic missile defense. Massively used distributed projectiles with DSL interpreter installed in each of them woul almost ideal test bed for the virus-like distributed implementation of SGT, which could easily directed self-organized distributed swarms effectively attacking both ind vidual and collective (incl. other swarm) targets, without any centralized facilities. The Multiple Kill Vehicle (MKV) [21] was a planned missile defense program whose goal was to design, develop, and deploy multiple small kinetic-energy-based warheads that can intercept and multiple ballistic missiles, including possible decoy targets (the project was canceled, same as the previous one, but its possible rebirth in the future not excluded too). The MKV co �� , 2011, � 2 The advantages of this program are that it can be initially applied to any available system creating distributed command and control infrastructure particularly oriented on the currently discovered targets and dynamic situations. This automatically created over at runtime after indiscriminate damages to any system components mentioned above (due to fully interpreted, mobile, virus-like implemen- Any other centralized or distributed scenarios, with different levels of detailing (like the one of “launch on remote concept” ig. 17) can also be effec- tively described in DSL, as experimental programming shows. (The figure shows transmission of tracking information to the interceptor’s flight computer and launching the interceptor earlier and farther down- range than the ship’s own radar would al- We will mention here some other known in the past projects related to missile defense, which are currently under theoretical investigation for a possible use of SGT for their management and si- the Reagan and the first Bush administra- Earth orbit that would fire range ballistic missiles launched from any- hough the program was eliminated by the Clinton Administration, the concept of Brilliant Pebbles remains among the most effective means of ballistic missile defense. Massively used distributed projectiles with DSL interpreter installed in each of them would be an like distributed implementation of SGT, which could easily organized distributed swarms effectively attacking both indi- t any centralized facilities. The Multiple Kill Vehicle (MKV) [21] was a planned missile defense program whose goal was to based warheads that can intercept and multiple ballistic missiles, including possible decoy targets (the project was canceled, same as the previous one, but its possible rebirth in the future not excluded too). The MKV con- ISSN 1028-9763. �� cept provided the capability for more than one kill vehicle to be launch With multiple kill vehicles on a single target "cloud" the probability for a hit on the actual wa head is enhanced. The capability of the system to intercept multiple independent targets was also planned to be tested. This, same a serve as a perfect test for the technology offered in this paper, especially for organizing collective behavior of multiple kill vehicles in highly dynamic and unpredictable situations. 8.3. Scenarios of Possible Nuclear Conflicts To investigate the power and limits of applications of the technology offered, a number of hyp thetic scenarios (far from all possible) of greater world conflicts have been programmed in DSL, like those in [22] (copied in fig. 18 without further details as may be controversial and much fa tasized for the current state of international relations, and only dynamics and possible patterns of interactions between different regions of the globe are of interest for this paper). a) c) e) Fig. 18. Examples of scenarios of possible global nuclear conflicts started by: a) mistake; b) threat; c) retaliation; d) nuclear exchange; e) invasion; f) terrorism will, which can be effectively provided by SGT (with the whole countries behaving as an integral brain, possibly even unmanned in time critical situations), could believably prevent and avoid such conflicts in real time. These and extinguish the developing nuclear madness. 9. Other Researched Applications 9.1. Emergency Management Using DSL interpreters installed in massively wearable devices may allow us to assemble ble systems from any wreckage after the disasters, using any remaining manual including [23]. These emergent systems can provide statistics of casualties, guide the delivery of relief disaster zone, as well as cooperate with �� , 2011, � 2 cept provided the capability for more than one kill vehicle to be launched from a single booster. With multiple kill vehicles on a single target "cloud" the probability for a hit on the actual wa head is enhanced. The capability of the system to intercept multiple independent targets was also planned to be tested. This, same as the previously mentioned Brilliant Pebbles project, would serve as a perfect test for the technology offered in this paper, especially for organizing collective behavior of