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Self-Aware Computing Systems.

By: Kounev, Samuel.
Contributor(s): Kephart, Jeffrey O | Milenkoski, Aleksandar | Zhu, Xiaoyun.
Material type: TextTextSeries: eBooks on Demand.Publisher: Cham : Springer International Publishing, 2017Copyright date: ©2017Description: 1 online resource (720 pages).Content type: text Media type: computer Carrier type: online resourceISBN: 9783319474748.Subject(s): Computer scienceGenre/Form: Electronic books.Additional physical formats: Print version:: Self-Aware Computing SystemsDDC classification: 4 Online resources: Click here to view this ebook.
Contents:
Preface -- Background -- Content -- Intended Readership -- Contents -- Contributors -- Part I Introduction -- 1 The Notion of Self-aware Computing -- 1.1 Introduction -- 1.2 Definition of Self-aware Computing -- 1.3 Previous Initiatives in Self-aware Computing -- 1.3.1 Self-awareness in Artificial Intelligence -- 1.3.2 Engineering Self-aware Systems -- 1.3.3 Self-awareness in Pervasive Computing -- 1.3.4 Systems with Decentralized Self-awareness -- 1.3.5 Computational Self-awareness -- 1.4 A Concept of a Self-aware Learning and Reasoning Loop -- 1.5 Conclusion -- References -- 2 Self-aware Computing Systems: Related Concepts and Research Areas -- 2.1 Introduction -- 2.2 Control -- 2.3 Artificial Intelligence -- 2.3.1 Overview of Agents and Multi-agent Systems -- 2.3.2 Comparison with Self-aware Computing -- 2.4 Autonomic Computing -- 2.5 Organic Computing -- 2.6 Service-Based Systems and Cloud Computing -- 2.6.1 Service-Based Systems -- 2.6.2 Cloud Computing -- 2.6.3 Comparison with Self-aware Computing -- 2.7 Self-organizing Systems -- 2.7.1 Overview of Self-organizing Systems -- 2.7.2 Cross-pollination Opportunities with Self-aware Computing -- 2.8 Self-adaptive Systems -- 2.8.1 Overview of Basic Self-adaptive Systems -- 2.8.2 Anticipatory Self-adaptive Systems -- 2.9 Reflective Computing -- 2.10 Models@run.time and Reflection -- 2.11 Situation-Aware Systems and Context Awareness -- 2.12 Symbiotic Cognitive Computing -- 2.13 Auto-tuning -- 2.14 Constructive Definition -- 2.15 Summary -- References -- 3 Towards a Framework for the Levels and Aspects of Self-aware Computing Systems -- 3.1 Introduction -- 3.1.1 Why Consider Types of Self-awareness in Computing Systems? -- 3.1.2 Summary of This Chapter -- 3.2 Fundamentals, Inspiration, and Interpretations in Computing -- 3.2.1 What Is Self-awareness? -- 3.2.2 Interpretations and Applications.
