The FoCAS workshop focuses on identifying and addressing challenges related to the development of collective adaptive systems -- systems composed of massive numbers of components in which both invidual elements and the system as whole adapt to changing execution conditions. The 2014 workshop at SASO is the 2nd occurrence of the workshop, following the first successful FOCAS workshop held at the European Conference on ALife (ECAL) in 2013.
{"title":"2nd FOCAS Workshop on Fundamentals of Collective Adaptive Systems","authors":"Giacomo Cabri, E. Hart","doi":"10.1109/SASOW.2014.8","DOIUrl":"https://doi.org/10.1109/SASOW.2014.8","url":null,"abstract":"The FoCAS workshop focuses on identifying and addressing challenges related to the development of collective adaptive systems -- systems composed of massive numbers of components in which both invidual elements and the system as whole adapt to changing execution conditions. The 2014 workshop at SASO is the 2nd occurrence of the workshop, following the first successful FOCAS workshop held at the European Conference on ALife (ECAL) in 2013.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"61 1","pages":"6-7"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88329221","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 functionality and the performance of smart environment applications can be hampered by faults. Fault tolerance solutions aim to achieve graceful performance degradation in the presence of faults, ideally without leading to application failures. This is a reactive approach and, by itself, gives little flexibility and time for preventing potential failures. We propose a proactive fault-prevention framework, which predicts potential low-level hardware, software and network faults and tries to prevent them via dynamic adaptation. We envision that the proposed framework will provide better control over performance degradation of smart environment applications, increased reliability and availability, and a reduced number of manual user interventions.
{"title":"Fault-Prevention in Smart Environments for Dependable Applications","authors":"E. Warriach, T. Ozcelebi, J. Lukkien","doi":"10.1109/SASO.2014.35","DOIUrl":"https://doi.org/10.1109/SASO.2014.35","url":null,"abstract":"The functionality and the performance of smart environment applications can be hampered by faults. Fault tolerance solutions aim to achieve graceful performance degradation in the presence of faults, ideally without leading to application failures. This is a reactive approach and, by itself, gives little flexibility and time for preventing potential failures. We propose a proactive fault-prevention framework, which predicts potential low-level hardware, software and network faults and tries to prevent them via dynamic adaptation. We envision that the proposed framework will provide better control over performance degradation of smart environment applications, increased reliability and availability, and a reduced number of manual user interventions.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"36 1","pages":"183-184"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90619206","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 many technical systems, such as smart grids, the central issue is to enable multiple devices to solve a resource allocation problem in a cooperative manner. If the devices' ability to change their contribution is subject to inertia, the problem has to be solved proactively. This means that the allocation of resources is scheduled beforehand, based on predictions of the future demand. Because of the scheduling problem's complexity, schedules should be created rather sporadically for a coarse-grained time pattern. However, because the resource allocation problem has to be solved for all time steps and the demand and provision of resources is uncertain, devices have to reactively adapt their contributions according to the current circumstances. In this paper, we present a mechanism that allows the participants to incorporate the information of proactively created schedules in their reactive decisions in order to steer the system in a stable and efficient way. In particular, the decisions are guided by schedules that already include information about possible uncertainties. While this combination avoids inertia based problems, it significantly reduces the computational costs of searching for high quality solutions. Throughout the paper, the problem of maintaining the balance between energy production and consumption in decentralized autonomous power management systems serves to illustrate our algorithm and results.
{"title":"Proactive Guidance for Dynamic and Cooperative Resource Allocation under Uncertainties","authors":"Gerrit Anders, Florian Siefert, M. Mair, W. Reif","doi":"10.1109/SASO.2014.14","DOIUrl":"https://doi.org/10.1109/SASO.2014.14","url":null,"abstract":"In many technical systems, such as smart grids, the central issue is to enable multiple devices to solve a resource allocation problem in a cooperative manner. If the devices' ability to change their contribution is subject to inertia, the problem has to be solved proactively. This means that the allocation of resources is scheduled beforehand, based on predictions of the future demand. Because of the scheduling problem's complexity, schedules should be created rather sporadically for a coarse-grained time pattern. However, because the resource allocation problem has to be solved for all time steps and the demand and provision of resources is uncertain, devices have to reactively adapt their contributions according to the current circumstances. In this paper, we present a mechanism that allows the participants to incorporate the information of proactively created schedules in their reactive decisions in order to steer the system in a stable and efficient way. In particular, the decisions are guided by schedules that already include information about possible uncertainties. While this combination avoids inertia based problems, it significantly reduces the computational costs of searching for high quality solutions. Throughout the paper, the problem of maintaining the balance between energy production and consumption in decentralized autonomous power management systems serves to illustrate our algorithm and results.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"12 1","pages":"21-30"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88037889","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}
Cooperation is the foundation of wireless ad hoc networks with nodes forwarding their neighbors' packets for the common good. However, energy and bandwidth constraints combined with selfish behaviour lead to collapsed networks where all nodes defect. Researchers have tried to incentivize or enforce the nodes for cooperation in various ways. However, these techniques do not consider the heterogeneous networks in which a diverse set of nodes with different cognitive capabilities exist. Furthermore, in ad hoc networks identity is a fuzzy concept. It is easy to forge multiple identities and hide defective behaviour. Moreover, the nature of the wireless medium is always ambiguous due to collisions, interference and asymmetric links. In all this uncertainty, having complete information about the intentions of the nodes and acting on it is not straightforward. Backed by evolutionary game theory and multi-agent systems research, we adapt and modify two meta strategies to embrace this uncertainty. These modified meta strategies, Win Stay Loose Shift and Stochastic Imitate Best Strategy, do not require strict identity information and only depend on nodes' own capabilities. Nodes monitor the traffic in their neighbourhood by using a two-hop overhearing method, and decide whether they should be cooperative or defective. We show that nodes are able to discover and use the best strategy in their locality and protect themselves against the exploitation by free riders who devise Sybil attacks by changing their identities.
