{"title":"基于qos约束的联邦云资源分配博弈","authors":"Xin Xu, Huiqun Yu, Xinyu Cong","doi":"10.1109/IMIS.2013.53","DOIUrl":null,"url":null,"abstract":"Federated cloud emerges recently to overcome resource limitation of IaaS providers by federating different cloud resources which belong to separate organizations. The main objective of IaaS providers is to obtain maximal profits and guarantee QoS requirements of customers at the same time. In this paper, we propose a cooperative game algorithm that helps the resource allocation decision-making process with a flexible resource amount of the total federation. This algorithm also takes the QoS constraints into account and provides two different approaches for cost-sensitive or time-sensitive customers. Simulation results show that the proposed algorithm improves various QoS requirements and increases the satisfaction level of customer's requests.","PeriodicalId":425979,"journal":{"name":"2013 Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing","volume":"602 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"A QoS-Constrained Resource Allocation Game in Federated Cloud\",\"authors\":\"Xin Xu, Huiqun Yu, Xinyu Cong\",\"doi\":\"10.1109/IMIS.2013.53\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Federated cloud emerges recently to overcome resource limitation of IaaS providers by federating different cloud resources which belong to separate organizations. The main objective of IaaS providers is to obtain maximal profits and guarantee QoS requirements of customers at the same time. In this paper, we propose a cooperative game algorithm that helps the resource allocation decision-making process with a flexible resource amount of the total federation. This algorithm also takes the QoS constraints into account and provides two different approaches for cost-sensitive or time-sensitive customers. Simulation results show that the proposed algorithm improves various QoS requirements and increases the satisfaction level of customer's requests.\",\"PeriodicalId\":425979,\"journal\":{\"name\":\"2013 Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing\",\"volume\":\"602 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMIS.2013.53\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMIS.2013.53","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A QoS-Constrained Resource Allocation Game in Federated Cloud
Federated cloud emerges recently to overcome resource limitation of IaaS providers by federating different cloud resources which belong to separate organizations. The main objective of IaaS providers is to obtain maximal profits and guarantee QoS requirements of customers at the same time. In this paper, we propose a cooperative game algorithm that helps the resource allocation decision-making process with a flexible resource amount of the total federation. This algorithm also takes the QoS constraints into account and provides two different approaches for cost-sensitive or time-sensitive customers. Simulation results show that the proposed algorithm improves various QoS requirements and increases the satisfaction level of customer's requests.