使用联邦学习的边缘计算节能多任务

IF 0.6 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS International Journal of Pervasive Computing and Communications Pub Date : 2022-07-08 DOI:10.1108/ijpcc-03-2022-0106

Mukesh Soni, N. Nayak, Ashima Kalra, S. Degadwala, Nikhil Kumar Singh, Shweta Singh

{"title":"使用联邦学习的边缘计算节能多任务","authors":"Mukesh Soni, N. Nayak, Ashima Kalra, S. Degadwala, Nikhil Kumar Singh, Shweta Singh","doi":"10.1108/ijpcc-03-2022-0106","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe purpose of this paper is to improve the existing paradigm of edge computing to maintain a balanced energy usage.\n\n\nDesign/methodology/approach\nThe new greedy algorithm is proposed to balance the energy consumption in edge computing.\n\n\nFindings\nThe new greedy algorithm can balance energy more efficiently than the random approach by an average of 66.59 percent.\n\n\nOriginality/value\nThe results are shown in this paper which are better as compared to existing algorithms.\n","PeriodicalId":43952,"journal":{"name":"International Journal of Pervasive Computing and Communications","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Energy efficient multi-tasking for edge computing using federated learning\",\"authors\":\"Mukesh Soni, N. Nayak, Ashima Kalra, S. Degadwala, Nikhil Kumar Singh, Shweta Singh\",\"doi\":\"10.1108/ijpcc-03-2022-0106\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThe purpose of this paper is to improve the existing paradigm of edge computing to maintain a balanced energy usage.\\n\\n\\nDesign/methodology/approach\\nThe new greedy algorithm is proposed to balance the energy consumption in edge computing.\\n\\n\\nFindings\\nThe new greedy algorithm can balance energy more efficiently than the random approach by an average of 66.59 percent.\\n\\n\\nOriginality/value\\nThe results are shown in this paper which are better as compared to existing algorithms.\\n\",\"PeriodicalId\":43952,\"journal\":{\"name\":\"International Journal of Pervasive Computing and Communications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2022-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Pervasive Computing and Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/ijpcc-03-2022-0106\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Pervasive Computing and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/ijpcc-03-2022-0106","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}

引用次数: 0

摘要

本文的目的是改进现有的边缘计算范式，以保持平衡的能源使用。设计/方法/方法为了平衡边缘计算中的能量消耗，提出了一种新的贪婪算法。结果贪心算法的能量平衡效率比随机算法平均高66.59%。与现有的算法相比，本文给出了更好的结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Energy efficient multi-tasking for edge computing using federated learning

Purpose The purpose of this paper is to improve the existing paradigm of edge computing to maintain a balanced energy usage. Design/methodology/approach The new greedy algorithm is proposed to balance the energy consumption in edge computing. Findings The new greedy algorithm can balance energy more efficiently than the random approach by an average of 66.59 percent. Originality/value The results are shown in this paper which are better as compared to existing algorithms.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Journal of Pervasive Computing and Communications COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-

CiteScore

6.60

自引率

0.00%

发文量