3.3 A Conceptual Framework -- 3.3.1 Overarching Levels of Self-awareness -- 3.3.2 Aspects of Reflective and Meta-reflective Self-awareness -- 3.3.3 Domain of Self-awareness -- 3.3.4 Putting It All Together -- 3.4 Self-awareness and Goals -- 3.5 Challenges -- References -- 4 Reference Scenarios for Self-aware Computing -- 4.1 Introduction -- 4.2 Rationale -- 4.3 Adaptive Sorting -- 4.3.1 Scenario -- 4.3.2 Key Questions -- 4.4 Data Center Resource Management -- 4.4.1 Scenario -- 4.4.2 Key Questions -- 4.5 Cyber-Physical Systems -- 4.5.1 Thermostat -- 4.5.2 Smart Home -- 4.5.3 Smart Micro-grid -- 4.5.4 System of Autonomous Shuttles -- 4.6 Conclusion -- References -- Part II System Architectures -- 5 Architectural Concepts for Self-aware Computing Systems -- 5.1 Introduction -- 5.2 Preliminaries -- 5.2.1 Running Example: Smart Home -- 5.2.2 Architectural Modeling with UML -- 5.2.3 Self-awareness Terminology and Framework -- 5.3 Architectural Elements for Self-awareness -- 5.3.1 System, Environmental Context, and Modules -- 5.3.2 Reflective and Prereflective Processes -- 5.3.3 Awareness Models, Empirical Data (Models), and Goal Models -- 5.4 Architectural Relations for Self-awareness -- 5.4.1 Data Flow Related to Self-awareness -- 5.4.2 Awareness and Expression Links -- 5.5 Self-awareness and Architecture -- 5.5.1 Self-awareness: Awareness of the Context -- 5.5.2 Self-awareness: Awareness of Its Own Elements -- 5.5.3 Self-loops and Cyclic Self-awareness -- 5.5.4 Meta-Self-awareness -- 5.6 Discussion -- 5.6.1 Architectural Views -- 5.6.2 Coverage -- 5.7 Conclusion -- References -- 6 Generic Architectures for Individual Self-aware Computing Systems -- 6.1 Introduction -- 6.2 Preliminaries -- 6.2.1 Running Example: Smart Home -- 6.2.2 Self-awareness Terminology, Framework, and Notation -- 6.3 Pre-reflective Self-awareness.
6.3.1 Encapsulated Access to the Pre-reflective Subsystem -- 6.3.2 Direct Access to the Pre-reflective Subsystem -- 6.3.3 Summary -- 6.4 Reflective Self-awareness -- 6.4.1 Local Reflection -- 6.4.2 Hierarchical and Centralized Reflection -- 6.4.3 Coordinated Reflection -- 6.4.4 Summary -- 6.5 Meta-reflective Self-awareness -- 6.5.1 Hierarchical and Centralized Meta-Reflection -- 6.5.2 Hierarchical and Centralized Meta--Meta-Reflection -- 6.5.3 Summary -- 6.6 Discussion -- 6.6.1 Control Schemes -- 6.6.2 Architectural Styles: The External and Internal Approaches -- 6.7 Conclusion -- References -- 7 Architectures for Collective Self-aware Computing Systems -- 7.1 Introduction -- 7.1.1 Chapter Overview -- 7.1.2 Chapter Organisation -- 7.1.3 Meta-Architecture Overview -- 7.2 Definitions and Notations for Collectives -- 7.3 The Self-awareness of Collectives -- 7.3.1 General Considerations -- 7.3.2 Collective Self-awareness and Self-aware Collectives -- 7.3.3 Approaches for Achieving Self-aware Collectives -- 7.4 Self-awareness Levels -- 7.4.1 Collective Self-awareness Based on System Self-awareness -- 7.4.2 Dynamic Self-awareness Changes in the Collective -- 7.5 Types of Relations -- 7.5.1 Goals -- 7.5.2 Knowledge -- 7.5.3 Acting -- 7.6 Organisation Patterns -- 7.6.1 Overview of Organisation Patterns -- 7.6.2 Hierarchical Collective -- 7.6.3 Peer-to-Peer Collective -- 7.6.4 Stigmergic Collective -- 7.6.5 Pattern Composition and Encapsulation -- 7.7 Developing the Architecture of Collective Self-aware Systems -- 7.7.1 Viable Architectures -- 7.7.2 Navigating the Meta-Architectural Space -- 7.8 Conclusions -- References -- 8 State of the Art in Architectures for Self-aware Computing Systems -- 8.1 Introduction -- 8.2 Reference Architectures -- 8.2.1 MAPE-K Loop -- 8.2.2 Reference Architecture for Self-managed Systems.
