{"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}
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.