The complexity of large distributed systems makes the monitoring, necessary for self governance and autonomic functions, very problematic. Systems will be ordered hierarchically, consisting of systems of systems. Furthermore a system may be constructed from systems that are fundamentally different in topology from itself. This means that a monitoring strategy that is successful in one part of the system will not necessarily perform well in another system sector. This work considers a phase transition through four system topologies, observed to occur in the evolution of many self organising systems, starting at a regular circular 2D lattice to a scale-free phase. The best monitoring strategy for a scale-free system is considered with a form of acquaintance monitoring proposed. Thus when a system is observed to be acting in a scale-free manner the most suitable monitoring strategy can be deployed. This paper presents two applications that use the results of this work to monitor and influence distinct layers in network topologies
{"title":"Using Signatures of Self-Organisation for Monitoring and Influencing Large Scale Autonomic Systems","authors":"A. Taleb-Bendiab, P. Miseldine, D. Lamb","doi":"10.1109/EASE.2007.30","DOIUrl":"https://doi.org/10.1109/EASE.2007.30","url":null,"abstract":"The complexity of large distributed systems makes the monitoring, necessary for self governance and autonomic functions, very problematic. Systems will be ordered hierarchically, consisting of systems of systems. Furthermore a system may be constructed from systems that are fundamentally different in topology from itself. This means that a monitoring strategy that is successful in one part of the system will not necessarily perform well in another system sector. This work considers a phase transition through four system topologies, observed to occur in the evolution of many self organising systems, starting at a regular circular 2D lattice to a scale-free phase. The best monitoring strategy for a scale-free system is considered with a form of acquaintance monitoring proposed. Thus when a system is observed to be acting in a scale-free manner the most suitable monitoring strategy can be deployed. This paper presents two applications that use the results of this work to monitor and influence distinct layers in network topologies","PeriodicalId":239972,"journal":{"name":"Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems (EASe'07)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116810766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We outline a potential approach to the development of future autonomic NASA space exploration missions. The approach is quite different from other efforts to date, and is inspired by the human immunological system and exploits agent-based technologies to support autonomic features such as: self-managing, self-configuring, self-healing, self-optimizing, self-protecting, and finally two novel features of future NASA swarm-based missions: self-predicting and self-learning, which may help in extending levels of autonomy in future missions. The approach offers several detection mechanisms for recognizing self and non-self patterns. This sense of "self" of the immunological system is related to the ability to learn to recognize new kinds of threats. The hierarchical architecture based on agents offers a high flexibility for repairing, maintaining, configuring, and optimizing functions of the spacecraft in real time
{"title":"Asteroid Exploration with Autonomic Systems A Biologically-Inspired Approach based on the Immunological System","authors":"O. Flórez-Choque, M. Hinchey","doi":"10.1109/EASE.2007.5","DOIUrl":"https://doi.org/10.1109/EASE.2007.5","url":null,"abstract":"We outline a potential approach to the development of future autonomic NASA space exploration missions. The approach is quite different from other efforts to date, and is inspired by the human immunological system and exploits agent-based technologies to support autonomic features such as: self-managing, self-configuring, self-healing, self-optimizing, self-protecting, and finally two novel features of future NASA swarm-based missions: self-predicting and self-learning, which may help in extending levels of autonomy in future missions. The approach offers several detection mechanisms for recognizing self and non-self patterns. This sense of \"self\" of the immunological system is related to the ability to learn to recognize new kinds of threats. The hierarchical architecture based on agents offers a high flexibility for repairing, maintaining, configuring, and optimizing functions of the spacecraft in real time","PeriodicalId":239972,"journal":{"name":"Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems (EASe'07)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124794892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper describes a software architecture for parallel kinematic machines and its evolvement to a self-adaptive system striving to optimize, protect and heal itself Self-* properties are provided by self-manager components that observe and manipulate their associated system parts. A development approach for the self-managers is outlined, as is a first realization of a self-manager responsible for the control core. This self-manager distributes control components during runtime and makes feasibility decisions based on a runtime schedulability analysis
