边缘云平台中的多设备任务卸载与调度

Moch Yasin, T. Ahmad, R. Ijtihadie
{"title":"边缘云平台中的多设备任务卸载与调度","authors":"Moch Yasin, T. Ahmad, R. Ijtihadie","doi":"10.1109/COMNETSAT53002.2021.9530831","DOIUrl":null,"url":null,"abstract":"Offloading is the way we manage jobs in mobile computing. We execute some jobs in the mobile device itself, cloud, or fog server in remote areas with more computing capability through the internet. Many researchers focus on minimizing mobile energy consumption by profiling the jobs, choosing the right combination of mobile-cloud execution. Little researchers focus on scheduling the job execution. In contrast, this execution schedule determines overall energy consumption and execution time of all mobile devices in a group of offloading, such as healthcare and security systems. Here, we propose a scheduled data transfer and job execution to minimize energy consumption and offloading time. Also, the scheduled offloading is compared to unscheduled ones in a cloud-edge platform. We get a significant time efficiency of 54 percent and -0,32 percent efficiency of energy from the simulation.","PeriodicalId":148136,"journal":{"name":"2021 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-Device Task Offloading with Scheduling in an Edge Cloud Platform\",\"authors\":\"Moch Yasin, T. Ahmad, R. Ijtihadie\",\"doi\":\"10.1109/COMNETSAT53002.2021.9530831\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Offloading is the way we manage jobs in mobile computing. We execute some jobs in the mobile device itself, cloud, or fog server in remote areas with more computing capability through the internet. Many researchers focus on minimizing mobile energy consumption by profiling the jobs, choosing the right combination of mobile-cloud execution. Little researchers focus on scheduling the job execution. In contrast, this execution schedule determines overall energy consumption and execution time of all mobile devices in a group of offloading, such as healthcare and security systems. Here, we propose a scheduled data transfer and job execution to minimize energy consumption and offloading time. Also, the scheduled offloading is compared to unscheduled ones in a cloud-edge platform. We get a significant time efficiency of 54 percent and -0,32 percent efficiency of energy from the simulation.\",\"PeriodicalId\":148136,\"journal\":{\"name\":\"2021 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMNETSAT53002.2021.9530831\",\"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 International Conference on Communication, Networks and Satellite (COMNETSAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMNETSAT53002.2021.9530831","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

卸载是我们在移动计算中管理工作的方式。我们通过互联网在具有更多计算能力的偏远地区的移动设备本身、云或雾服务器上执行一些工作。许多研究人员专注于通过分析工作,选择正确的移动云执行组合来最大限度地减少移动能耗。很少有研究者关注工作执行的调度。相反,此执行计划决定了一组卸载(例如医疗保健和安全系统)中所有移动设备的总体能耗和执行时间。在这里,我们提出了一个计划的数据传输和作业执行,以最大限度地减少能耗和卸载时间。此外,在云边缘平台中,将计划的卸载与未计划的卸载进行比较。通过仿真,我们获得了54%的时间效率和- 0.32%的能量效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-Device Task Offloading with Scheduling in an Edge Cloud Platform
Offloading is the way we manage jobs in mobile computing. We execute some jobs in the mobile device itself, cloud, or fog server in remote areas with more computing capability through the internet. Many researchers focus on minimizing mobile energy consumption by profiling the jobs, choosing the right combination of mobile-cloud execution. Little researchers focus on scheduling the job execution. In contrast, this execution schedule determines overall energy consumption and execution time of all mobile devices in a group of offloading, such as healthcare and security systems. Here, we propose a scheduled data transfer and job execution to minimize energy consumption and offloading time. Also, the scheduled offloading is compared to unscheduled ones in a cloud-edge platform. We get a significant time efficiency of 54 percent and -0,32 percent efficiency of energy from the simulation.
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
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信