{"title":"QoE-aware virtual machine placement for cloud games","authors":"Hua-Jun Hong, De-Yu Chen, Chun-Ying Huang, Kuan-Ta Chen, Cheng-Hsin Hsu","doi":"10.1109/NETGAMES.2013.6820610","DOIUrl":null,"url":null,"abstract":"We study an optimization problem to maximize the cloud gaming provider's total profit while achieving just-good-enough Quality-of-Experience (QoE). The optimization problem has exponential running time, and we develop an efficient heuristic algorithm. We also present an alternative formulation and algorithms for closed cloud gaming services, in which the profit is not a concern and overall gaming QoE needs to be maximized. We conduct extensive trace-driven simulations, which show that the proposed heuristic algorithms: (i) achieve close-to-optimal solutions, (ii) always achive 80+% QoE level, and (iii) outperform the state-of-the-art placement heuristic by up to 3.5 times in profits.","PeriodicalId":289229,"journal":{"name":"2013 12th Annual Workshop on Network and Systems Support for Games (NetGames)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 12th Annual Workshop on Network and Systems Support for Games (NetGames)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NETGAMES.2013.6820610","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 28
Abstract
We study an optimization problem to maximize the cloud gaming provider's total profit while achieving just-good-enough Quality-of-Experience (QoE). The optimization problem has exponential running time, and we develop an efficient heuristic algorithm. We also present an alternative formulation and algorithms for closed cloud gaming services, in which the profit is not a concern and overall gaming QoE needs to be maximized. We conduct extensive trace-driven simulations, which show that the proposed heuristic algorithms: (i) achieve close-to-optimal solutions, (ii) always achive 80+% QoE level, and (iii) outperform the state-of-the-art placement heuristic by up to 3.5 times in profits.