H. Badri, Tayebeh Bahreini, Daniel Grosu, Kai Yang
{"title":"Multi-stage stochastic programming for service placement in edge computing systems: poster","authors":"H. Badri, Tayebeh Bahreini, Daniel Grosu, Kai Yang","doi":"10.1145/3132211.3132461","DOIUrl":null,"url":null,"abstract":"Efficient service placement of mobile applications on the edge servers is one of the main challenges in Mobile Edge Computing (MEC). The service placement problem in MEC has to consider several issues that were not present in the data-center settings. After the initial service placement, mobile users may move to different locations which may increase the execution time or the cost of running the applications. In addition to this, the resource availability of servers may change over time. Therefore, an efficient service placement algorithm must be adaptive to this dynamic setting.","PeriodicalId":389022,"journal":{"name":"Proceedings of the Second ACM/IEEE Symposium on Edge Computing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Second ACM/IEEE Symposium on Edge Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3132211.3132461","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Efficient service placement of mobile applications on the edge servers is one of the main challenges in Mobile Edge Computing (MEC). The service placement problem in MEC has to consider several issues that were not present in the data-center settings. After the initial service placement, mobile users may move to different locations which may increase the execution time or the cost of running the applications. In addition to this, the resource availability of servers may change over time. Therefore, an efficient service placement algorithm must be adaptive to this dynamic setting.
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