{"title":"femtocloud的在线用户驱动任务调度","authors":"C. Anglano, M. Canonico, Marco Guazzone","doi":"10.1109/FMEC.2019.8795304","DOIUrl":null,"url":null,"abstract":"In Fog Computing, FemtoClouds are emerging computing systems consisting of a set of heterogeneous mobile devices whose users allow to run tasks offloaded by other users. FemtoClouds are well suited to run Bag-of-Tasks (BoTs) applications, but they need effective scheduling algorithms that are able to deal with collections of independently-owned, heterogeneous devices that can suddenly leave the system. In this paper, we present UDFS, an online scheduling algorithm that, by combining knowledge-free task and device selection policies with suitable heterogeneity and volatility tolerance mechanisms, can effectively schedule a stream of BoT applications on FemtoClouds. We evaluate the ability of UDFS to achieve its design goals and to perform better than existing scheduling alternatives, by carrying out a thorough simulation study for a large set of realistic scenarios. Our results indeed show that UDFS can effectively schedule a stream of BoT applications on FemtoClouds, and it can do so more effectively than existing scheduling alternatives.","PeriodicalId":101825,"journal":{"name":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Online User-driven Task Scheduling for FemtoClouds\",\"authors\":\"C. Anglano, M. Canonico, Marco Guazzone\",\"doi\":\"10.1109/FMEC.2019.8795304\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In Fog Computing, FemtoClouds are emerging computing systems consisting of a set of heterogeneous mobile devices whose users allow to run tasks offloaded by other users. FemtoClouds are well suited to run Bag-of-Tasks (BoTs) applications, but they need effective scheduling algorithms that are able to deal with collections of independently-owned, heterogeneous devices that can suddenly leave the system. In this paper, we present UDFS, an online scheduling algorithm that, by combining knowledge-free task and device selection policies with suitable heterogeneity and volatility tolerance mechanisms, can effectively schedule a stream of BoT applications on FemtoClouds. We evaluate the ability of UDFS to achieve its design goals and to perform better than existing scheduling alternatives, by carrying out a thorough simulation study for a large set of realistic scenarios. Our results indeed show that UDFS can effectively schedule a stream of BoT applications on FemtoClouds, and it can do so more effectively than existing scheduling alternatives.\",\"PeriodicalId\":101825,\"journal\":{\"name\":\"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FMEC.2019.8795304\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FMEC.2019.8795304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Online User-driven Task Scheduling for FemtoClouds
In Fog Computing, FemtoClouds are emerging computing systems consisting of a set of heterogeneous mobile devices whose users allow to run tasks offloaded by other users. FemtoClouds are well suited to run Bag-of-Tasks (BoTs) applications, but they need effective scheduling algorithms that are able to deal with collections of independently-owned, heterogeneous devices that can suddenly leave the system. In this paper, we present UDFS, an online scheduling algorithm that, by combining knowledge-free task and device selection policies with suitable heterogeneity and volatility tolerance mechanisms, can effectively schedule a stream of BoT applications on FemtoClouds. We evaluate the ability of UDFS to achieve its design goals and to perform better than existing scheduling alternatives, by carrying out a thorough simulation study for a large set of realistic scenarios. Our results indeed show that UDFS can effectively schedule a stream of BoT applications on FemtoClouds, and it can do so more effectively than existing scheduling alternatives.