{"title":"Sybil-Resistant Meta Strategies for the Forwarder's Dilemma","authors":"Y. Durmus, Andreas Loukas, E. Onur, K. Langendoen","doi":"10.1109/SASO.2014.21","DOIUrl":"https://doi.org/10.1109/SASO.2014.21","url":null,"abstract":"Cooperation is the foundation of wireless ad hoc networks with nodes forwarding their neighbors' packets for the common good. However, energy and bandwidth constraints combined with selfish behaviour lead to collapsed networks where all nodes defect. Researchers have tried to incentivize or enforce the nodes for cooperation in various ways. However, these techniques do not consider the heterogeneous networks in which a diverse set of nodes with different cognitive capabilities exist. Furthermore, in ad hoc networks identity is a fuzzy concept. It is easy to forge multiple identities and hide defective behaviour. Moreover, the nature of the wireless medium is always ambiguous due to collisions, interference and asymmetric links. In all this uncertainty, having complete information about the intentions of the nodes and acting on it is not straightforward. Backed by evolutionary game theory and multi-agent systems research, we adapt and modify two meta strategies to embrace this uncertainty. These modified meta strategies, Win Stay Loose Shift and Stochastic Imitate Best Strategy, do not require strict identity information and only depend on nodes' own capabilities. Nodes monitor the traffic in their neighbourhood by using a two-hop overhearing method, and decide whether they should be cooperative or defective. We show that nodes are able to discover and use the best strategy in their locality and protect themselves against the exploitation by free riders who devise Sybil attacks by changing their identities.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"6 1","pages":"90-99"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81171835","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 identify two different forms of diversity present in engineered collective systems, namely heterogeneity (genotypic/phenotypic diversity) and dynamics (temporal diversity). Three qualitatively different case studies are analysed, and it is shown that both forms of diversity can be beneficial in very different problem and application domains. Behavioural diversity is shown to be motivated by input diversity and this observation is used to present recommendations for designers of collective systems.
{"title":"It's Good to Be Different: Diversity, Heterogeneity, and Dynamics in Collective Systems","authors":"Peter R. Lewis, Harry Goldingay, Vivek Nallur","doi":"10.1109/SASOW.2014.36","DOIUrl":"https://doi.org/10.1109/SASOW.2014.36","url":null,"abstract":"We identify two different forms of diversity present in engineered collective systems, namely heterogeneity (genotypic/phenotypic diversity) and dynamics (temporal diversity). Three qualitatively different case studies are analysed, and it is shown that both forms of diversity can be beneficial in very different problem and application domains. Behavioural diversity is shown to be motivated by input diversity and this observation is used to present recommendations for designers of collective systems.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"18 1","pages":"84-89"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79318299","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}
Jan Kantert, Sebastian Bödelt, Sarah Edenhofer, Sven Tomforde, J. Hähner, C. Müller-Schloer
In an open Trusted Desktop Grid system, users can voluntarily participate in order to share resources. Thereby, computational trust is used to isolate malicious agents. Since a fully self-organised solution can suffer in emergent situations like the trust-breakdown scenario, we investigate an additional normative entity to guide the overall system behaviour by still keeping the autonomy of all agents. Within this interactive demonstration, we present a 3D visualisation of the current system status showing how the mutual trust relations between agents and / or groups of agents could be used as basis for automated decisions to issue norms.
