{"title":"异构移动云计算中多任务应用的动态资源编排","authors":"Q. Qi, J. Liao, Jingyu Wang, Qi Li, Yufei Cao","doi":"10.1109/INFCOMW.2016.7562076","DOIUrl":null,"url":null,"abstract":"The mobile cloud computing (MCC) that takes wireless access network as transmission medium and uses mobile devices as client becomes the newest evolution trends of cloud computing. When offloading the complicated multi-task application to the MCC environment, each task executes individually in terms of its own computation, storage and bandwidth requirement. Due to user's mobility, the provided resources contain different performance metrics that may affect the destination choice. Nevertheless, these heterogeneous MCC resources lack integrated management and can hardly cooperate with each other. Thus, how to choose the appropriate offload destination and orchestrate the resources for multi-task is a challenging problem. This paper decouples resource control of mobile cloud from user plane, where a centralized controller is responsible for resource orchestration, offload and migration. The resource orchestration is formulated as multi-objective optimal problem that contains the metrics of energy consumption, cost and availability. Finally, a particle swarm algorithm is used to obtain the approximate optimal solutions. Simulation results show that the solutions can hit Pareto optimum of resource orchestration in acceptable time.","PeriodicalId":348177,"journal":{"name":"2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"9 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Dynamic resource orchestration for multi-task application in heterogeneous mobile cloud computing\",\"authors\":\"Q. Qi, J. Liao, Jingyu Wang, Qi Li, Yufei Cao\",\"doi\":\"10.1109/INFCOMW.2016.7562076\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The mobile cloud computing (MCC) that takes wireless access network as transmission medium and uses mobile devices as client becomes the newest evolution trends of cloud computing. When offloading the complicated multi-task application to the MCC environment, each task executes individually in terms of its own computation, storage and bandwidth requirement. Due to user's mobility, the provided resources contain different performance metrics that may affect the destination choice. Nevertheless, these heterogeneous MCC resources lack integrated management and can hardly cooperate with each other. Thus, how to choose the appropriate offload destination and orchestrate the resources for multi-task is a challenging problem. This paper decouples resource control of mobile cloud from user plane, where a centralized controller is responsible for resource orchestration, offload and migration. The resource orchestration is formulated as multi-objective optimal problem that contains the metrics of energy consumption, cost and availability. Finally, a particle swarm algorithm is used to obtain the approximate optimal solutions. Simulation results show that the solutions can hit Pareto optimum of resource orchestration in acceptable time.\",\"PeriodicalId\":348177,\"journal\":{\"name\":\"2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)\",\"volume\":\"9 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INFCOMW.2016.7562076\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INFCOMW.2016.7562076","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic resource orchestration for multi-task application in heterogeneous mobile cloud computing
The mobile cloud computing (MCC) that takes wireless access network as transmission medium and uses mobile devices as client becomes the newest evolution trends of cloud computing. When offloading the complicated multi-task application to the MCC environment, each task executes individually in terms of its own computation, storage and bandwidth requirement. Due to user's mobility, the provided resources contain different performance metrics that may affect the destination choice. Nevertheless, these heterogeneous MCC resources lack integrated management and can hardly cooperate with each other. Thus, how to choose the appropriate offload destination and orchestrate the resources for multi-task is a challenging problem. This paper decouples resource control of mobile cloud from user plane, where a centralized controller is responsible for resource orchestration, offload and migration. The resource orchestration is formulated as multi-objective optimal problem that contains the metrics of energy consumption, cost and availability. Finally, a particle swarm algorithm is used to obtain the approximate optimal solutions. Simulation results show that the solutions can hit Pareto optimum of resource orchestration in acceptable time.