8.2.3 Reference Architecture for Models@run.time Systems -- 8.2.4 Organic Computing -- 8.2.5 Requirements-Awareness -- 8.2.6 Decentralized Architectures from AI and MAS -- 8.3 Architectural Frameworks and Languages -- 8.3.1 Reflective Architectures -- 8.3.2 Mechatronic UML -- 8.3.3 MUSIC -- 8.3.4 ExecUtable RuntimE MegAmodels (EUREMA) -- 8.3.5 Multi-Quality Auto-Tuning (MQuAT) -- 8.3.6 Descartes Modeling Language (DML) -- 8.4 Open Challenges -- 8.5 Conclusion -- References -- Part III Methods and Algorithms -- 9 Self-modeling and Self-awareness -- 9.1 Introduction -- 9.1.1 Self-modeling -- 9.1.2 Motivation -- 9.2 Background -- 9.2.1 The DDDAS Program -- 9.2.2 Models@run.time -- 9.2.3 Situation Awareness -- 9.2.4 Reflection -- 9.3 CARS: An Extended Example -- 9.4 Modeling Issues -- 9.4.1 Modeling Questions -- 9.5 Data Analytics -- 9.5.1 Grammatical Inference -- 9.5.2 Other Mathematical Methods -- 9.5.3 Supporting Processes -- 9.6 Challenges -- 9.6.1 Language as a Challenge -- 9.6.2 The i-Room -- 9.7 Conclusions and Prospects -- References -- 10 Transition Strategies for Increasing Self-awareness in Existing Types of Computing Systems -- 10.1 Introduction -- 10.2 Capabilities and Functions of Self-aware Systems: An Overview -- 10.3 Computing Systems Analysis -- 10.3.1 Existing Distributed Systems Architectures -- 10.3.2 Service-Based Systems (SBSs) -- 10.3.3 Systems-of-Systems (SoSs) -- 10.3.4 Multiagent Systems (MASs) -- 10.3.5 Cloud Computing -- 10.3.6 Pervasive Computing -- 10.4 Transition Strategies -- 10.4.1 Transition Strategies in Service-Based Systems (SBSs) -- 10.4.2 Transition Strategies in Multiagent Systems (MASs) -- 10.5 Example of Transition Strategies: Smart Home Case Study -- 10.6 Conclusions and Open Challenges -- References -- 11 Synthesis and Verification of Self-aware Computing Systems -- 11.1 Introduction.
11.2 From Design-Time to Run-Time Synthesis of Self-aware Choreographies of Software Services -- 11.2.1 Setting the Context -- 11.2.2 The Need for Self-adaptation -- 11.2.3 Method for the Synthesis of Self-adaptable Choreographies -- 11.2.4 Dealing with Choreography Self-adaptation -- 11.2.5 Case Study -- 11.3 Synthesis of Self-adaptive Connectors Meeting Behavioral and Quality Requirements -- 11.3.1 QB-Synthesis: Quality and Behavioral Connector Synthesis -- 11.3.2 QB-Synthesis of Self-adaptive Connector -- 11.3.3 Open Issues -- 11.4 Quantitative Verification at Run-Time -- 11.4.1 Application to Self-aware Systems -- 11.4.2 Research Challenges -- 11.5 Parametric Verification -- 11.5.1 Parametric Markov Chains -- 11.5.2 State of the Art -- 11.5.3 Parameter Synthesis -- 11.5.4 Model Repair -- 11.6 Run-Time Verification and Probabilistic Models -- 11.7 Analysis and Synthesis of Self-adaptation Exploiting Environment Assumptions -- 11.7.1 Model Checking Stochastic Games -- 11.7.2 Reasoning About Self-adaptation Using Stochastic Games -- 11.7.3 From Design-Time Analysis to Run-Time Synthesis -- 11.8 Summary -- References -- 12 Self-adaptation for Individual Self-aware Computing Systems -- 12.1 Introduction -- 12.2 What Drives Adaptation? -- 12.2.1 Adapting to Changes in High-Level Goals -- 12.2.2 Adapting to Changes in the System -- 12.2.3 Adapting to Changes in the Environment -- 12.3 Adaptation Techniques -- 12.3.1 Control Theory -- 12.3.2 Machine Learning -- 12.3.3 Optimization and Operations Research -- 12.4 Adaptation Evaluation -- 12.5 Interaction of Different Adaptation Strategies -- 12.6 Conclusion -- References -- 13 Self-adaptation in Collective Self-aware Computing Systems -- 13.1 Introduction -- 13.2 Actions -- 13.2.1 Scenarios -- 13.2.2 Mitigating Undesirable Collective Behaviors -- 13.2.3 Capitalizing on Desirable Collective Behaviors.
