The goal of this work is to gain a better understanding of the role that inter-agent variation plays in self-organizing systems. We develop both continuous and discrete models of a multi-agent coordination procedure based on response thresholds and use these models to analyze the average behavior of a system as well as examine the dynamics of single instances of the problem. Results indicate that variation in the behaviors of agents can lead to increased stability and more effective self-organization in cooperative multi-agent systems.
{"title":"On the Impact of Variation on Self-Organizing Systems","authors":"A. Campbell, Cortney Riggs, A. Wu","doi":"10.1109/SASO.2011.23","DOIUrl":"https://doi.org/10.1109/SASO.2011.23","url":null,"abstract":"The goal of this work is to gain a better understanding of the role that inter-agent variation plays in self-organizing systems. We develop both continuous and discrete models of a multi-agent coordination procedure based on response thresholds and use these models to analyze the average behavior of a system as well as examine the dynamics of single instances of the problem. Results indicate that variation in the behaviors of agents can lead to increased stability and more effective self-organization in cooperative multi-agent systems.","PeriodicalId":165565,"journal":{"name":"2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130851940","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}
In recent years it has become more and more evident that openness and adaptivity are key characteristics of next generation distributed systems. The reason for that is not least the advent of computing trends like Ubiquitous Computing, Ambient Intelligence, and Cyber Physical Systems, where systems are usually open for dynamic integration and able to react adaptively to changing situations. Despite being open and adaptive it is a common requirement for such systems to be safe. However, traditional safety assurance techniques, both state-of-the-practice and state-of-the-art, are not sufficient in this context. We recently developed some initial solution concepts based on conditional safety certificates and corresponding runtime analyses. In this paper we show how to operationalize these concepts. To this end we present in detail how to specify conditional safety certificates, how to transform them into suitable runtime models, and how these models finally support dynamic safety evaluations.
{"title":"A Safety Engineering Framework for Open Adaptive Systems","authors":"D. Schneider, M. Trapp","doi":"10.1109/SASO.2011.20","DOIUrl":"https://doi.org/10.1109/SASO.2011.20","url":null,"abstract":"In recent years it has become more and more evident that openness and adaptivity are key characteristics of next generation distributed systems. The reason for that is not least the advent of computing trends like Ubiquitous Computing, Ambient Intelligence, and Cyber Physical Systems, where systems are usually open for dynamic integration and able to react adaptively to changing situations. Despite being open and adaptive it is a common requirement for such systems to be safe. However, traditional safety assurance techniques, both state-of-the-practice and state-of-the-art, are not sufficient in this context. We recently developed some initial solution concepts based on conditional safety certificates and corresponding runtime analyses. In this paper we show how to operationalize these concepts. To this end we present in detail how to specify conditional safety certificates, how to transform them into suitable runtime models, and how these models finally support dynamic safety evaluations.","PeriodicalId":165565,"journal":{"name":"2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128769279","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 technical systems like robots or cars are composed of many embedded subsystems to control partial dynamical effects of the whole system. In order to ease engineering and to cope with changing environmental or system properties, these subsystems need to be self-adapting. But for this to be feasible, they cannot observe the theoretically required state space of the whole system. Instead, they need to work with a reduced set of input variables. This leads to a lack of information which may induce unintended, dynamic interactions between the self-adaptation processes. Within this paper, a method is proposed in order to control the self-adaptation processes and to fight these interactions in a goal directed way. The approach is investigated on a real robotic arm.
