Spatial publish subscribe (SPS) is a basic primitive underlying many real-time, interactive applications such as online games or discrete-time simulations. Voronoi Self-organizing Overlay (VSO) is a scalable SPS service designed to adjust workload automatically to avoid system overload or underload. We investigate the deployment of VSO on Planet Lab, to evaluate whether it is feasible to scale up SPS operations in real environments. Our results show that by ensuring enough capacities for super-nodes (called matchers), such automatic load balancing can scale up a Second Life region to over 200 entities while still maintaining proper discovery consistency.
{"title":"Deployment Issues of Voronoi Self-Organizing Overlays","authors":"Man-Chun Li, Shun-Yun Hu, Kuan-Ta Chen","doi":"10.1109/SASO.2011.35","DOIUrl":"https://doi.org/10.1109/SASO.2011.35","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. Voronoi Self-organizing Overlay (VSO) is a scalable SPS service designed to adjust workload automatically to avoid system overload or underload. We investigate the deployment of VSO on Planet Lab, to evaluate whether it is feasible to scale up SPS operations in real environments. Our results show that by ensuring enough capacities for super-nodes (called matchers), such automatic load balancing can scale up a Second Life region to over 200 entities while still maintaining proper discovery consistency.","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":"128975448","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 area of self-stabilization in large scale networks has been received increasing attention among researchers, since self-stabilization provides a foundation for self-properties, including self-healing, self-organizing and self-adaptive. This paper makes contributions in two areas. First, we describe a new extended approach of self-stabilization, called self-stabilization with service guarantee. Second, we propose a self-stabilizing protocol computing and preserving the knowledge of neighbor clusters, called CNK. A cluster-head maintains about each neighbor cluster: the identity of its head, paths leading to it, and the list of members. The most interesting property of CNK is the service guarantee during the stabilization phase. CNK quickly provides, in at most 4 rounds, the following minimal useful service: "each cluster-head knows valid paths leading to heads of all its neighbor clusters". CNK protocol preserves the minimal service despite changes in the clustering structure (creation of new clusters, restructuring or crumbling of existing clusters). The knowledge of neighbor clusters is thus highly available. This knowledge is enough to allow the continuity functioning of hierarchical protocols as hierarchical routing protocols.
{"title":"Self-Stabilizing Computation and Preservation of Knowledge of Neighbor Clusters","authors":"C. Johnen, Fouzi Mekhaldi","doi":"10.1109/SASO.2011.15","DOIUrl":"https://doi.org/10.1109/SASO.2011.15","url":null,"abstract":"The area of self-stabilization in large scale networks has been received increasing attention among researchers, since self-stabilization provides a foundation for self-properties, including self-healing, self-organizing and self-adaptive. This paper makes contributions in two areas. First, we describe a new extended approach of self-stabilization, called self-stabilization with service guarantee. Second, we propose a self-stabilizing protocol computing and preserving the knowledge of neighbor clusters, called CNK. A cluster-head maintains about each neighbor cluster: the identity of its head, paths leading to it, and the list of members. The most interesting property of CNK is the service guarantee during the stabilization phase. CNK quickly provides, in at most 4 rounds, the following minimal useful service: \"each cluster-head knows valid paths leading to heads of all its neighbor clusters\". CNK protocol preserves the minimal service despite changes in the clustering structure (creation of new clusters, restructuring or crumbling of existing clusters). The knowledge of neighbor clusters is thus highly available. This knowledge is enough to allow the continuity functioning of hierarchical protocols as hierarchical routing protocols.","PeriodicalId":165565,"journal":{"name":"2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"37 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":"127887132","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}
M. Zeller, C. Prehofer, Gereon Weiss, D. Eilers, R. Knorr
While there has been considerable work on self-adaptive systems, applying these techniques to networked, embedded systems poses several new problems due to the requirements of embedded real-time systems. Among others, we have to consider memory and hardware limitations, as well as task schedulability and timing dependencies. The goal of this paper is to find a correct placement of software components efficiently, even though most of these individual constraints are highly intractable (NP-complete). This is a prerequisite for runtime adaptation in such domains and can be used for system optimization, extension or failure handling. We introduce an integrated model of system constraints for efficient computation of software component allocation, focusing on automotive embedded systems. For solving these, we have developed and compared two techniques based on SAT solving and Simulated Annealing, which enforce placement constraints efficiently. This reduces the size of the constraints significantly, but still leads to 2 million variables and more than 126 thousand equations in our case study with realistic automotive system settings. We show that both approaches provide solutions in several seconds on current commodity hardware, and show that SAT solving is more efficient for larger sets of equations.
{"title":"Towards Self-Adaptation in Real-Time, Networked Systems: Efficient Solving of System Constraints for Automotive Embedded Systems","authors":"M. Zeller, C. Prehofer, Gereon Weiss, D. Eilers, R. Knorr","doi":"10.1109/SASO.2011.19","DOIUrl":"https://doi.org/10.1109/SASO.2011.19","url":null,"abstract":"While there has been considerable work on self-adaptive systems, applying these techniques to networked, embedded systems poses several new problems due to the requirements of embedded real-time systems. Among others, we have to consider memory and hardware limitations, as well as task schedulability and timing dependencies. The goal of this paper is to find a correct placement of software components efficiently, even though most of these individual constraints are highly intractable (NP-complete). This is a prerequisite for runtime adaptation in such domains and can be used for system optimization, extension or failure handling. We introduce an integrated model of system constraints for efficient computation of software component allocation, focusing on automotive embedded systems. For solving these, we have developed and compared two techniques based on SAT solving and Simulated Annealing, which enforce placement constraints efficiently. This reduces the size of the constraints significantly, but still leads to 2 million variables and more than 126 thousand equations in our case study with realistic automotive system settings. We show that both approaches provide solutions in several seconds on current commodity hardware, and show that SAT solving is more efficient for larger sets of equations.","PeriodicalId":165565,"journal":{"name":"2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems","volume":"99 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":"126842070","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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