{"title":"基于组合加权法的多接入边缘计算多目标卸载决策","authors":"Dan Ye, Xiaogang Wang, Jin Hou","doi":"10.11648/j.iotcc.20210903.11","DOIUrl":null,"url":null,"abstract":": Generally, in the edge computing scenario, edge devices can offload tasks to the edge servers to reduce device energy consumption and task execution delay. It is necessary to find an offloading strategy which can balance and minimize the task execution delay and device energy consumption. This is usually classified as a multi-objective problem. It is a common method to get the Pareto optimal solution set by using multi-objective optimization algorithm. However, there is a problem about how to find out the eclectic optimal solution that can embody the user's subjective consciousness and meet the objective information of Pareto optimal solution set. This paper solved this problem by combining subjective and objective combination weighting method. First, the subjective weight matrix which reflects the user's subjective consciousness is obtained by analytic hierarchy process. Then, the objective weight matrix which can embody the objective information of the index is obtained through the entropy method. Finally, the combination weight matrix is obtained by subjective and objective weighting method. After comprehensively evaluating the Pareto optimal solution set, the solution with the minimum comprehensive evaluation value is regarded as the Pareto compromise optimal solution. In this paper, the combination weighting method is applied to multi-access edge computing scenario and verify its feasibility in this scenario.","PeriodicalId":173948,"journal":{"name":"Internet of Things and Cloud Computing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-objective Offloading Decision Based on Combination Weighting Method for Multi-access Edge Computing\",\"authors\":\"Dan Ye, Xiaogang Wang, Jin Hou\",\"doi\":\"10.11648/j.iotcc.20210903.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": Generally, in the edge computing scenario, edge devices can offload tasks to the edge servers to reduce device energy consumption and task execution delay. It is necessary to find an offloading strategy which can balance and minimize the task execution delay and device energy consumption. This is usually classified as a multi-objective problem. It is a common method to get the Pareto optimal solution set by using multi-objective optimization algorithm. However, there is a problem about how to find out the eclectic optimal solution that can embody the user's subjective consciousness and meet the objective information of Pareto optimal solution set. This paper solved this problem by combining subjective and objective combination weighting method. First, the subjective weight matrix which reflects the user's subjective consciousness is obtained by analytic hierarchy process. Then, the objective weight matrix which can embody the objective information of the index is obtained through the entropy method. Finally, the combination weight matrix is obtained by subjective and objective weighting method. After comprehensively evaluating the Pareto optimal solution set, the solution with the minimum comprehensive evaluation value is regarded as the Pareto compromise optimal solution. In this paper, the combination weighting method is applied to multi-access edge computing scenario and verify its feasibility in this scenario.\",\"PeriodicalId\":173948,\"journal\":{\"name\":\"Internet of Things and Cloud Computing\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Internet of Things and Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11648/j.iotcc.20210903.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet of Things and Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/j.iotcc.20210903.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-objective Offloading Decision Based on Combination Weighting Method for Multi-access Edge Computing
: Generally, in the edge computing scenario, edge devices can offload tasks to the edge servers to reduce device energy consumption and task execution delay. It is necessary to find an offloading strategy which can balance and minimize the task execution delay and device energy consumption. This is usually classified as a multi-objective problem. It is a common method to get the Pareto optimal solution set by using multi-objective optimization algorithm. However, there is a problem about how to find out the eclectic optimal solution that can embody the user's subjective consciousness and meet the objective information of Pareto optimal solution set. This paper solved this problem by combining subjective and objective combination weighting method. First, the subjective weight matrix which reflects the user's subjective consciousness is obtained by analytic hierarchy process. Then, the objective weight matrix which can embody the objective information of the index is obtained through the entropy method. Finally, the combination weight matrix is obtained by subjective and objective weighting method. After comprehensively evaluating the Pareto optimal solution set, the solution with the minimum comprehensive evaluation value is regarded as the Pareto compromise optimal solution. In this paper, the combination weighting method is applied to multi-access edge computing scenario and verify its feasibility in this scenario.