{"title":"Controlling the Learning Dynamics of Interacting Self-Adapting Systems","authors":"N. Rosemann, W. Brockmann, Christian Lintze","doi":"10.1109/SASO.2011.11","DOIUrl":"https://doi.org/10.1109/SASO.2011.11","url":null,"abstract":"Complex technical systems like robots or cars are composed of many embedded subsystems to control partial dynamical effects of the whole system. In order to ease engineering and to cope with changing environmental or system properties, these subsystems need to be self-adapting. But for this to be feasible, they cannot observe the theoretically required state space of the whole system. Instead, they need to work with a reduced set of input variables. This leads to a lack of information which may induce unintended, dynamic interactions between the self-adaptation processes. Within this paper, a method is proposed in order to control the self-adaptation processes and to fight these interactions in a goal directed way. The approach is investigated on a real robotic arm.","PeriodicalId":165565,"journal":{"name":"2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132007222","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}
Mirko Viroli, Elena Nardini, G. Castelli, M. Mamei, F. Zambonelli
Technology evolution is providing new pervasive service scenarios characterised by a huge number of distributed and dynamic devices. Accordingly, a new generation of services and infrastructures are emerging which support situatedness, adaptivity and diversity. In this paper we model the overall world of services, data and devices, as a distributed computational ecosystem. As such, each entity will be modelled as an autonomous, spatially-situated individual of the ecosystem, whose existence and state is reified by an LSA (Live Semantic Annotation). Ecosystem behaviour is controlled by coordination rules called eco-laws, which are chemical-like reactions evolving the population of LSAs. We describe an architecture that is at the basis of the SAPERE project ("Self-aware Pervasive Service Ecosystems", www.sapere-project.eu), supporting the vision along with a model of eco-laws, and show their usefulness in a scenario of adaptive pervasive displays.
{"title":"Towards a Coordination Approach to Adaptive Pervasive Service Ecosystems","authors":"Mirko Viroli, Elena Nardini, G. Castelli, M. Mamei, F. Zambonelli","doi":"10.1109/SASO.2011.42","DOIUrl":"https://doi.org/10.1109/SASO.2011.42","url":null,"abstract":"Technology evolution is providing new pervasive service scenarios characterised by a huge number of distributed and dynamic devices. Accordingly, a new generation of services and infrastructures are emerging which support situatedness, adaptivity and diversity. In this paper we model the overall world of services, data and devices, as a distributed computational ecosystem. As such, each entity will be modelled as an autonomous, spatially-situated individual of the ecosystem, whose existence and state is reified by an LSA (Live Semantic Annotation). Ecosystem behaviour is controlled by coordination rules called eco-laws, which are chemical-like reactions evolving the population of LSAs. We describe an architecture that is at the basis of the SAPERE project (\"Self-aware Pervasive Service Ecosystems\", www.sapere-project.eu), supporting the vision along with a model of eco-laws, and show their usefulness in a scenario of adaptive pervasive displays.","PeriodicalId":165565,"journal":{"name":"2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131888242","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}
Spatial publish subscribe (SPS) is a basic primitive underlying many real-time, interactive applications such as online games or discrete-time simulations. Supporting SPS on a large-scale, however, requires sufficient resources and proper load distribution among the simulation units. For load distribution, existing mechanisms either use a static partitioning, such that over-provisioning or overloading are bound to occur, or require manual adjustments unsuitable for massive workloads. We describe Voronoi Self-organizing Overlay (VSO), which extends a Voronoi-based Overlay network (VON) to automatically partition and manage a logical space to support SPS. Efficient resource usage thus is possible as only the units necessary to maintain the system are used. Load is also balanced among the resource units so that overloading or over-provisioning can be avoided. We use simulations to verify our design and describe some preliminary results.
