{"title":"云环境下大数据应用的容量分配","authors":"M. Ciavotta, E. Gianniti, D. Ardagna","doi":"10.1145/3053600.3053630","DOIUrl":null,"url":null,"abstract":"The aim of this work is to present the problem of Capacity Allocation for multiple classes of Big Data applications running in the Cloud. The objective is the minimization of the renting out costs subject to the fulfillment of QoS requirements expressed in terms of application deadlines. We propose a preliminary version of a tool embedding a local-search-based algorithm exploiting also an integer nonlinear mathematical formulation and a queueing network simulation to solve the problem.","PeriodicalId":115833,"journal":{"name":"Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Capacity Allocation for Big Data Applications in the Cloud\",\"authors\":\"M. Ciavotta, E. Gianniti, D. Ardagna\",\"doi\":\"10.1145/3053600.3053630\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this work is to present the problem of Capacity Allocation for multiple classes of Big Data applications running in the Cloud. The objective is the minimization of the renting out costs subject to the fulfillment of QoS requirements expressed in terms of application deadlines. We propose a preliminary version of a tool embedding a local-search-based algorithm exploiting also an integer nonlinear mathematical formulation and a queueing network simulation to solve the problem.\",\"PeriodicalId\":115833,\"journal\":{\"name\":\"Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3053600.3053630\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3053600.3053630","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Capacity Allocation for Big Data Applications in the Cloud
The aim of this work is to present the problem of Capacity Allocation for multiple classes of Big Data applications running in the Cloud. The objective is the minimization of the renting out costs subject to the fulfillment of QoS requirements expressed in terms of application deadlines. We propose a preliminary version of a tool embedding a local-search-based algorithm exploiting also an integer nonlinear mathematical formulation and a queueing network simulation to solve the problem.