{"title":"车辆边缘云的轨迹感知边缘节点聚类","authors":"Jaewook Lee, Haneul Ko, Sangheon Pack","doi":"10.1109/CCNC.2019.8651870","DOIUrl":null,"url":null,"abstract":"In vehicular edge clouds, tasks from vehicles are processed nearby edge nodes (ENs) and thus low latency services can be provided. However, under high vehicular mobility, frequent service migration between two ENs and increased handover latency can be observed. In this paper, we introduce a trajectory-aware edge node clustering (TENC) scheme in which multiple ENs form a cluster depending on the trajectory of a target vehicle. To attain the optimal performance, we formulate an optimization problem by means of a constrained Markov decision process (CMDP). Evaluation results demonstrate that the obtained optimal policy can minimize service delay significantly.","PeriodicalId":285899,"journal":{"name":"2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Trajectory-Aware Edge Node Clustering in Vehicular Edge Clouds\",\"authors\":\"Jaewook Lee, Haneul Ko, Sangheon Pack\",\"doi\":\"10.1109/CCNC.2019.8651870\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In vehicular edge clouds, tasks from vehicles are processed nearby edge nodes (ENs) and thus low latency services can be provided. However, under high vehicular mobility, frequent service migration between two ENs and increased handover latency can be observed. In this paper, we introduce a trajectory-aware edge node clustering (TENC) scheme in which multiple ENs form a cluster depending on the trajectory of a target vehicle. To attain the optimal performance, we formulate an optimization problem by means of a constrained Markov decision process (CMDP). Evaluation results demonstrate that the obtained optimal policy can minimize service delay significantly.\",\"PeriodicalId\":285899,\"journal\":{\"name\":\"2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)\",\"volume\":\"93 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCNC.2019.8651870\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCNC.2019.8651870","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Trajectory-Aware Edge Node Clustering in Vehicular Edge Clouds
In vehicular edge clouds, tasks from vehicles are processed nearby edge nodes (ENs) and thus low latency services can be provided. However, under high vehicular mobility, frequent service migration between two ENs and increased handover latency can be observed. In this paper, we introduce a trajectory-aware edge node clustering (TENC) scheme in which multiple ENs form a cluster depending on the trajectory of a target vehicle. To attain the optimal performance, we formulate an optimization problem by means of a constrained Markov decision process (CMDP). Evaluation results demonstrate that the obtained optimal policy can minimize service delay significantly.