{"title":"Runtime Analysis of a Self-Adaptive Hard Real-Time Robotic Control System","authors":"J. Steiner, M. Hagner","doi":"10.1109/EASE.2007.23","DOIUrl":"https://doi.org/10.1109/EASE.2007.23","url":null,"abstract":"This paper describes a software architecture for parallel kinematic machines and its evolvement to a self-adaptive system striving to optimize, protect and heal itself Self-* properties are provided by self-manager components that observe and manipulate their associated system parts. A development approach for the self-managers is outlined, as is a first realization of a self-manager responsible for the control core. This self-manager distributes control components during runtime and makes feasibility decisions based on a runtime schedulability analysis","PeriodicalId":239972,"journal":{"name":"Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems (EASe'07)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127715390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The complexity of modern middleware, and software solutions, is growing at an exponential rate. Only self-managing, or autonomic computing technology can reasonably stem the confusion this complexity brings to bear on human administrators. While much has been published on "architecture" and "function" for producing such systems, little has been written about the engineering of self-managing systems as a distinct paradigm. In this paper we suggest a straw-man for engineering of autonomic systems that is based on two essential tracks: a set of engineering principles that should guide the planning of autonomic systems and their interfaces and secondly a set of mathematical foundations upon which such systems can best be constructed. These foundational attributes are intended to guide the thinking of R&D organizations pursuing the development of autonomic computing capability. The role of architecture and standards is also discussed, highlighting their role in inter-component management
{"title":"Foundations of Autonomic Computing Development","authors":"Sam Lightstone","doi":"10.1109/EASE.2007.12","DOIUrl":"https://doi.org/10.1109/EASE.2007.12","url":null,"abstract":"The complexity of modern middleware, and software solutions, is growing at an exponential rate. Only self-managing, or autonomic computing technology can reasonably stem the confusion this complexity brings to bear on human administrators. While much has been published on \"architecture\" and \"function\" for producing such systems, little has been written about the engineering of self-managing systems as a distinct paradigm. In this paper we suggest a straw-man for engineering of autonomic systems that is based on two essential tracks: a set of engineering principles that should guide the planning of autonomic systems and their interfaces and secondly a set of mathematical foundations upon which such systems can best be constructed. These foundational attributes are intended to guide the thinking of R&D organizations pursuing the development of autonomic computing capability. The role of architecture and standards is also discussed, highlighting their role in inter-component management","PeriodicalId":239972,"journal":{"name":"Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems (EASe'07)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131353716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Computing systems become increasingly large and complex. Their dependability and autonomy are of great concern today, where self-healing is a challenging topic. This paper presented an innovative model and technology to realize the self-healing function under the real-time requirement. This approach, different from the existing technologies, is based on a new concept defined as consequence-oriented diagnosis and healing. Derived from the new concept, a prototype model for proactive self-healing actions is presented. Then, this paper proposes a hybrid tool that combines MDD, fuzzy logic and neural network, which is efficient, accurate and intelligent. Some examples to help illustrate the concepts are shown across the paper
{"title":"Consequence Oriented Self-Healing and Hybrid Diagnosis Integrating Decision Diagram, Fuzzy Logic and Neural Network","authors":"Yuan-Shun Dai, M. Hinchey, Qingpei Hu","doi":"10.1109/EASE.2007.8","DOIUrl":"https://doi.org/10.1109/EASE.2007.8","url":null,"abstract":"Computing systems become increasingly large and complex. Their dependability and autonomy are of great concern today, where self-healing is a challenging topic. This paper presented an innovative model and technology to realize the self-healing function under the real-time requirement. This approach, different from the existing technologies, is based on a new concept defined as consequence-oriented diagnosis and healing. Derived from the new concept, a prototype model for proactive self-healing actions is presented. Then, this paper proposes a hybrid tool that combines MDD, fuzzy logic and neural network, which is efficient, accurate and intelligent. Some examples to help illustrate the concepts are shown across the paper","PeriodicalId":239972,"journal":{"name":"Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems (EASe'07)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115952911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Nordstrom, A. Dubey, T. Keskinpala, R. Datta, S. Neema, T. Bapty