{"title":"Interactive Simulation of an Open Trusted Desktop Grid System with Visualisation in 3D","authors":"Jan Kantert, Sebastian Bödelt, Sarah Edenhofer, Sven Tomforde, J. Hähner, C. Müller-Schloer","doi":"10.1109/SASO.2014.39","DOIUrl":"https://doi.org/10.1109/SASO.2014.39","url":null,"abstract":"In an open Trusted Desktop Grid system, users can voluntarily participate in order to share resources. Thereby, computational trust is used to isolate malicious agents. Since a fully self-organised solution can suffer in emergent situations like the trust-breakdown scenario, we investigate an additional normative entity to guide the overall system behaviour by still keeping the autonomy of all agents. Within this interactive demonstration, we present a 3D visualisation of the current system status showing how the mutual trust relations between agents and / or groups of agents could be used as basis for automated decisions to issue norms.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"56 1","pages":"191-192"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79651593","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}
Benedikt Eberhardinger, W. Reif, F. Wotawa, T. Holvoet
Welcome to the first edition of the Workshop on Quality Assurance for Self-adaptive, Self-organising Systems (QA4SASO 2014). Developing self-adaptive, self-organising systems that fulfil the requirements of different stakeholders is no simple matter. Quality assurance is required at each phase of the entire development process, starting from requirements elicitation, agent design, system architecture design, and finally in the implementation, testing, and deployment of the system. The quality of the artefacts from each development phase affects the rest of the system, since all parts are closely related to each other. Furthermore, the shift of adaptation decisions from design-time to run-time - necessitated by the need of the systems to adapt to changing circumstances - makes it difficult, but even more essential, to assure high quality standards in these kind of systems. Accordingly, the analysis and evaluation of these self-systems has to take into account the specific operational context to achieve high quality standards. As a consequence, we like to address the following challenges in the workshop on quality assurance for self-adaptive, self-organising systems: Evolutionary developing system, interleaving mechanisms, uncertainty according the system environment, open system architecture, and large number of system participants. The necessity to investigate this field has already been recognised and addressed in different communities, but there exists so far no platform to bring all these communities together. Therefore, the workshop provides an open stage for discussions about the different aspects of quality assurance for self-adaptive, self-organising systems.
{"title":"Quality Assurance for Self-Adaptive, Self-Organising Systems (Message from the Workshop Organisers)","authors":"Benedikt Eberhardinger, W. Reif, F. Wotawa, T. Holvoet","doi":"10.1109/SASOW.2014.30","DOIUrl":"https://doi.org/10.1109/SASOW.2014.30","url":null,"abstract":"Welcome to the first edition of the Workshop on Quality Assurance for Self-adaptive, Self-organising Systems (QA4SASO 2014). Developing self-adaptive, self-organising systems that fulfil the requirements of different stakeholders is no simple matter. Quality assurance is required at each phase of the entire development process, starting from requirements elicitation, agent design, system architecture design, and finally in the implementation, testing, and deployment of the system. The quality of the artefacts from each development phase affects the rest of the system, since all parts are closely related to each other. Furthermore, the shift of adaptation decisions from design-time to run-time - necessitated by the need of the systems to adapt to changing circumstances - makes it difficult, but even more essential, to assure high quality standards in these kind of systems. Accordingly, the analysis and evaluation of these self-systems has to take into account the specific operational context to achieve high quality standards. As a consequence, we like to address the following challenges in the workshop on quality assurance for self-adaptive, self-organising systems: Evolutionary developing system, interleaving mechanisms, uncertainty according the system environment, open system architecture, and large number of system participants. The necessity to investigate this field has already been recognised and addressed in different communities, but there exists so far no platform to bring all these communities together. Therefore, the workshop provides an open stage for discussions about the different aspects of quality assurance for self-adaptive, self-organising systems.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"9 1","pages":"108-109"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75811073","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 paper we investigate scalability issues of self-synchronization emergent properties, described with the pulse coupled oscillator model. As in the pulse coupled oscillator model the information propagation process is a gossip-like process, huge amounts of network traffic can be generated, causing thus scalability issues of the whole collective adaptive systems. These issues are even more emphasized in collective adaptive heterogeneous systems called Machine-to-Machine (M2M) systems. Namely, these systems consist not only from one large complex network, but also from a larger number of different interconnected complex networks. The easiest way to reduce network traffic in large networks is to use different overlay network topologies. An overlay network topology can be seen as a layer of a virtual network topology on top of a physical network, enabling significantly less messages to be exchanged during a synchronization process. However, the implementation process of overlay network topologies is not very efficient in real-world environments, as will be discussed in the paper. Therefore, we propose a mechanism for selective coupling implemented on the sender side that can be used to reduce both network traffic and time to synchronization without negatively affecting the entire synchronization process. Moreover, in some cases the rate of successful synchronization outcomes can be also increased when using the proposed mechanism.
