D. Balasubramaniam, R. Morrison, K. Mickan, G. Kirby, B. Warboys, I. Robertson, B. Snowdon, Robert Mark Greenwood, Wykeen Seet
Self-adaptive systems modify their own behaviour in response to stimuli from their operating environments. The major policy considerations for such systems are determining what, when and how adaptations should be carried out. This paper presents mechanisms for feedback and change that support policy decisions for self-adaptation within a computationally complete architecture description language based on the π-calculus. Our contribution is support for feedback through software-encoded probes, gauges and an event distribution network together with support for change through decomposition, reification, reflection, recomposition and hyper-code.
{"title":"Support for feedback and change in self-adaptive systems","authors":"D. Balasubramaniam, R. Morrison, K. Mickan, G. Kirby, B. Warboys, I. Robertson, B. Snowdon, Robert Mark Greenwood, Wykeen Seet","doi":"10.1145/1075405.1075409","DOIUrl":"https://doi.org/10.1145/1075405.1075409","url":null,"abstract":"Self-adaptive systems modify their own behaviour in response to stimuli from their operating environments. The major policy considerations for such systems are determining what, when and how adaptations should be carried out. This paper presents mechanisms for feedback and change that support policy decisions for self-adaptation within a computationally complete architecture description language based on the π-calculus. Our contribution is support for feedback through software-encoded probes, gauges and an event distribution network together with support for change through decomposition, reification, reflection, recomposition and hyper-code.","PeriodicalId":326554,"journal":{"name":"Workshop on Self-Healing Systems","volume":"120-121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117144225","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}
J. S. Bradbury, J. Cordy, J. Dingel, M. Wermelinger
As dynamic software architecture use becomes more widespread, a variety of formal specification languages have been developed to gain a better understanding of the foundations of this type of software evolutionary change. In this paper we survey 14 formal specification approaches based on graphs, process algebras, logic, and other formalisms. Our survey will evaluate the ability of each approach to specify self-managing systems as well as the ability to address issues regarding expressiveness and scalability. Based on the results of our survey we will provide recommendations on future directions for improving the specification of dynamic software architectures, specifically self-managed architectures.
{"title":"A survey of self-management in dynamic software architecture specifications","authors":"J. S. Bradbury, J. Cordy, J. Dingel, M. Wermelinger","doi":"10.1145/1075405.1075411","DOIUrl":"https://doi.org/10.1145/1075405.1075411","url":null,"abstract":"As dynamic software architecture use becomes more widespread, a variety of formal specification languages have been developed to gain a better understanding of the foundations of this type of software evolutionary change. In this paper we survey 14 formal specification approaches based on graphs, process algebras, logic, and other formalisms. Our survey will evaluate the ability of each approach to specify self-managing systems as well as the ability to address issues regarding expressiveness and scalability. Based on the results of our survey we will provide recommendations on future directions for improving the specification of dynamic software architectures, specifically self-managed architectures.","PeriodicalId":326554,"journal":{"name":"Workshop on Self-Healing Systems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125074919","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}
Traditionally, software models are associated with development and maintenance related activities. This paper demonstrates that models also serve a vital purpose in supporting the self awareness and management of software systems in their deployed environments. We use probes to observe the executing software system by extracting the outside stimuli the system is subjected to. We use this information to concurrently simulate the model-behavior of the software system. The state of the simulating system then mirrors the state of the executing system. In this setting, the simulation serves as a foundation to self awareness through which differences among simulated behavior and real behavior are investigated. The simulation also serves as a guide to self management (i.e., self healing, self configuration) where the system uses additional information provided in the simulating model to manage itself.
