{"title":"Deadline-Aware Peer-to-Peer Task Offloading in Stochastic Mobile Cloud Computing Systems","authors":"Chongyu Zhou, C. Tham","doi":"10.1109/SAHCN.2018.8397142","DOIUrl":null,"url":null,"abstract":"By taking advantage of pervasive mobile devices and their pairwise encounters, Mobile Cloud Computing (MCC) offers an efficient solution for mobile devices to execute complex applications in a collaborative manner. In this paper, we consider the problem of distributed task offloading in MCC systems with deadline constraints. We propose an online distributed task offloading (DTO) algorithm for practical MCC systems where each mobile user can dynamically make offloading decisions to nearby mobile devices in order to process computation tasks in a collaborative manner. The DTO scheme is lightweight and fully distributed. Through rigorous theoretical analysis, we prove that the proposed DTO algorithm can meet the deadline constraints of the computation tasks and achieve a near-optimal system-wide utility. Furthermore, through real testbed experiments and trace-driven simulations, we compare the DTO scheme with several baseline methods and demonstrate its effectiveness.","PeriodicalId":139623,"journal":{"name":"2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAHCN.2018.8397142","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
By taking advantage of pervasive mobile devices and their pairwise encounters, Mobile Cloud Computing (MCC) offers an efficient solution for mobile devices to execute complex applications in a collaborative manner. In this paper, we consider the problem of distributed task offloading in MCC systems with deadline constraints. We propose an online distributed task offloading (DTO) algorithm for practical MCC systems where each mobile user can dynamically make offloading decisions to nearby mobile devices in order to process computation tasks in a collaborative manner. The DTO scheme is lightweight and fully distributed. Through rigorous theoretical analysis, we prove that the proposed DTO algorithm can meet the deadline constraints of the computation tasks and achieve a near-optimal system-wide utility. Furthermore, through real testbed experiments and trace-driven simulations, we compare the DTO scheme with several baseline methods and demonstrate its effectiveness.