{"title":"一种新的移动边缘计算联合卸载和资源分配方案","authors":"Boutheina Dab, N. Aitsaadi, R. Langar","doi":"10.1109/CCNC.2019.8651879","DOIUrl":null,"url":null,"abstract":"Recently Mobile Edge Computing (MEC) promises a great latency reduction by pushing mobile computing and storage to the network edge. MEC solutions allows the intensive applications to be computed in nearby servers at the edge. In this work, we envision a multi-user WiFi-based MEC architecture. We tackle the problem of joint task assignment and resource allocation. The main objective of our scheme is to minimize the energy consumption on the mobile terminal side under the application latency constraint. Based on extensive simulations conducted in NS3 while considering real input traces, we show that our approach outperforms the related prominent strategies in terms of: i) energy consumption and ii) completion delay.","PeriodicalId":285899,"journal":{"name":"2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"A Novel Joint Offloading and Resource Allocation Scheme for Mobile Edge Computing\",\"authors\":\"Boutheina Dab, N. Aitsaadi, R. Langar\",\"doi\":\"10.1109/CCNC.2019.8651879\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently Mobile Edge Computing (MEC) promises a great latency reduction by pushing mobile computing and storage to the network edge. MEC solutions allows the intensive applications to be computed in nearby servers at the edge. In this work, we envision a multi-user WiFi-based MEC architecture. We tackle the problem of joint task assignment and resource allocation. The main objective of our scheme is to minimize the energy consumption on the mobile terminal side under the application latency constraint. Based on extensive simulations conducted in NS3 while considering real input traces, we show that our approach outperforms the related prominent strategies in terms of: i) energy consumption and ii) completion delay.\",\"PeriodicalId\":285899,\"journal\":{\"name\":\"2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"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.2019.8651879\",\"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.2019.8651879","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Joint Offloading and Resource Allocation Scheme for Mobile Edge Computing
Recently Mobile Edge Computing (MEC) promises a great latency reduction by pushing mobile computing and storage to the network edge. MEC solutions allows the intensive applications to be computed in nearby servers at the edge. In this work, we envision a multi-user WiFi-based MEC architecture. We tackle the problem of joint task assignment and resource allocation. The main objective of our scheme is to minimize the energy consumption on the mobile terminal side under the application latency constraint. Based on extensive simulations conducted in NS3 while considering real input traces, we show that our approach outperforms the related prominent strategies in terms of: i) energy consumption and ii) completion delay.