{"title":"Architecture differencing for self management","authors":"Alexander Egyed","doi":"10.1145/1075405.1075414","DOIUrl":"https://doi.org/10.1145/1075405.1075414","url":null,"abstract":"Traditionally, software models are associated with development and maintenance related activities. This paper demonstrates that models also serve a vital purpose in supporting the self awareness and management of software systems in their deployed environments. We use probes to observe the executing software system by extracting the outside stimuli the system is subjected to. We use this information to concurrently simulate the model-behavior of the software system. The state of the simulating system then mirrors the state of the executing system. In this setting, the simulation serves as a foundation to self awareness through which differences among simulated behavior and real behavior are investigated. The simulation also serves as a guide to self management (i.e., self healing, self configuration) where the system uses additional information provided in the simulating model to manage itself.","PeriodicalId":326554,"journal":{"name":"Workshop on Self-Healing Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130581189","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 propose a high-level approach to software architecture that bridges the gap between system requirements (in the problem space) and the architectural design (in the solution space). We use abstract constraint- and intent-based architectural prescriptions to enable architectural reflection, reification, and distributed configuration discovery as the basis for designing adaptive, self-configuring software systems. We discuss some key architectural properties and patterns that facilitate the design and implementation of self-configuring systems, and use these as the basis for an example prototype architecture for self-evolving systems called Distributed Configuration Routing (DCR). Finally, we propose the development of architectural prescription languages (APLs) and enhanced system design environments to provide better support for intent-based architectures.
{"title":"Exploiting architectural prescriptions for self-managing, self-adaptive systems: a position paper","authors":"Matthew J. Hawthorne, D. Perry","doi":"10.1145/1075405.1075420","DOIUrl":"https://doi.org/10.1145/1075405.1075420","url":null,"abstract":"We propose a high-level approach to software architecture that bridges the gap between system requirements (in the problem space) and the architectural design (in the solution space). We use abstract constraint- and intent-based architectural prescriptions to enable architectural reflection, reification, and distributed configuration discovery as the basis for designing adaptive, self-configuring software systems. We discuss some key architectural properties and patterns that facilitate the design and implementation of self-configuring systems, and use these as the basis for an example prototype architecture for self-evolving systems called Distributed Configuration Routing (DCR). Finally, we propose the development of architectural prescription languages (APLs) and enhanced system design environments to provide better support for intent-based architectures.","PeriodicalId":326554,"journal":{"name":"Workshop on Self-Healing Systems","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131989310","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}
Kaustubh R. Joshi, M. Hiltunen, R. Schlichting, W. Sanders, A. Agbaria
Constructing adaptive software that is capable of changing behavior at runtime is a challenging software engineering problem. However, the problem of determining when and how such a system should adapt, i.e., the system's adaptation policy, can be even more challenging. To optimize the behavior of a system over its lifetime, the policy must often take into account not only the current system state, but also the anticipated future behavior of the system. This paper presents a systematic approach based on using Markov Decision Processes to model the system and to generate optimal adaptation policies for it. In our approach, we update the model on-line based on system measurements and generate updated adaptation policies at runtime when necessary. We present the general approach and then outline its application to a distributed message dissemination system based on AT&T's iMobile platform.
{"title":"Online model-based adaptation for optimizing performance and dependability","authors":"Kaustubh R. Joshi, M. Hiltunen, R. Schlichting, W. Sanders, A. Agbaria","doi":"10.1145/1075405.1075422","DOIUrl":"https://doi.org/10.1145/1075405.1075422","url":null,"abstract":"Constructing adaptive software that is capable of changing behavior at runtime is a challenging software engineering problem. However, the problem of determining when and how such a system should adapt, i.e., the system's adaptation policy, can be even more challenging. To optimize the behavior of a system over its lifetime, the policy must often take into account not only the current system state, but also the anticipated future behavior of the system. This paper presents a systematic approach based on using Markov Decision Processes to model the system and to generate optimal adaptation policies for it. In our approach, we update the model on-line based on system measurements and generate updated adaptation policies at runtime when necessary. We present the general approach and then outline its application to a distributed message dissemination system based on AT&T's iMobile platform.","PeriodicalId":326554,"journal":{"name":"Workshop on Self-Healing Systems","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116249490","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}
Failure recovery in distributed systems poses a difficult challenge because of the requirement for high availability. Failure scenarios are usually unpredictable so they can not easily be foreseen. In this research we propose a planning based approach to failure recovery. This approach automates failure recovery by capturing the state after failure, defining an acceptable recovered state as a goal and applying planning to get from the initial state to the goal state. By using planning, this approach can recover from a variety of failed states and reach any of several acceptable states: from minimal functionality to complete recovery.