multiple kill vehicles in highly dynamic and unpredictable situations. rios of Possible Nuclear Conflicts To investigate the power and limits of applications of the technology offered, a number of hyp thetic scenarios (far from all possible) of greater world conflicts have been programmed in DSL, ig. 18 without further details as may be controversial and much fa tasized for the current state of international relations, and only dynamics and possible patterns of interactions between different regions of the globe are of interest for this paper). b) d) f) Examples of scenarios of possible global nuclear conflicts started by: a) mistake; b) threat; c) retaliation; d) nuclear exchange; e) invasion; f) terrorism which can be effectively provided by SGT (with the whole countries behaving as an integral brain, possibly even unmanned in time critical situations), could believably prevent and avoid such conflicts in real time. These solutions can seize initiative even after the start of the conflict and extinguish the developing nuclear madness. Other Researched Applications Using DSL interpreters installed in massively wearable devices may allow us to assemble wreckage after the disasters, using any remaining communication channels, . These emergent systems can provide distributed self statistics of casualties, guide the delivery of relief goods, coordinate collective esca disaster zone, as well as cooperate with rescue teams. A world nuclear war [22] may be the one that involves most or all nuclear powers releasing a large proportion of their nuclear weapons at targets in nuclear, and perhaps non-nuclear, states. Such a war could be initiated accidentally, aggressively or pre-emptively and could continue and spread through these means or by retaliation by a party attacked by nuclear weapons. start through a reaction to terrorist attacks, or through the need to pr tect against overwhelming military opposition, or through the use of small battlefield tactical nuclear weapons meant to destroy hardened targets. The simulation in DSL shows that highly organized distributed sy tems with global consciousness and will, 31 ed from a single booster. With multiple kill vehicles on a single target "cloud" the probability for a hit on the actual war- head is enhanced. The capability of the system to intercept multiple independent targets was also s the previously mentioned Brilliant Pebbles project, would serve as a perfect test for the technology offered in this paper, especially for organizing collective behavior of multiple kill vehicles in highly dynamic and unpredictable situations. To investigate the power and limits of applications of the technology offered, a number of hypo- thetic scenarios (far from all possible) of greater world conflicts have been programmed in DSL, ig. 18 without further details as may be controversial and much fan- tasized for the current state of international relations, and only dynamics and possible patterns of interactions between different regions of the globe are of interest for this paper). which can be effectively provided by SGT (with the whole countries behaving as an integral brain, possibly even unmanned in time critical situations), could believably prevent and avoid after the start of the conflict Using DSL interpreters installed in massively wearable devices may allow us to assemble worka- communication channels, distributed self-awareness, collect goods, coordinate collective escape from the A world nuclear war [22] may be the one that involves most or all nuclear powers releasing a large proportion of their nuclear weapons at targets in nuclear, and perhaps nuclear, states. Such a war could be initiated accidentally, aggressively emptively and could continue and spread through these means or by retaliation by a party attacked by nuclear weapons. Such a war could start through a reaction to terrorist attacks, or through the need to pro- tect against overwhelming military tion, or through the use of small battlefield tactical nuclear weapons meant to destroy hardened The simulation in DSL shows that highly organized distributed sys- tems with global consciousness and 32 9.2. Distributed Avionics Implanting DSL interpreter copies into main control nodes of the aircraft may provide a intelligent, layer of its self-analysis and self ing from any point and collecting & fusing key data from other points pretation network with local, dynamic, and emergent links will be damages, especially with wireless provide global control integrity, even in a physically pleting missions. a) Crisis Management c) Electronic warfare e) Terrorism & piracy fight Fig. 19. Some other SGT applications tures and key resources, establishing protective networked mechanisms Other systems can be involved from the SGT layer for emergent covery. For example, in relation to energy infrastructures, the technology networks from the air or ground needed, directly accessing the disaster