13.3 Reasoning and Goals.
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Item type Current location Call number URL Status Date due Barcode
Electronic Book UT Tyler Online
Online
QA76.S45 2017 (Browse shelf) http://ebookcentral.proquest.com/lib/uttyler/detail.action?docID=4790540 Available EBC4790540

Preface -- Background -- Content -- Intended Readership -- Contents -- Contributors -- Part I Introduction -- 1 The Notion of Self-aware Computing -- 1.1 Introduction -- 1.2 Definition of Self-aware Computing -- 1.3 Previous Initiatives in Self-aware Computing -- 1.3.1 Self-awareness in Artificial Intelligence -- 1.3.2 Engineering Self-aware Systems -- 1.3.3 Self-awareness in Pervasive Computing -- 1.3.4 Systems with Decentralized Self-awareness -- 1.3.5 Computational Self-awareness -- 1.4 A Concept of a Self-aware Learning and Reasoning Loop -- 1.5 Conclusion -- References -- 2 Self-aware Computing Systems: Related Concepts and Research Areas -- 2.1 Introduction -- 2.2 Control -- 2.3 Artificial Intelligence -- 2.3.1 Overview of Agents and Multi-agent Systems -- 2.3.2 Comparison with Self-aware Computing -- 2.4 Autonomic Computing -- 2.5 Organic Computing -- 2.6 Service-Based Systems and Cloud Computing -- 2.6.1 Service-Based Systems -- 2.6.2 Cloud Computing -- 2.6.3 Comparison with Self-aware Computing -- 2.7 Self-organizing Systems -- 2.7.1 Overview of Self-organizing Systems -- 2.7.2 Cross-pollination Opportunities with Self-aware Computing -- 2.8 Self-adaptive Systems -- 2.8.1 Overview of Basic Self-adaptive Systems -- 2.8.2 Anticipatory Self-adaptive Systems -- 2.9 Reflective Computing -- 2.10 Models@run.time and Reflection -- 2.11 Situation-Aware Systems and Context Awareness -- 2.12 Symbiotic Cognitive Computing -- 2.13 Auto-tuning -- 2.14 Constructive Definition -- 2.15 Summary -- References -- 3 Towards a Framework for the Levels and Aspects of Self-aware Computing Systems -- 3.1 Introduction -- 3.1.1 Why Consider Types of Self-awareness in Computing Systems? -- 3.1.2 Summary of This Chapter -- 3.2 Fundamentals, Inspiration, and Interpretations in Computing -- 3.2.1 What Is Self-awareness? -- 3.2.2 Interpretations and Applications.

3.3 A Conceptual Framework -- 3.3.1 Overarching Levels of Self-awareness -- 3.3.2 Aspects of Reflective and Meta-reflective Self-awareness -- 3.3.3 Domain of Self-awareness -- 3.3.4 Putting It All Together -- 3.4 Self-awareness and Goals -- 3.5 Challenges -- References -- 4 Reference Scenarios for Self-aware Computing -- 4.1 Introduction -- 4.2 Rationale -- 4.3 Adaptive Sorting -- 4.3.1 Scenario -- 4.3.2 Key Questions -- 4.4 Data Center Resource Management -- 4.4.1 Scenario -- 4.4.2 Key Questions -- 4.5 Cyber-Physical Systems -- 4.5.1 Thermostat -- 4.5.2 Smart Home -- 4.5.3 Smart Micro-grid -- 4.5.4 System of Autonomous Shuttles -- 4.6 Conclusion -- References -- Part II System Architectures -- 5 Architectural Concepts for Self-aware Computing Systems -- 5.1 Introduction -- 5.2 Preliminaries -- 5.2.1 Running Example: Smart Home -- 5.2.2 Architectural Modeling with UML -- 5.2.3 Self-awareness Terminology and Framework -- 5.3 Architectural Elements for Self-awareness -- 5.3.1 System, Environmental Context, and Modules -- 5.3.2 Reflective and Prereflective Processes -- 5.3.3 Awareness Models, Empirical Data (Models), and Goal Models -- 5.4 Architectural Relations for Self-awareness -- 5.4.1 Data Flow Related to Self-awareness -- 5.4.2 Awareness and Expression Links -- 5.5 Self-awareness and Architecture -- 5.5.1 Self-awareness: Awareness of the Context -- 5.5.2 Self-awareness: Awareness of Its Own Elements -- 5.5.3 Self-loops and Cyclic Self-awareness -- 5.5.4 Meta-Self-awareness -- 5.6 Discussion -- 5.6.1 Architectural Views -- 5.6.2 Coverage -- 5.7 Conclusion -- References -- 6 Generic Architectures for Individual Self-aware Computing Systems -- 6.1 Introduction -- 6.2 Preliminaries -- 6.2.1 Running Example: Smart Home -- 6.2.2 Self-awareness Terminology, Framework, and Notation -- 6.3 Pre-reflective Self-awareness.