{"title":"A planning based approach to failure recovery in distributed systems","authors":"N. Arshad, D. Heimbigner, A. Wolf","doi":"10.1145/1075405.1075407","DOIUrl":"https://doi.org/10.1145/1075405.1075407","url":null,"abstract":"Failure recovery in distributed systems poses a difficult challenge because of the requirement for high availability. Failure scenarios are usually unpredictable so they can not easily be foreseen. In this research we propose a planning based approach to failure recovery. This approach automates failure recovery by capturing the state after failure, defining an acceptable recovered state as a goal and applying planning to get from the initial state to the goal state. By using planning, this approach can recover from a variety of failed states and reach any of several acceptable states: from minimal functionality to complete recovery.","PeriodicalId":326554,"journal":{"name":"Workshop on Self-Healing Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116392849","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}
A distributed software system's deployment architecture can have a significant impact on the system's properties, which depend on various system parameters, such as network bandwidth, frequencies of software component interactions, and so on. Recent studies have shown that the quality of deployment architectures can be improved significantly via active system monitoring, efficient estimation of the improved deployment architecture, and system redeployment. However, the lack of a common framework for improving a system's deployment architecture has resulted in ad hoc solutions. In this paper, we present an extensible framework that guides the design and development of solutions to this problem, enables the extension and reuse of the solutions, and facilitates autonomic analysis and redeployment of a system's deployment architecture.
{"title":"An extensible framework for autonomic analysis and improvement of distributed deployment architectures","authors":"S. Malek, Marija Mikic-Rakic, N. Medvidović","doi":"10.1145/1075405.1075424","DOIUrl":"https://doi.org/10.1145/1075405.1075424","url":null,"abstract":"A distributed software system's deployment architecture can have a significant impact on the system's properties, which depend on various system parameters, such as network bandwidth, frequencies of software component interactions, and so on. Recent studies have shown that the quality of deployment architectures can be improved significantly via active system monitoring, efficient estimation of the improved deployment architecture, and system redeployment. However, the lack of a common framework for improving a system's deployment architecture has resulted in ad hoc solutions. In this paper, we present an extensible framework that guides the design and development of solutions to this problem, enables the extension and reuse of the solutions, and facilitates autonomic analysis and redeployment of a system's deployment architecture.","PeriodicalId":326554,"journal":{"name":"Workshop on Self-Healing Systems","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123741010","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}
Increasing demands for reliability and dependability clash with the reality of escalating security compromises and vulnerability discoveries. Improvements in attack methodologies such as polymorphic viruses, tampering of source code repositories, and automation of distributed strikes are no match for the untimely detection and manual recovery practices used today. We present a run-time method to automate recovery from kernel level system compromises. It is capable of returning modified system call table addresses back to their original values, terminating hidden processes, removing hidden files, and blocking attacker traffic to hidden connections. Self-healing mechanisms such as this can be employed to create more reliable intrusion tolerant operating systems and applications. A working prototype has been implemented as a loadable kernel module on Linux, and can be easily enhanced for other operating systems.
{"title":"Self-healing mechanisms for kernel system compromises","authors":"S. Ring, D. Esler, E. Cole","doi":"10.1145/1075405.1075425","DOIUrl":"https://doi.org/10.1145/1075405.1075425","url":null,"abstract":"Increasing demands for reliability and dependability clash with the reality of escalating security compromises and vulnerability discoveries. Improvements in attack methodologies such as polymorphic viruses, tampering of source code repositories, and automation of distributed strikes are no match for the untimely detection and manual recovery practices used today. We present a run-time method to automate recovery from kernel level system compromises. It is capable of returning modified system call table addresses back to their original values, terminating hidden processes, removing hidden files, and blocking attacker traffic to hidden connections. Self-healing mechanisms such as this can be employed to create more reliable intrusion tolerant operating systems and applications. A working prototype has been implemented as a loadable kernel module on Linux, and can be easily enhanced for other operating systems.","PeriodicalId":326554,"journal":{"name":"Workshop on Self-Healing Systems","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115301719","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}
Self-adaptive software continually evaluates and modifies its own behavior to meet changing demands. One of the key issues in constructing such software is that of planning when and what kinds of adaptations are appropriate. In this paper, we present an architecture-centric knowledge-based approach for specifying and enacting architectural adaptation policies as the main driver for self-adaptive behavior. Our work applies explicitly represented knowledge-based policies for the definition and enactment of software adaptation at the architectural level. A key benefit of our approach is the decoupling of adaptation policy from system implementation as well as the independent and dynamic evolution of policies themselves. We elaborate our overall approach, present prototype tools and techniques for its support, and discuss future research directions.