In large scale scientific computing, proper planning and management of computational resources lead to higher system utilizations and increased scientific productivity. Scientists are increasingly leveraging the use of business process management techniques and workflow management tools to balance the needs of the scientific analyses with the availability of computational resources. However, the advancements in productivity from execution of workflows in a large scale computing environments are often thwarted by runtime resource failures. This paper presents our initial work toward autonomic model based fault analysis in workflow based environments
{"title":"Model Predictive Analysis for AutonomicWorkflow Management in Large-scale Scientific Computing Environments","authors":"S. Nordstrom, A. Dubey, T. Keskinpala, R. Datta, S. Neema, T. Bapty","doi":"10.1109/EASE.2007.18","DOIUrl":"https://doi.org/10.1109/EASE.2007.18","url":null,"abstract":"In large scale scientific computing, proper planning and management of computational resources lead to higher system utilizations and increased scientific productivity. Scientists are increasingly leveraging the use of business process management techniques and workflow management tools to balance the needs of the scientific analyses with the availability of computational resources. However, the advancements in productivity from execution of workflows in a large scale computing environments are often thwarted by runtime resource failures. This paper presents our initial work toward autonomic model based fault analysis in workflow based environments","PeriodicalId":239972,"journal":{"name":"Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems (EASe'07)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126585655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. E. Johnston, Roy Sterritt, E. Hanna, P. O'Hagan
The application of the biological metaphor of the autonomic nervous system to computing has created the paradigm of autonomic computing, in which computer systems self-regulate by using automatic reactions to defend, optimize and heal. Agent technologies have been highlighted in the literature as particularly appropriate for the development of autonomic systems. This paper reports on an investigation of the use of the autonomic concepts of reflex autonomicity and apoptosis in the development of a multi-agent system. Findings are discussed with reference to the use of the JADE agent platform for development
{"title":"Reflex Autonomicity in an Agent-Based Security System :: The Autonomic Access Control System","authors":"S. E. Johnston, Roy Sterritt, E. Hanna, P. O'Hagan","doi":"10.1109/EASE.2007.22","DOIUrl":"https://doi.org/10.1109/EASE.2007.22","url":null,"abstract":"The application of the biological metaphor of the autonomic nervous system to computing has created the paradigm of autonomic computing, in which computer systems self-regulate by using automatic reactions to defend, optimize and heal. Agent technologies have been highlighted in the literature as particularly appropriate for the development of autonomic systems. This paper reports on an investigation of the use of the autonomic concepts of reflex autonomicity and apoptosis in the development of a multi-agent system. Findings are discussed with reference to the use of the JADE agent platform for development","PeriodicalId":239972,"journal":{"name":"Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems (EASe'07)","volume":"85 32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128449617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
NASA is pursing ever increasing autonomous systems to perform new science and exploration. These missions will be out of contact with mission control for extended periods of time in very harsh and unforgiving environments. To successfully perform these missions autonomously, they will have to have autonomic properties. There have been recent studies of failures of robotic systems that examine how robots are failing in the field. By studying the types of failures that are occurring in robots autonomic properties can be developed for not only robots but for NASA autonomous missions to make them more robust. This paper examines the failures that were identified in a study of robot failures and maps them on to some autonomic properties that would address these failures. By classifying the failures and then mapping them to autonomic properties, classes of autonomic properties can be developed that can then be specialized for each particular mission
{"title":"Overcoming Robotic Failures through Autonomicity","authors":"C. Rouff, J. Rash, W. Truszkowski","doi":"10.1109/EASE.2007.21","DOIUrl":"https://doi.org/10.1109/EASE.2007.21","url":null,"abstract":"NASA is pursing ever increasing autonomous systems to perform new science and exploration. These missions will be out of contact with mission control for extended periods of time in very harsh and unforgiving environments. To successfully perform these missions autonomously, they will have to have autonomic properties. There have been recent studies of failures of robotic systems that examine how robots are failing in the field. By studying the types of failures that are occurring in robots autonomic properties can be developed for not only robots but for NASA autonomous missions to make them more robust. This paper examines the failures that were identified in a study of robot failures and maps them on to some autonomic properties that would address these failures. By classifying the failures and then mapping them to autonomic properties, classes of autonomic properties can be developed that can then be specialized for each particular mission","PeriodicalId":239972,"journal":{"name":"Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems (EASe'07)","volume":"265 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114002724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Developing robot control applications is a software engineering domain that still relies on low-level development tools with limited testing capabilities. The Java application building center (jABC), a framework for model-based application development that supports the modelling process of service-oriented software applications, on the contrary offers a number of early error detection mechanisms like animation, analysis, simulation, and formal verification. We investigate the adequacy of jABC to model, verify and implement robot control applications in a model driven paradigm, and aim at addressing the design of software for autonomous robots for space missions later on. Being able to model and verify their reconfiguration behaviour before launching them is of central importance there. We developed a proof-of-concept application that controls a Legoreg Mindstormstrade robot which finds its way through a maze. As this maze may change dynamically, the robot must be capable of reacting and adjusting its behaviour. This application was completely modelled, verified, and generated with the jABC
{"title":"Model Driven Design of Reliable Robot Control Programs Using the jABC","authors":"S. Jorges, C. Kubczak, F. Pageau, T. Margaria","doi":"10.1109/EASE.2007.17","DOIUrl":"https://doi.org/10.1109/EASE.2007.17","url":null,"abstract":"Developing robot control applications is a software engineering domain that still relies on low-level development tools with limited testing capabilities. The Java application building center (jABC), a framework for model-based application development that supports the modelling process of service-oriented software applications, on the contrary offers a number of early error detection mechanisms like animation, analysis, simulation, and formal verification. We investigate the adequacy of jABC to model, verify and implement robot control applications in a model driven paradigm, and aim at addressing the design of software for autonomous robots for space missions later on. Being able to model and verify their reconfiguration behaviour before launching them is of central importance there. We developed a proof-of-concept application that controls a Legoreg Mindstormstrade robot which finds its way through a maze. As this maze may change dynamically, the robot must be capable of reacting and adjusting its behaviour. This application was completely modelled, verified, and generated with the jABC","PeriodicalId":239972,"journal":{"name":"Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems (EASe'07)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114771718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Integrated vehicle health management (IVHM) systems on modern aircraft or autonomous unmanned vehicles should provide diagnostic and prognostic capabilities with lower support costs and amount of data traffic. When mission objectives cannot be reached for the control system since unanticipated operating conditions exists, namely a failure, the mission plan must be revised or altered according to the health monitoring system assessment. Representation of the system health knowledge must facilitate interaction with the control system to compensate for subsystem degradation. Several generic architectures have been described for the implementation of health monitoring systems and their integration with the control system. In particular, the OSA-CBM approach is considered in this work as initial point, and it is evolved in the sense of self-health awareness, by defining an appropriated multi-agent smart health management architecture based on smart device models, communication agents and a distributed control system. A case study about its application on fuel-cells as auxiliary power generator will demonstrate the integration
{"title":"A Multi-Agent-Based Management Approach for Self-Health Awareness in Autonomous Systems","authors":"G. González, C. Angulo, C. Raya","doi":"10.1109/EASE.2007.3","DOIUrl":"https://doi.org/10.1109/EASE.2007.3","url":null,"abstract":"Integrated vehicle health management (IVHM) systems on modern aircraft or autonomous unmanned vehicles should provide diagnostic and prognostic capabilities with lower support costs and amount of data traffic. When mission objectives cannot be reached for the control system since unanticipated operating conditions exists, namely a failure, the mission plan must be revised or altered according to the health monitoring system assessment. Representation of the system health knowledge must facilitate interaction with the control system to compensate for subsystem degradation. Several generic architectures have been described for the implementation of health monitoring systems and their integration with the control system. In particular, the OSA-CBM approach is considered in this work as initial point, and it is evolved in the sense of self-health awareness, by defining an appropriated multi-agent smart health management architecture based on smart device models, communication agents and a distributed control system. A case study about its application on fuel-cells as auxiliary power generator will demonstrate the integration","PeriodicalId":239972,"journal":{"name":"Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems (EASe'07)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123828016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：