{"title":"用于高性能物联网网络的团优先自适应路由","authors":"Yang-Hsin Fan","doi":"10.1109/CCSSE.2016.7784353","DOIUrl":null,"url":null,"abstract":"In this work, we propose clique-first adaptive routes (CFAR) for high-performance internet of things (IoT) networks. In the beginning, CFAR classifies IoT to construct a set of clique class. Second, it sets a class of path for each clique. Third, it calculates executing time for first path of first clique to determine each performance. Next, computing execution time for the rest of paths of first clique arranges each performance of IoT. After that, to iterate the previous steps for each clique sets the role of host. While all paths and IoT are evaluated, a high-performance IoT networks can be obtained. The effectiveness of CFAR is proven in experimental results that CFAR achieve 1.98 times to compare average for all benchmarks.","PeriodicalId":136809,"journal":{"name":"2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Clique-first adaptive routes for high performance IoT networks\",\"authors\":\"Yang-Hsin Fan\",\"doi\":\"10.1109/CCSSE.2016.7784353\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we propose clique-first adaptive routes (CFAR) for high-performance internet of things (IoT) networks. In the beginning, CFAR classifies IoT to construct a set of clique class. Second, it sets a class of path for each clique. Third, it calculates executing time for first path of first clique to determine each performance. Next, computing execution time for the rest of paths of first clique arranges each performance of IoT. After that, to iterate the previous steps for each clique sets the role of host. While all paths and IoT are evaluated, a high-performance IoT networks can be obtained. The effectiveness of CFAR is proven in experimental results that CFAR achieve 1.98 times to compare average for all benchmarks.\",\"PeriodicalId\":136809,\"journal\":{\"name\":\"2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCSSE.2016.7784353\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCSSE.2016.7784353","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Clique-first adaptive routes for high performance IoT networks
In this work, we propose clique-first adaptive routes (CFAR) for high-performance internet of things (IoT) networks. In the beginning, CFAR classifies IoT to construct a set of clique class. Second, it sets a class of path for each clique. Third, it calculates executing time for first path of first clique to determine each performance. Next, computing execution time for the rest of paths of first clique arranges each performance of IoT. After that, to iterate the previous steps for each clique sets the role of host. While all paths and IoT are evaluated, a high-performance IoT networks can be obtained. The effectiveness of CFAR is proven in experimental results that CFAR achieve 1.98 times to compare average for all benchmarks.
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