Proceedings of the 16th ACM Symposium on QoS and Security for Wireless and Mobile Networks最新文献

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An Energy Efficient Architecture of self-sustainable WSN based on Energy Harvesting and Wireless Charging with Consideration of Deployment Cost 考虑部署成本的基于能量收集和无线充电的自我可持续WSN节能架构
Khaled Abid, Ghada Jaber, Hicham Lakhlef, A. Lounis, A. Bouabdallah
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引用次数: 4
Session details: Session 4: IoT Systems 会议详情:会议4:物联网系统
Samir Chouali
{"title":"Session details: Session 4: IoT Systems","authors":"Samir Chouali","doi":"10.1145/3436360","DOIUrl":"https://doi.org/10.1145/3436360","url":null,"abstract":"","PeriodicalId":103892,"journal":{"name":"Proceedings of the 16th ACM Symposium on QoS and Security for Wireless and Mobile Networks","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132002735","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}
引用次数: 0
A Vertex-centric Markov Chain Algorithm for Network Clustering based on b-Coloring 基于b-着色的以顶点为中心的网络聚类马尔可夫链算法
Jianyi Lin, C. Mio
{"title":"A Vertex-centric Markov Chain Algorithm for Network Clustering based on b-Coloring","authors":"Jianyi Lin, C. Mio","doi":"10.1145/3416013.3426459","DOIUrl":"https://doi.org/10.1145/3416013.3426459","url":null,"abstract":"The massive size and complexity of big datasets such as those coming from social, natural and sensor environments raise utmost challenges to unsupervised cluster analysis methods in terms of performance scalability in designing algorithms, also considering parallel and distributed networking context. To cope with these hindrances, the parallelization of clustering techniques, also benefiting from GPU-centered computation, can contribute to fill the gap in applicative areas such as optimization of network routing or management of large-scale IoT networks, thus enabling the extraction, processing and policy making relying on rich network information that are typically represented in the form of graphs. One established approach to clustering graphs is through the coloring techniques, and indeed, graph clustering and graph coloring can be viewed as tied. We devise a graph clustering technique based on a Markov Chain method aimed at b-coloring the data points, that works in efficient vertex-centric parallel manner and produces a valid clustering with reduced number of color classes. We assess our algorithm against synthetic data encapsulating group structure characteristics and present a brief convergence analysis of the method.","PeriodicalId":103892,"journal":{"name":"Proceedings of the 16th ACM Symposium on QoS and Security for Wireless and Mobile Networks","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126338184","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}
引用次数: 0
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