{"title":"MDP modeling of resource provisioning in virtualized content-delivery networks","authors":"A. Haghighi, S. Shah-Heydari, S. Shahbazpanahi","doi":"10.1109/ICNP.2017.8117600","DOIUrl":null,"url":null,"abstract":"In this paper a Markov decision process (MDP) model for virtualized content delivery networks is proposed. We use stochastic optimization to assign cloud site resources to each user group. We propose how quality of experience (QoE) can be included in the modeling and optimization. We then present an optimal solution for a constraint-free version of the problem, and show the improvement in accumulated revenue when our optimization model is used. A sub-optimal algorithm is proposed that would reduce the complexity of the problem. Simulation results are presented to support merits of the proposed algorithm.","PeriodicalId":6462,"journal":{"name":"2017 IEEE 25th International Conference on Network Protocols (ICNP)","volume":"181 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 25th International Conference on Network Protocols (ICNP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNP.2017.8117600","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper a Markov decision process (MDP) model for virtualized content delivery networks is proposed. We use stochastic optimization to assign cloud site resources to each user group. We propose how quality of experience (QoE) can be included in the modeling and optimization. We then present an optimal solution for a constraint-free version of the problem, and show the improvement in accumulated revenue when our optimization model is used. A sub-optimal algorithm is proposed that would reduce the complexity of the problem. Simulation results are presented to support merits of the proposed algorithm.