6.3.1 Encapsulated Access to the Pre-reflective Subsystem -- 6.3.2 Direct Access to the Pre-reflective Subsystem -- 6.3.3 Summary -- 6.4 Reflective Self-awareness -- 6.4.1 Local Reflection -- 6.4.2 Hierarchical and Centralized Reflection -- 6.4.3 Coordinated Reflection -- 6.4.4 Summary -- 6.5 Meta-reflective Self-awareness -- 6.5.1 Hierarchical and Centralized Meta-Reflection -- 6.5.2 Hierarchical and Centralized Meta--Meta-Reflection -- 6.5.3 Summary -- 6.6 Discussion -- 6.6.1 Control Schemes -- 6.6.2 Architectural Styles: The External and Internal Approaches -- 6.7 Conclusion -- References -- 7 Architectures for Collective Self-aware Computing Systems -- 7.1 Introduction -- 7.1.1 Chapter Overview -- 7.1.2 Chapter Organisation -- 7.1.3 Meta-Architecture Overview -- 7.2 Definitions and Notations for Collectives -- 7.3 The Self-awareness of Collectives -- 7.3.1 General Considerations -- 7.3.2 Collective Self-awareness and Self-aware Collectives -- 7.3.3 Approaches for Achieving Self-aware Collectives -- 7.4 Self-awareness Levels -- 7.4.1 Collective Self-awareness Based on System Self-awareness -- 7.4.2 Dynamic Self-awareness Changes in the Collective -- 7.5 Types of Relations -- 7.5.1 Goals -- 7.5.2 Knowledge -- 7.5.3 Acting -- 7.6 Organisation Patterns -- 7.6.1 Overview of Organisation Patterns -- 7.6.2 Hierarchical Collective -- 7.6.3 Peer-to-Peer Collective -- 7.6.4 Stigmergic Collective -- 7.6.5 Pattern Composition and Encapsulation -- 7.7 Developing the Architecture of Collective Self-aware Systems -- 7.7.1 Viable Architectures -- 7.7.2 Navigating the Meta-Architectural Space -- 7.8 Conclusions -- References -- 8 State of the Art in Architectures for Self-aware Computing Systems -- 8.1 Introduction -- 8.2 Reference Architectures -- 8.2.1 MAPE-K Loop -- 8.2.2 Reference Architecture for Self-managed Systems.

