Modern and evolving domains such as ambient intelligence, context-aware applications, and pervasive computing require that software systems be able to cope with unprecedented degrees of runtime variability. This demands that software systems be flexible, and easily adaptable in the wake of change. Providing such flexibility is a multi-faceted challenge where the architectural design plays a key role. This tutorial presents the current state of practice in software architecture for adaptive systems, and provides an overview of the research directions in which the Software Architecture community is moving to better solve these issues.
{"title":"Architectural Styles for Adaptive Systems: A Tutorial","authors":"L. Baresi, Sam Guinea","doi":"10.1109/SASO.2012.38","DOIUrl":"https://doi.org/10.1109/SASO.2012.38","url":null,"abstract":"Modern and evolving domains such as ambient intelligence, context-aware applications, and pervasive computing require that software systems be able to cope with unprecedented degrees of runtime variability. This demands that software systems be flexible, and easily adaptable in the wake of change. Providing such flexibility is a multi-faceted challenge where the architectural design plays a key role. This tutorial presents the current state of practice in software architecture for adaptive systems, and provides an overview of the research directions in which the Software Architecture community is moving to better solve these issues.","PeriodicalId":126067,"journal":{"name":"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"7 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117340621","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 consider self-organized synchronization in a wireless network, in a setting where there may be transmissions in the network interfering with the reception of synchronization pulses. Persistent existence of interference may prevent synchronization pulses from being heard, which potentially divides the network to multiple connected components separated by interference barriers. We investigate methods to coordinate the synchronization transmission and/or reception strategies within connected components, so that they may grow by bridging barriers. Symmetry in the self-organized connected component growth is broken by synchronization IDs, with a resolution mechanism allowing a finite ID space. Simulation results in a random network with distance-dependent path loss a represented. The coordination methods increase the probability of convergence from multiple connected components to a single connected component covering the whole network significantly.
{"title":"Bridging Interference Barriers in Self-Organized Synchronization","authors":"Parth Amin, V. Ganesan, O. Tirkkonen","doi":"10.1109/SASO.2012.30","DOIUrl":"https://doi.org/10.1109/SASO.2012.30","url":null,"abstract":"We consider self-organized synchronization in a wireless network, in a setting where there may be transmissions in the network interfering with the reception of synchronization pulses. Persistent existence of interference may prevent synchronization pulses from being heard, which potentially divides the network to multiple connected components separated by interference barriers. We investigate methods to coordinate the synchronization transmission and/or reception strategies within connected components, so that they may grow by bridging barriers. Symmetry in the self-organized connected component growth is broken by synchronization IDs, with a resolution mechanism allowing a finite ID space. Simulation results in a random network with distance-dependent path loss a represented. The coordination methods increase the probability of convergence from multiple connected components to a single connected component covering the whole network significantly.","PeriodicalId":126067,"journal":{"name":"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125394278","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 fully distributed networks data mining is an important tool for monitoring, control, and for offering personalized services to users. The underlying data model can change as a function of time according to periodic (daily, weakly) patterns, sudden changes, or long term transformations of the environment or the system itself. For a large space of the possible models for this dynamism-when the network is very large but only a few training samples can be obtained at all nodes locally-no efficient fully distributed solution is known. Here we present an approach, that is able to follow concept drift in very large scale and fully distributed networks. The algorithm does not collect data to a central location, instead it is based on online learners taking random walks in the network. To achieve adaptivity the diversity of the learners is controlled by managing the life spans of the models. We demonstrate through a thorough experimental analysis, that in a well specified range of feasible models of concept drift, where there is little data available locally in a large network, our algorithm outperforms known methods from related work.