power installations, etc. 9.5. Advanced Command and Control In DSL it is possible to define high sion-making while delegating C2 routines, appearing at runtime as a derivative of environment states, to automatic interpretation. It is also convenient to retical and practical issues of advanced C2 explicitly. tures, more flexible and diverse, Some of the mentioned above SGT and DSL researched application areas as w ones are shown in fig. 19, with additional references [28 ISSN 1028-9763. �� Implanting DSL interpreter copies into main control nodes of the aircraft may provide a analysis and self-recovery, by the spreading recursive ing from any point and collecting & fusing key data from other points [24]. pretation network with local, dynamic, and emergent links will be fully functional under any damages, especially with wireless communications between the interpreters. This may always provide global control integrity, even in a physically disintegrating object, saving lives and co b) Cyber warfare d) Military avionics e) Terrorism & piracy fight Fig. 19. Some other SGT applications tures and key resources, establishing protective networked mechanisms throughout them Other systems can be involved from the SGT layer for emergent infrastructure protection and r For example, in relation to energy infrastructures, the technology can networks from the air or ground, trace electric, gas, or oil supply lines, sensing their states ( ssing the disaster zones), also providing regular or emergent sentry duties at Advanced Command and Control possible to define high-level scenarios concentrating on mission goals and top legating C2 routines, appearing at runtime as a derivative of environment states, to automatic interpretation. It is also convenient to express in retical and practical issues of advanced C2 explicitly. A variety of non-traditional tures, more flexible and diverse, had been considered in DSL [27]. Some of the mentioned above SGT and DSL researched application areas as w ig. 19, with additional references [28–38]. 9.3. Sensor Networks Wireless sensors may be dropped from the air massively, as dust”. Having a cation range, they must operate in a network to do nonlocal jobs in a distributed environment. With technology offered their emergent networks into a universal parallel computer opera ing in DSL [25] solve complex lems-from just collecting and fu ing scattered data to outlining and assembling images of the distr buted phenomena like, for exa ple, flooding, smog, birds, movement of troops, etc., analyzing their behavior and trac ing them as a whole 9.4. Infrastructure Protection Navigating the systems at runtime, the technology and integrity of �� , 2011, � 2 Implanting DSL interpreter copies into main control nodes of the aircraft may provide a higher, spreading recursive scenarios start- The embedded inter- fully functional under any the interpreters. This may always disintegrating object, saving lives and com- throughout them [26]. infrastructure protection and re- can help observe power sensing their states (and, if regular or emergent sentry duties at level scenarios concentrating on mission goals and top deci- legating C2 routines, appearing at runtime as a derivative of the mission and express in DSL any theo- traditional C2 infrastruc- Some of the mentioned above SGT and DSL researched application areas as well as other Sensor Networks Wireless sensors may be dropped from the air massively, as “smart dust”. Having a limited communi- cation range, they must operate in a network to do nonlocal jobs in a distributed environment. With the technology offered, we can convert their emergent networks into a universal parallel computer operat- 5]. It can effectively solve complex distributed prob- from just collecting and fus- ing scattered data to outlining and assembling images of the distri- buted phenomena like, for exam- ple, flooding, smog, flocks of birds, movement of troops, etc., their behavior and track- a whole. . Infrastructure Protection Navigating the systems at runtime, can analyze safety and integrity of critical infrastruc- ISSN 1028-9763. �� , 2011, � 2 33 10. Conclusions We have described a novel ideology and the supporting Spatial Grasp Technology (SGT) for high-level management of distributed dynamic systems that can be useful for advanced air and missile defense. SGT, among others, offers the following possibilities: • Many targets can be simultaneously captured over the defended area and individually followed & studied by spreading mobile intelligence propagating in networked space (between limited range radars). • SGT can analyze many moving targets in parallel and cooperatively, discovering, whether this is individual or swarm attack, and properly orienting the global system response. • In case of multiple targets and limited physical resources, SGT can globally assess which targets are most important to shoot. • Based on full interpretation of