8.2.3 Reference Architecture for Models@run.time Systems -- 8.2.4 Organic Computing -- 8.2.5 Requirements-Awareness -- 8.2.6 Decentralized Architectures from AI and MAS -- 8.3 Architectural Frameworks and Languages -- 8.3.1 Reflective Architectures -- 8.3.2 Mechatronic UML -- 8.3.3 MUSIC -- 8.3.4 ExecUtable RuntimE MegAmodels (EUREMA) -- 8.3.5 Multi-Quality Auto-Tuning (MQuAT) -- 8.3.6 Descartes Modeling Language (DML) -- 8.4 Open Challenges -- 8.5 Conclusion -- References -- Part III Methods and Algorithms -- 9 Self-modeling and Self-awareness -- 9.1 Introduction -- 9.1.1 Self-modeling -- 9.1.2 Motivation -- 9.2 Background -- 9.2.1 The DDDAS Program -- 9.2.2 Models@run.time -- 9.2.3 Situation Awareness -- 9.2.4 Reflection -- 9.3 CARS: An Extended Example -- 9.4 Modeling Issues -- 9.4.1 Modeling Questions -- 9.5 Data Analytics -- 9.5.1 Grammatical Inference -- 9.5.2 Other Mathematical Methods -- 9.5.3 Supporting Processes -- 9.6 Challenges -- 9.6.1 Language as a Challenge -- 9.6.2 The i-Room -- 9.7 Conclusions and Prospects -- References -- 10 Transition Strategies for Increasing Self-awareness in Existing Types of Computing Systems -- 10.1 Introduction -- 10.2 Capabilities and Functions of Self-aware Systems: An Overview -- 10.3 Computing Systems Analysis -- 10.3.1 Existing Distributed Systems Architectures -- 10.3.2 Service-Based Systems (SBSs) -- 10.3.3 Systems-of-Systems (SoSs) -- 10.3.4 Multiagent Systems (MASs) -- 10.3.5 Cloud Computing -- 10.3.6 Pervasive Computing -- 10.4 Transition Strategies -- 10.4.1 Transition Strategies in Service-Based Systems (SBSs) -- 10.4.2 Transition Strategies in Multiagent Systems (MASs) -- 10.5 Example of Transition Strategies: Smart Home Case Study -- 10.6 Conclusions and Open Challenges -- References -- 11 Synthesis and Verification of Self-aware Computing Systems -- 11.1 Introduction.

11.2 From Design-Time to Run-Time Synthesis of Self-aware Choreographies of Software Services -- 11.2.1 Setting the Context -- 11.2.2 The Need for Self-adaptation -- 11.2.3 Method for the Synthesis of Self-adaptable Choreographies -- 11.2.4 Dealing with Choreography Self-adaptation -- 11.2.5 Case Study -- 11.3 Synthesis of Self-adaptive Connectors Meeting Behavioral and Quality Requirements -- 11.3.1 QB-Synthesis: Quality and Behavioral Connector Synthesis -- 11.3.2 QB-Synthesis of Self-adaptive Connector -- 11.3.3 Open Issues -- 11.4 Quantitative Verification at Run-Time -- 11.4.1 Application to Self-aware Systems -- 11.4.2 Research Challenges -- 11.5 Parametric Verification -- 11.5.1 Parametric Markov Chains -- 11.5.2 State of the Art -- 11.5.3 Parameter Synthesis -- 11.5.4 Model Repair -- 11.6 Run-Time Verification and Probabilistic Models -- 11.7 Analysis and Synthesis of Self-adaptation Exploiting Environment Assumptions -- 11.7.1 Model Checking Stochastic Games -- 11.7.2 Reasoning About Self-adaptation Using Stochastic Games -- 11.7.3 From Design-Time Analysis to Run-Time Synthesis -- 11.8 Summary -- References -- 12 Self-adaptation for Individual Self-aware Computing Systems -- 12.1 Introduction -- 12.2 What Drives Adaptation? -- 12.2.1 Adapting to Changes in High-Level Goals -- 12.2.2 Adapting to Changes in the System -- 12.2.3 Adapting to Changes in the Environment -- 12.3 Adaptation Techniques -- 12.3.1 Control Theory -- 12.3.2 Machine Learning -- 12.3.3 Optimization and Operations Research -- 12.4 Adaptation Evaluation -- 12.5 Interaction of Different Adaptation Strategies -- 12.6 Conclusion -- References -- 13 Self-adaptation in Collective Self-aware Computing Systems -- 13.1 Introduction -- 13.2 Actions -- 13.2.1 Scenarios -- 13.2.2 Mitigating Undesirable Collective Behaviors -- 13.2.3 Capitalizing on Desirable Collective Behaviors.

13.3 Reasoning and Goals.

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