{"title":"Gossip-Based Learning under Drifting Concepts in Fully Distributed Networks","authors":"István Hegedüs, Róbert Ormándi, Márk Jelasity","doi":"10.1109/SASO.2012.13","DOIUrl":"https://doi.org/10.1109/SASO.2012.13","url":null,"abstract":"In fully distributed networks data mining is an important tool for monitoring, control, and for offering personalized services to users. The underlying data model can change as a function of time according to periodic (daily, weakly) patterns, sudden changes, or long term transformations of the environment or the system itself. For a large space of the possible models for this dynamism-when the network is very large but only a few training samples can be obtained at all nodes locally-no efficient fully distributed solution is known. Here we present an approach, that is able to follow concept drift in very large scale and fully distributed networks. The algorithm does not collect data to a central location, instead it is based on online learners taking random walks in the network. To achieve adaptivity the diversity of the learners is controlled by managing the life spans of the models. We demonstrate through a thorough experimental analysis, that in a well specified range of feasible models of concept drift, where there is little data available locally in a large network, our algorithm outperforms known methods from related work.","PeriodicalId":126067,"journal":{"name":"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116521343","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}
Jennifer M. Miller, L. Rossi, H. Luan, Chien-Chung Shen
In this paper, we analyze and evaluate swarm interactions using varying amounts of kinetic memory, defined as the stored velocity states for n discrete time steps in the past. We show that kinetic memory can play a key role in the dynamics of biological and artificial aggregations. It is reasonable to suppose that individuals possess a memory of the immediate past and use this information to their advantage when swarming. Similarly, in wireless robotic applications, the storage of past movements requires nocommunication and can be used to stabilize aggregations. In fact, in wireless robotic applications, the communication rate between nearby individuals is more limited than in many biological applications, so the time step used to update an individual's velocity is greater. In this paper, we develop and analyze updating schemes for interacting individuals in a swarm. We show that we can stabilize and destabilize coherent translating structures using suitable adjustments to the updating scheme. Using this framework, we design an updating scheme to provide maximum stability for coherent structures that arise from a three-zone swarming model. Finally, we verify the effectiveness of our updating methodology using realistic QualNet simulations of a swarm of networked robots.
{"title":"The Role of Memory in Stabilizing Swarms","authors":"Jennifer M. Miller, L. Rossi, H. Luan, Chien-Chung Shen","doi":"10.1109/SASO.2012.22","DOIUrl":"https://doi.org/10.1109/SASO.2012.22","url":null,"abstract":"In this paper, we analyze and evaluate swarm interactions using varying amounts of kinetic memory, defined as the stored velocity states for n discrete time steps in the past. We show that kinetic memory can play a key role in the dynamics of biological and artificial aggregations. It is reasonable to suppose that individuals possess a memory of the immediate past and use this information to their advantage when swarming. Similarly, in wireless robotic applications, the storage of past movements requires nocommunication and can be used to stabilize aggregations. In fact, in wireless robotic applications, the communication rate between nearby individuals is more limited than in many biological applications, so the time step used to update an individual's velocity is greater. In this paper, we develop and analyze updating schemes for interacting individuals in a swarm. We show that we can stabilize and destabilize coherent translating structures using suitable adjustments to the updating scheme. Using this framework, we design an updating scheme to provide maximum stability for coherent structures that arise from a three-zone swarming model. Finally, we verify the effectiveness of our updating methodology using realistic QualNet simulations of a swarm of networked robots.","PeriodicalId":126067,"journal":{"name":"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125776827","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}
Software systems today are increasingly used in changing environments and expected to adapt with variable adaptation concerns. This requirement demands a systematic approach to efficiently construct system global adaptation behaviour according to the dynamic adaptation requirements. This paper presents Transformer a framework for adaptation behaviour composition support based on reusable and compos able adaptation components. Rather than using one adaptation module for all possible contexts, Transformer constructs system global adaptation behaviour by contextually fusing adaptation plans from multiple adaptation components. Explicit conflict resolution is provided to handle possible conflicts raised in the fusion process. In addition to the description of the Transformer framework, this paper also presents its implementation and its application to a video conferencing system. Qualitative analysis and simulation results show that our framework exhibits significant advantage over traditional approaches in light of flexibility and reusability of the adaptation components with little performance overhead.