flexible mission scenarios (which can re-launch their parts or the whole) the distributed air & missile defense system can remain fully operational after any indiscriminate damages. • SGT can operate in both live and simulation modes, with runtime simulation of evolving events serving as look-ahead facility for live control. • SGT can take full responsibility for key decisions in most critical situations, excluding, if needed, humans from the control loop. The ideology and technology developed can convert any distributed system into an integral dynamic brain which can quickly assess and withstand asymmetric situations and threats, protect critical infrastructures, win local and global conflicts, as well as avoid and terminate them at different stages of their development. REFERENCES 1. Ballistic Missile Defense Review Report. – US Department of Defense. – 2010. – Feb. – �� - �� : http://www.defense.gov/bmdr/docs/BMDR%20as%20of%2026JAN10%200630_for%20web.pdf. 2. Proc. International Symposium on Air Defense 2020+ [�� ]. – �� : http://www.isad2020.org.sa/english/online.php. 3. Sapaty P.S. Distributed Technology for Global Control / P.S. Sapaty // Book chapter, Lecture Notes in Electrical Engineering. – 2009. – Vol. 37. – . 3 – 24. 4. Sapaty . Ruling Distributed Dynamic Worlds / Sapaty . – New York: John Wiley & Sons, 2005. – 256 p. 5. Sapaty . 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High-Level Technology to Manage Distributed Robotized Systems / Sapaty . // Military Robotics. – London UK, 2010. – 85 p. 13. Sapaty P. Spatial Scenarios for Distributed Unmanned Systems / P. Sapaty, M. Sugisaka, K.-D. Kuh- nert // Proc. AUVSI’s Unmanned Systems North America 2009. – Washington, DC, USA, 2009. – 16 p. 14. Sapaty P.S. Providing Spatial Integrity For Distributed Unmanned Systems / P.S. Sapaty // Proc. 6th International Conference in Control, Automation and Robotics ICINCO 2009. – Milan, Italy, 2009. – 12 p. 15. Sapaty P.S. Meeting the World Challenges: From Philosophy to Information technology to Applica- tions / P.S. Sapaty // Keynote lecture, Proc. 6th International Conference in Control, Automation and Ro- botics ICINCO 2009. – Milan, Italy, 2009. – 15 p. 34 ISSN 1028-9763. �� , 2011, � 2 16. Sapaty P. DEW in a Network Enabled Environment / P. Sapaty, A. Morozov, M. 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Six Escalation Scenarios Spiraling World to Nuclear War [�� ] / C. Moore. – �� : http://www.carolmoore.net/nuclearwar/alternatescenarios.html. 23. Advanced IT Support of Crisis Relief Missions / P. Sapaty, M. Sugisaka, R. Finkelstein [et al.] // Jour- nal of Emergency Management. – 2006. – Vol. 4, N 4. – P. 29 – 36. 24. Sapaty P. Grasping the Whole by Spatial Intelligence: A Higher Level for Distributed Avionics / P. Sapaty // Proc. Military Avionics. – London, UK, 2008. – 52 p. 25. Sapaty P. Intelligent Management of Distributed Sensor Networks / P. Sapaty // Sensors and Com- mand, Control, Communications and Intelligence (C3I) Technologies for Homeland Security and Homel- and Defense VI. Proc. SPIE. – 2007. – Vol. 6538, N 653812. – P. 45 – 52. 26. Sapaty P. Gestalt-Based Integrity of Distributed Networked Systems / P. Sapaty // SPIE Europe Secu- rity + Defence, bcc Berliner Congress Centre. – Berlin, Germany, 2009. – P. 63 – 70. 27. A New Concept of Flexible Organization for Distributed Robotized Systems / P. Sapaty, A. Morozov, R. Finkelstein [et al.] // Proc. Twelfth International Symposium on Artificial Life and Robotics (AROB 12th’07). – Beppu, Japan, 2007. – Jan 25–27. – 7 p. 28. Sapaty P. Countering Asymmetric Situations with Distributed Artificial Life and Robotics Approach / P. Sapaty, M. Sugisaka // Proc. Fifteenth International Symposium on Artificial Life and Robotics (AROB 15th’10). – Beppu, Oita, Japan: B-Con Plaza, 2010. – Feb. 5–7. – 5 p. 29. Sapaty P. Distributed Capability for Battlespace Dominance / P. Sapaty // Proc. Electronic Warfare 2009 Conference & Exhibition. – London, UK, 2009. – 54 p. 30. Developing High-Level Management Facilities for Distributed Unmanned Systems / P. Sapaty, K.-D. Kuhnert, M. Sugisaka [et al.] // Proc. Fourteenth International Symposium on Artificial Life and Robotics (AROB 14th’09). – Beppu, Japan: B-Con Plaza, 2009. – Feb. 5–7. – 7 p. 31. Sapaty P. Distributed Technology for Global Dominance / P. Sapaty // Proc. SPIE. Defense Transfor- mation and Net-Centric Systems. – 2008. – Vol. 6981, N 69810T. – P. 33 – 41. 32. Intelligent management of distributed dynamic sensor networks / P. Sapaty, M. Sugisaka, J. Delgado- Frias [et al.] // Artificial Life and Robotics. – 2008. – Vol. 12, N 1–2. – P. 51 – 59. 