{"title":"Scalability Issues of Firefly-Based Self-Synchronization in Collective Adaptive Systems","authors":"I. Bojic, T. Lipić, M. Kusek","doi":"10.1109/SASOW.2014.15","DOIUrl":"https://doi.org/10.1109/SASOW.2014.15","url":null,"abstract":"In this paper we investigate scalability issues of self-synchronization emergent properties, described with the pulse coupled oscillator model. As in the pulse coupled oscillator model the information propagation process is a gossip-like process, huge amounts of network traffic can be generated, causing thus scalability issues of the whole collective adaptive systems. These issues are even more emphasized in collective adaptive heterogeneous systems called Machine-to-Machine (M2M) systems. Namely, these systems consist not only from one large complex network, but also from a larger number of different interconnected complex networks. The easiest way to reduce network traffic in large networks is to use different overlay network topologies. An overlay network topology can be seen as a layer of a virtual network topology on top of a physical network, enabling significantly less messages to be exchanged during a synchronization process. However, the implementation process of overlay network topologies is not very efficient in real-world environments, as will be discussed in the paper. Therefore, we propose a mechanism for selective coupling implemented on the sender side that can be used to reduce both network traffic and time to synchronization without negatively affecting the entire synchronization process. Moreover, in some cases the rate of successful synchronization outcomes can be also increased when using the proposed mechanism.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"24 1","pages":"68-73"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83120637","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 Collective Adaptive Systems problem is particularly challenging when applied to resource allocation and resource coordination in wireless tactical networks. This paper attempts to characterize the problem in detail in an incremental manner, starting with the simplest version of the problem that includes many assumptions and then building up the complexity of the problem by removing the assumptions. The objective is for researchers to be able to understand the full complexity and subtleties of the problem and to provide a common language for discussing the problems, assumptions, and solutions.
{"title":"A Perspective on Defining the Collective Adaptive Systems Problem","authors":"Niranjan Suri, A. Scott","doi":"10.1109/SASOW.2014.12","DOIUrl":"https://doi.org/10.1109/SASOW.2014.12","url":null,"abstract":"The Collective Adaptive Systems problem is particularly challenging when applied to resource allocation and resource coordination in wireless tactical networks. This paper attempts to characterize the problem in detail in an incremental manner, starting with the simplest version of the problem that includes many assumptions and then building up the complexity of the problem by removing the assumptions. The objective is for researchers to be able to understand the full complexity and subtleties of the problem and to provide a common language for discussing the problems, assumptions, and solutions.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"113 1","pages":"26-31"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85279999","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}
Collaborative learning in collective adaptive systems is an active, open research area. In the Allow Ensembles project, we investigate this problem by a component called Evolutionary Knowledge. One problem arising in this context is that concepts of collaborative learning can hardly be studied without an actual real-world system. In this paper, we present our concept of a simulation tool of a real-world urban traffic system used as a framework to investigate collaborative learning. In contrast to existing ready-to-use traffic simulators, its purpose is not the accurate simulation of microscopic or macroscopic traffic flow models. Instead, it is used to generate data to train a knowledge model learning context parameters and their interrelations, which cannot be deduced from an analytical description of the system, but arise as emergent properties from the complexity of the system. Using the simulation we want to investigate the effects of different collaborative learning strategies on emergence in a complex urban mobility system applying different knowledge exchange patterns among entities. We describe the need for and the area of application of our simulator, show the differences to existing traffic simulation tools, and present an outline of its conceptual architecture.
{"title":"Towards a Real-World Simulator for Collaborative Distributed Learning in the Scenario of Urban Mobility","authors":"Andreas Poxrucker, G. Bahle, P. Lukowicz","doi":"10.1109/SASOW.2014.18","DOIUrl":"https://doi.org/10.1109/SASOW.2014.18","url":null,"abstract":"Collaborative learning in collective adaptive systems is an active, open research area. In the Allow Ensembles project, we investigate this problem by a component called Evolutionary Knowledge. One problem arising in this context is that concepts of collaborative learning can hardly be studied without an actual real-world system. In this paper, we present our concept of a simulation tool of a real-world urban traffic system used as a framework to investigate collaborative learning. In contrast to existing ready-to-use traffic simulators, its purpose is not the accurate simulation of microscopic or macroscopic traffic flow models. Instead, it is used to generate data to train a knowledge model learning context parameters and their interrelations, which cannot be deduced from an analytical description of the system, but arise as emergent properties from the complexity of the system. Using the simulation we want to investigate the effects of different collaborative learning strategies on emergence in a complex urban mobility system applying different knowledge exchange patterns among entities. We describe the need for and the area of application of our simulator, show the differences to existing traffic simulation tools, and present an outline of its conceptual architecture.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"26 1","pages":"44-48"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86141706","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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