{"title":"Towards Meta-Adaptation Support with Reusable and Composable Adaptation Components","authors":"Ning Gui, V. D. Florio","doi":"10.1109/SASO.2012.11","DOIUrl":"https://doi.org/10.1109/SASO.2012.11","url":null,"abstract":"Software systems today are increasingly used in changing environments and expected to adapt with variable adaptation concerns. This requirement demands a systematic approach to efficiently construct system global adaptation behaviour according to the dynamic adaptation requirements. This paper presents Transformer a framework for adaptation behaviour composition support based on reusable and compos able adaptation components. Rather than using one adaptation module for all possible contexts, Transformer constructs system global adaptation behaviour by contextually fusing adaptation plans from multiple adaptation components. Explicit conflict resolution is provided to handle possible conflicts raised in the fusion process. In addition to the description of the Transformer framework, this paper also presents its implementation and its application to a video conferencing system. Qualitative analysis and simulation results show that our framework exhibits significant advantage over traditional approaches in light of flexibility and reusability of the adaptation components with little performance overhead.","PeriodicalId":126067,"journal":{"name":"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126627182","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}
Many contemporary applications in distributed systems and networks demand that the components adapt the system functionality at run-time. We are particularly concerned with intentional change involving choice, coordination and collective action: this we call organised adaptation. There are many proposed formalisms for engineering such adaptation, primarily stemming from the fields of multi-agent systems and autonomic computing, and we propose an analytic framework against which we evaluate a number of prominent formalisms. We discuss the future challenges facing engineers of organised adaptation, in particular the requirement for a formal method for systems development and evaluation.
{"title":"Engineering Organised Adaptation: A Tutorial","authors":"J. Pitt, A. Artikis","doi":"10.1109/SASO.2012.37","DOIUrl":"https://doi.org/10.1109/SASO.2012.37","url":null,"abstract":"Many contemporary applications in distributed systems and networks demand that the components adapt the system functionality at run-time. We are particularly concerned with intentional change involving choice, coordination and collective action: this we call organised adaptation. There are many proposed formalisms for engineering such adaptation, primarily stemming from the fields of multi-agent systems and autonomic computing, and we propose an analytic framework against which we evaluate a number of prominent formalisms. We discuss the future challenges facing engineers of organised adaptation, in particular the requirement for a formal method for systems development and evaluation.","PeriodicalId":126067,"journal":{"name":"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"205 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123376525","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 biology, recent techniques in confocal microscopy have produced experimental data which highlights the importance of cellular dynamics in the evolution of biological shapes. Thus, to understand the mechanisms underlying the morphogenesis of multi-cellular organisms, we study this cellular dynamic system in terms of its properties: cell multiplication, cell migration, and apoptosis. Besides, understanding the convergence of the system toward a stable form, involves local interactions between cells. Indeed, the way that cells self-organize through these interactions determines the resulting form. Along with the mechanisms of convergence highlighted above, the dynamic system also undergoes controls established by the nature on the organisms growth. Hence, to let the system viable, the global behavior of cells has to be assessed at every state of their developement and must satisfy the constraints. Otherwise, the whole system self-adapts in regard to its global behavior. Thus, we must be able to formalize in a proper metric space a metaphor of cell dynamics in order to find conditions (decisions, states) that would make cells to self-organize and in which cells self-adapt so as to always satisfy operational constraints (such as those induced by the tissue or the use of resources). Therefore, the main point remains to find conditions in which the system is viable and maintains its shape while renewing. The aim of this paper is to explain the mathematical foundations of this work and describe a simulation tool to study the morphogenesis of a virtual organism.
{"title":"Mutational Analysis-Inspired Algorithms for Cells Self-Organization towards a Dynamic under Viability Constraints","authors":"Alexandra Fronville, A. Sarr, P. Ballet, V. Rodin","doi":"10.1109/SASO.2012.15","DOIUrl":"https://doi.org/10.1109/SASO.2012.15","url":null,"abstract":"In biology, recent techniques in confocal microscopy have produced experimental data which highlights the importance of cellular dynamics in the evolution of biological shapes. Thus, to understand the mechanisms underlying the morphogenesis of multi-cellular organisms, we study this cellular dynamic system in terms of its properties: cell multiplication, cell migration, and apoptosis. Besides, understanding the convergence of the system toward a stable form, involves local interactions between cells. Indeed, the way that cells self-organize through these interactions determines the resulting form. Along with the mechanisms of convergence highlighted above, the dynamic system also undergoes controls established by the nature on the organisms growth. Hence, to let the system viable, the global behavior of cells has to be assessed at every state of their developement and must satisfy the constraints. Otherwise, the whole system self-adapts in regard to its global behavior. Thus, we must be able to formalize in a proper metric space a metaphor of cell dynamics in order to find conditions (decisions, states) that would make cells to self-organize and in which cells self-adapt so as to always satisfy operational constraints (such as those induced by the tissue or the use of resources). Therefore, the main point remains to find conditions in which the system is viable and maintains its shape while renewing. The aim of this paper is to explain the mathematical foundations of this work and describe a simulation tool to study the morphogenesis of a virtual organism.","PeriodicalId":126067,"journal":{"name":"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122490882","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}
Natural multi-agent systems often rely on "correlated random walks" (random walks that are biased toward a current heading) to distribute their agents over a space (e.g., for foraging, search, etc.) Our contribution involves creation of a new movement and pheromone model that applies the concept of heading bias in random walks to a multi-agent, digital-ants system designed for cyber-security monitoring. We examine the relative performance effects of both pheromone and heading bias on speed of discovery of a target and search-area coverage in a two-dimensional network layout. We found that heading bias was unexpectedly helpful in reducing search time and that it was more influential than pheromone for improving coverage. We conclude that while pheromone is very important for rapid discovery, heading bias can also greatly improve both performance metrics.