33. Sapaty P. Global Management of Distributed EW-Related System / P. Sapaty // Proc. Electronic War- fare: Operations & Systems. – London, UK, 2007. – 44 p. 34. Grasping the Distributed Entirety / P. Sapaty, M. Sugisaka, N. Mirenkov [et al.] // Proc. Tenth Interna- tional Symposium on Artificial Life and Robotics (AROB 10th). – Beppu, Japan, 2005. – Feb. 4–6. – 6 p. 35. Sapaty P. Dynamic Air Traffic Management Using Distributed Brain Concept / P. Sapaty, V. Klimen- ko, M. Sugisaka // Proc. Ninth International Symposium on Artificial Life and Robotics (AROB 9th). – Beppu, Japan, 2004. – January. – 7 p. 36. Sapaty P. Optimized Space Search by Distributed Robotic Teams / P. Sapaty, M. Sugisaka // Proc. World Symposium Unmanned Systems. – Baltimore Convention Center, USA, 2003. – Jul. 15–17. – 12 p. 37. Sapaty P. Universal Distributed Brain for Mobile Multi-robot Systems / P. Sapaty, M. Sugisaka // Book chapter in Distributed Autonomous Robotic Systems. –Tokyo: Sringer-Verlag, 2002. – P. 26 – 34. 38. Sapaty P.S. Mobile Intelligence in Distributed Simulations / P.S. Sapaty, M.J. Corbin, S. Seidensticker // Proc. 14th Workshop on Standards for the Interoperability of Distributed Simulations. – Orlando: IST UCF, FL, 1995. – March. – 12 p. �� "�� 28.02.2011
id	nasplib_isofts_kiev_ua-123456789-83509
institution	Digital Library of Periodicals of National Academy of Sciences of Ukraine
issn	1028-9763
language	English
last_indexed	2025-12-02T00:14:10Z
publishDate	2011
publisher	Інститут проблем математичних машин і систем НАН України
record_format	dspace
spelling	Sapaty, P.S. 2015-06-20T08:22:36Z 2015-06-20T08:22:36Z 2011 Air & missile defense with spatial grasp technology / P.S. Sapaty // Мат. машини і системи. — 2011. — № 2. — С. 19-34. — Бібліогр.: 38 назв. — англ. 1028-9763 https://nasplib.isofts.kiev.ua/handle/123456789/83509 623.764 A high-level technology is revealed which can effectively convert any distributed system into a globally programmable spatial machine capable of operating without any central resources and self-recovering from indiscriminate damages. Integral mission scenarios in Distributed Scenario Language (DSL) can be injected from any point, runtime covering & grasping the whole system or its parts, setting operational infrastructures and orienting local and global behavior in the way needed. Distributed DSL interpreter organization and benefits of using this technology for integrated air and missile defense are discussed along with programming examples in this and other fields. Зображена високорівнева технологія, яка ефективно перетворює довільну розподілену систему на універсальну, глобально програмовану просторову машину, спроможну вирішувати складні задачі без центральних засобів та самовідновлюватись від пошкоджень у реальному часі. Системні місії задаються на спеціальній Мові Розподілених Сценаріїв (МРС), яка інтерпретується в високопаралельному та повністю розподіленому режимі. Структура мережевого інтерпретатора з МРС і заплановане використання технології для інтелектуальних розподілених систем протиповітряної та протиракетної оборони викладені разом з прикладами вирішення практичних задач у цій та інших областях. Описана высокоуровневая технология, эффективно превращающая любую распределенную систему в универсальную, глобально программируемую пространственную машину, способную решать сложные задачи без центральных устройств и самовосстанавливаться от повреждений в реальном времени. Системные миссии задаются на специальном Языке Распределенных Сценариев (ЯРС), который интепретируется в высокопараллельном и полностью распределенном режиме. Структура сетевого интерпретатора с ЯРС и планируемое применение технологии для интеллектуальных распределенных систем противовоздушной и противоракетной обороны изложены вместе с примерами решения практических задач в этой и других областях. en Інститут проблем математичних машин і систем НАН України Математичні машини і системи Нові інформаційні і телекомунікаційні технології Air & missile defense with spatial grasp technology Протиповітряна та протиракетна оборона на базі технології просторового захвату Противовоздушная и противоракетная оборона на базе технологии пространственного захвата Article published earlier
spellingShingle	Air & missile defense with spatial grasp technology Sapaty, P.S. Нові інформаційні і телекомунікаційні технології
title	Air & missile defense with spatial grasp technology
title_alt	Протиповітряна та протиракетна оборона на базі технології просторового захвату Противовоздушная и противоракетная оборона на базе технологии пространственного захвата
title_full	Air & missile defense with spatial grasp technology
title_fullStr	Air & missile defense with spatial grasp technology
title_full_unstemmed	Air & missile defense with spatial grasp technology
title_short	Air & missile defense with spatial grasp technology
title_sort	air & missile defense with spatial grasp technology
topic	Нові інформаційні і телекомунікаційні технології
topic_facet	Нові інформаційні і телекомунікаційні технології
url	https://nasplib.isofts.kiev.ua/handle/123456789/83509
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Air & missile defense with spatial grasp technology

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