{"title":"VSO: Self-Organizing Spatial Publish Subscribe","authors":"Shun-Yun Hu, Kuan-Ta Chen","doi":"10.1109/SASO.2011.13","DOIUrl":"https://doi.org/10.1109/SASO.2011.13","url":null,"abstract":"Spatial publish subscribe (SPS) is a basic primitive underlying many real-time, interactive applications such as online games or discrete-time simulations. Supporting SPS on a large-scale, however, requires sufficient resources and proper load distribution among the simulation units. For load distribution, existing mechanisms either use a static partitioning, such that over-provisioning or overloading are bound to occur, or require manual adjustments unsuitable for massive workloads. We describe Voronoi Self-organizing Overlay (VSO), which extends a Voronoi-based Overlay network (VON) to automatically partition and manage a logical space to support SPS. Efficient resource usage thus is possible as only the units necessary to maintain the system are used. Load is also balanced among the resource units so that overloading or over-provisioning can be avoided. We use simulations to verify our design and describe some preliminary results.","PeriodicalId":165565,"journal":{"name":"2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"13 41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127565171","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 behaviour of self-* systems is complex to model from an algorithmic point of view. Designing and specifying self-* systems implies a great amount of work that can be sensibly reduced if models can be reused and composed in a modular way. This article discusses a chemically-inspired architecture and formalisms that facilitate the creation of modular, reusable models based on behavioural patterns inspired by behaviours found in nature. The architecture is based on chemical-like laws ruling the evolution of the system. We show the reuse of general behavioural patterns using three concrete examples of self-* systems from different domains.
{"title":"Modeling Self-* Systems Using Chemically-Inspired Composable Patterns","authors":"Akla-Esso Tchao, Matteo Risoldi, G. Serugendo","doi":"10.1109/SASO.2011.22","DOIUrl":"https://doi.org/10.1109/SASO.2011.22","url":null,"abstract":"The behaviour of self-* systems is complex to model from an algorithmic point of view. Designing and specifying self-* systems implies a great amount of work that can be sensibly reduced if models can be reused and composed in a modular way. This article discusses a chemically-inspired architecture and formalisms that facilitate the creation of modular, reusable models based on behavioural patterns inspired by behaviours found in nature. The architecture is based on chemical-like laws ruling the evolution of the system. We show the reuse of general behavioural patterns using three concrete examples of self-* systems from different domains.","PeriodicalId":165565,"journal":{"name":"2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123383757","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 study in the use of neuroevolution to discover controllers for a simulated mobile ad hoc network. Neuroevolution is a technique whereby an evolutionary algorithm is used to produce artificial neural networks that solve a user-defined task. Here, we use neuroevolution to study a generic coverage-based problem, where agents in the network are to maximize the area covered by the largest connected component of the network. An example application for this work is the discovery of control algorithms for an ocean-monitoring mobile network. While this is a challenging problem domain for neuroevolution, results of our experiments reveal three important characteristics to be considered when using such an approach. Specifically, we found that approaches that implicitly reduce entropy, while explicitly addressing self-organization and scalability, are capable of discovering behaviors that remain stable even when they control networks of different sizes than were evaluated during evolution. This result suggests that neuroevolution may be a viable strategy for discovering controllers for self-organizing multi-agent systems.
{"title":"Neuroevolution of Controllers for Self-Organizing Mobile Ad Hoc Networks","authors":"David B. Knoester, P. McKinley","doi":"10.1109/SASO.2011.30","DOIUrl":"https://doi.org/10.1109/SASO.2011.30","url":null,"abstract":"This paper describes a study in the use of neuroevolution to discover controllers for a simulated mobile ad hoc network. Neuroevolution is a technique whereby an evolutionary algorithm is used to produce artificial neural networks that solve a user-defined task. Here, we use neuroevolution to study a generic coverage-based problem, where agents in the network are to maximize the area covered by the largest connected component of the network. An example application for this work is the discovery of control algorithms for an ocean-monitoring mobile network. While this is a challenging problem domain for neuroevolution, results of our experiments reveal three important characteristics to be considered when using such an approach. Specifically, we found that approaches that implicitly reduce entropy, while explicitly addressing self-organization and scalability, are capable of discovering behaviors that remain stable even when they control networks of different sizes than were evaluated during evolution. This result suggests that neuroevolution may be a viable strategy for discovering controllers for self-organizing multi-agent systems.","PeriodicalId":165565,"journal":{"name":"2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125456802","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 applies the concept of exploratory change to self-adaptive software systems and proposes and briefly specifies a new paradigm for self-adaptation named exploratory self-adaptation. In exploratory self-adaptation exploratory changes are continuously introduced into the software system as hypothetical improvements of its functional characteristics or quality attributes. Once introduced, these changes are evaluated: if the evaluation is positive, they remain and the system has self-adapted, otherwise the changes are rolled back.