{"title":"Directional Bias and Pheromone for Discovery and Coverage on Networks","authors":"Glenn A. Fink, K. Berenhaut, C. Oehmen","doi":"10.1109/SASO.2012.32","DOIUrl":"https://doi.org/10.1109/SASO.2012.32","url":null,"abstract":"Natural multi-agent systems often rely on \"correlated random walks\" (random walks that are biased toward a current heading) to distribute their agents over a space (e.g., for foraging, search, etc.) Our contribution involves creation of a new movement and pheromone model that applies the concept of heading bias in random walks to a multi-agent, digital-ants system designed for cyber-security monitoring. We examine the relative performance effects of both pheromone and heading bias on speed of discovery of a target and search-area coverage in a two-dimensional network layout. We found that heading bias was unexpectedly helpful in reducing search time and that it was more influential than pheromone for improving coverage. We conclude that while pheromone is very important for rapid discovery, heading bias can also greatly improve both performance metrics.","PeriodicalId":126067,"journal":{"name":"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126754070","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 systems, which enable runtime adaptation, are promising ways of dealing with environmental changes, including system intrusions or faults. Such software systems must modify themselves to better fit their environment. One of the main approaches to constructing such systems is to introduce multiple control loops. Software evolution is an essential activity for expanding this adaptation capability, and dynamic evolution has been envisaged as a way of systems adapting themselves at runtime. In this paper, we establish a development process to deal with dynamic evolution. We devise a goal model compiler to generate models for designing dynamic evolutions and a programming framework that supports dynamic deployment of control loops. We experimentally applied our approach to a system and discuss how our compiler and framework support dynamic evolution of self-adaptive systems.
{"title":"Towards Dynamic Evolution of Self-Adaptive Systems Based on Dynamic Updating of Control Loops","authors":"Hiroyuki Nakagawa, Akihiko Ohsuga, S. Honiden","doi":"10.1109/SASO.2012.17","DOIUrl":"https://doi.org/10.1109/SASO.2012.17","url":null,"abstract":"Self-adaptive systems, which enable runtime adaptation, are promising ways of dealing with environmental changes, including system intrusions or faults. Such software systems must modify themselves to better fit their environment. One of the main approaches to constructing such systems is to introduce multiple control loops. Software evolution is an essential activity for expanding this adaptation capability, and dynamic evolution has been envisaged as a way of systems adapting themselves at runtime. In this paper, we establish a development process to deal with dynamic evolution. We devise a goal model compiler to generate models for designing dynamic evolutions and a programming framework that supports dynamic deployment of control loops. We experimentally applied our approach to a system and discuss how our compiler and framework support dynamic evolution of self-adaptive systems.","PeriodicalId":126067,"journal":{"name":"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126281203","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}
By analyzing the similarity of a self-organizing system and an optimization process, we highlight that optimization can be considered as self-organization. We analyze the characteristics of some popular met heuristic algorithms such as firefly algorithm and cuckoo search for applications in self-organizing systems.
{"title":"Metaheuristic Algorithms for Self-Organizing Systems: A Tutorial","authors":"Xin-She Yang","doi":"10.1109/SASO.2012.40","DOIUrl":"https://doi.org/10.1109/SASO.2012.40","url":null,"abstract":"By analyzing the similarity of a self-organizing system and an optimization process, we highlight that optimization can be considered as self-organization. We analyze the characteristics of some popular met heuristic algorithms such as firefly algorithm and cuckoo search for applications in self-organizing systems.","PeriodicalId":126067,"journal":{"name":"2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"8 11-12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132434071","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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