{"title":"Towards a knowledge-based approach to architectural adaptation management","authors":"John C. Georgas, R. Taylor","doi":"10.1145/1075405.1075417","DOIUrl":"https://doi.org/10.1145/1075405.1075417","url":null,"abstract":"Self-adaptive software continually evaluates and modifies its own behavior to meet changing demands. One of the key issues in constructing such software is that of planning when and what kinds of adaptations are appropriate. In this paper, we present an architecture-centric knowledge-based approach for specifying and enacting architectural adaptation policies as the main driver for self-adaptive behavior. Our work applies explicitly represented knowledge-based policies for the definition and enactment of software adaptation at the architectural level. A key benefit of our approach is the decoupling of adaptation policy from system implementation as well as the independent and dynamic evolution of policies themselves. We elaborate our overall approach, present prototype tools and techniques for its support, and discuss future research directions.","PeriodicalId":326554,"journal":{"name":"Workshop on Self-Healing Systems","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117282893","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}
Complex distributed Internet services form the basis not only of e-commerce but increasingly of mission-critical network-based applications. What is new is that the workload and internal architecture of three-tier enterprise applications presents the opportunity for a new approach to keeping them running in the face of many common recoverable failures. The core of the approach is anomaly detection and localization based on statistical machine learning techniques. Unlike previous approaches, we propose anomaly detection and pattern mining not only for operational statistics such as mean response time, but also for structural behaviors of the system---what parts of the system, in what combinations, are being exercised in response to different kinds of external stimuli. In addition, rather than building baseline models a priori, we extract them by observing the behavior of the system over a short period of time during normal operation. We explain the necessary underlying assumptions and why they can be realized by systems research, report on some early successes using the approach, describe benefits of the approach that make it competitive as a path toward self-managing systems, and outline some research challenges. Our hope is that this approach will enable "new science" in the design of self-managing systems by allowing the rapid and widespread application of statistical learning theory techniques (SLT) to problems of system dependability.
{"title":"Combining statistical monitoring and predictable recovery for self-management","authors":"A. Fox, Emre Kıcıman, D. Patterson","doi":"10.1145/1075405.1075415","DOIUrl":"https://doi.org/10.1145/1075405.1075415","url":null,"abstract":"Complex distributed Internet services form the basis not only of e-commerce but increasingly of mission-critical network-based applications. What is new is that the workload and internal architecture of three-tier enterprise applications presents the opportunity for a new approach to keeping them running in the face of many common recoverable failures. The core of the approach is anomaly detection and localization based on statistical machine learning techniques. Unlike previous approaches, we propose anomaly detection and pattern mining not only for operational statistics such as mean response time, but also for structural behaviors of the system---what parts of the system, in what combinations, are being exercised in response to different kinds of external stimuli. In addition, rather than building baseline models a priori, we extract them by observing the behavior of the system over a short period of time during normal operation. We explain the necessary underlying assumptions and why they can be realized by systems research, report on some early successes using the approach, describe benefits of the approach that make it competitive as a path toward self-managing systems, and outline some research challenges. Our hope is that this approach will enable \"new science\" in the design of self-managing systems by allowing the rapid and widespread application of statistical learning theory techniques (SLT) to problems of system dependability.","PeriodicalId":326554,"journal":{"name":"Workshop on Self-Healing Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122115526","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}
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