{"title":"Exploratory Self-Adaptation in Software Systems","authors":"Stavros Stavru, S. Ilieva","doi":"10.1109/SASO.2011.36","DOIUrl":"https://doi.org/10.1109/SASO.2011.36","url":null,"abstract":"This paper applies the concept of exploratory change to self-adaptive software systems and proposes and briefly specifies a new paradigm for self-adaptation named exploratory self-adaptation. In exploratory self-adaptation exploratory changes are continuously introduced into the software system as hypothetical improvements of its functional characteristics or quality attributes. Once introduced, these changes are evaluated: if the evaluation is positive, they remain and the system has self-adapted, otherwise the changes are rolled back.","PeriodicalId":165565,"journal":{"name":"2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126877625","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}
In this work we investigate the self-organizing behavior of self-propelled, interacting particles. Using GPU-optimized molecular dynamics simulation we find steady state structures stabilized far-from-equilibrium. We show how these structures depend upon interaction parameters, thermodynamic parameters, and initial conditions.
{"title":"Self-Assembly and Self-Tuning Behavior of Self-Propelled Particles","authors":"Nguyen Nguyen, Eric Jankowski, S. Glotzer","doi":"10.1109/SASO.2011.39","DOIUrl":"https://doi.org/10.1109/SASO.2011.39","url":null,"abstract":"In this work we investigate the self-organizing behavior of self-propelled, interacting particles. Using GPU-optimized molecular dynamics simulation we find steady state structures stabilized far-from-equilibrium. We show how these structures depend upon interaction parameters, thermodynamic parameters, and initial conditions.","PeriodicalId":165565,"journal":{"name":"2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128478650","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}
Data diffusion techniques enable a distributed system to replicate and propagate data across a potentially unreliable network in order to provide better data protection and availability. This paper presents a novel evolutionary computation approach to developing network construction algorithms and data diffusion strategies. The proposed approach combines a linear genetic program with a cellular automaton to evolve digital organisms (agents) capable of self-organizing into different types of networks and self-adapting to changes in their surrounding environment, such as link failures and node churn. We assess the effectiveness of the proposed approach by conducting several experiments that explore different network structures under different environmental conditions. The results suggest the combined methods are able to produce self-organizing and self-adaptive agents that construct networks and efficiently distribute data throughout the network, while balancing competing concerns, such as minimizing energy consumption and providing reliability.
{"title":"An Evolutionary Approach to Network Self-Organization and Resilient Data Diffusion","authors":"A. J. Ramírez, B. Cheng, P. McKinley","doi":"10.1109/SASO.2011.31","DOIUrl":"https://doi.org/10.1109/SASO.2011.31","url":null,"abstract":"Data diffusion techniques enable a distributed system to replicate and propagate data across a potentially unreliable network in order to provide better data protection and availability. This paper presents a novel evolutionary computation approach to developing network construction algorithms and data diffusion strategies. The proposed approach combines a linear genetic program with a cellular automaton to evolve digital organisms (agents) capable of self-organizing into different types of networks and self-adapting to changes in their surrounding environment, such as link failures and node churn. We assess the effectiveness of the proposed approach by conducting several experiments that explore different network structures under different environmental conditions. The results suggest the combined methods are able to produce self-organizing and self-adaptive agents that construct networks and efficiently distribute data throughout the network, while balancing competing concerns, such as minimizing energy consumption and providing reliability.","PeriodicalId":165565,"journal":{"name":"2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128954568","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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