{"title":"边缘计算中有限资源下基于aco的任务卸载方法","authors":"Xueshuo Chen, Yuxing Mao, Hongyu Wang, Yihang Xu, Xiong Xiong, Danyang Li","doi":"10.1109/iSPEC53008.2021.9735909","DOIUrl":null,"url":null,"abstract":"Edge computing is put forward to solve the problem of data processing with an increasing number of Internet of Things (IoT) devices and the data generated by them. Task offloading problem gets lots of attention in this field with a great deal of research. However, most research consider data processing and task offloading on cloud server or edge server with virtualization technology rather than resource-constrained terminals (RCTs) where large sets of data come from that cannot even support Docker well. For this reason, this paper proposes a kind of resource model of RCTs and a novel description of IoT tasks that are beneficial to management of IoT resource with which services of IoT are grouped clearly. Then that method makes it convenient for ACO performing to solve task offloading problem under resource-constrained environment. Through the analysis of simulation, this approach can deal with that problem within a short time effectively which ensures the real-time and ultra-lightweight of edge computing system.","PeriodicalId":417862,"journal":{"name":"2021 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ACO-based Task Offloading Method with Limited Resource in Edge Computing\",\"authors\":\"Xueshuo Chen, Yuxing Mao, Hongyu Wang, Yihang Xu, Xiong Xiong, Danyang Li\",\"doi\":\"10.1109/iSPEC53008.2021.9735909\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Edge computing is put forward to solve the problem of data processing with an increasing number of Internet of Things (IoT) devices and the data generated by them. Task offloading problem gets lots of attention in this field with a great deal of research. However, most research consider data processing and task offloading on cloud server or edge server with virtualization technology rather than resource-constrained terminals (RCTs) where large sets of data come from that cannot even support Docker well. For this reason, this paper proposes a kind of resource model of RCTs and a novel description of IoT tasks that are beneficial to management of IoT resource with which services of IoT are grouped clearly. Then that method makes it convenient for ACO performing to solve task offloading problem under resource-constrained environment. Through the analysis of simulation, this approach can deal with that problem within a short time effectively which ensures the real-time and ultra-lightweight of edge computing system.\",\"PeriodicalId\":417862,\"journal\":{\"name\":\"2021 IEEE Sustainable Power and Energy Conference (iSPEC)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Sustainable Power and Energy Conference (iSPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iSPEC53008.2021.9735909\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Sustainable Power and Energy Conference (iSPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iSPEC53008.2021.9735909","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ACO-based Task Offloading Method with Limited Resource in Edge Computing
Edge computing is put forward to solve the problem of data processing with an increasing number of Internet of Things (IoT) devices and the data generated by them. Task offloading problem gets lots of attention in this field with a great deal of research. However, most research consider data processing and task offloading on cloud server or edge server with virtualization technology rather than resource-constrained terminals (RCTs) where large sets of data come from that cannot even support Docker well. For this reason, this paper proposes a kind of resource model of RCTs and a novel description of IoT tasks that are beneficial to management of IoT resource with which services of IoT are grouped clearly. Then that method makes it convenient for ACO performing to solve task offloading problem under resource-constrained environment. Through the analysis of simulation, this approach can deal with that problem within a short time effectively which ensures the real-time and ultra-lightweight of edge computing system.