{"title":"MoSeC:移动云服务组合","authors":"Huijun Wu, Dijiang Huang","doi":"10.1109/MobileCloud.2015.29","DOIUrl":null,"url":null,"abstract":"Mobile Cloud computing has shown its capability to support mobile devices for provisioning computing, storage and communication resources. Many existing research has proposed to offload computation tasks from mobile devices to clouds in order to reduce energy consumption, where the offloading service model is usually one-to-one. Due to the development of mobile sensing and location-based mobile cloud services, the cloud edge has been extended to the mobile devices and sensors. As a result, the one-to-one model is not sufficient to model the dynamic changes of mobile cloud-based services. Thus, a many-to-many (or multi-site) mobile cloud service composition is highly desired. In this research, MoSeC is presented to model the many-to-many mobile cloud service composition, where there are multiple surrogates, such as cloud computing nodes, mobile devices, or sensors, and their services (i.e., computation, storage, sensing, etc.) can be composed to fulfill functions required by a mobile service requestor. MoSeC takes into considerations the surrogates' changes due to their mobility and resource constraints. Moreover, MoSeC takes into considerations several service metrics for service mapping (or allocation) through a mobile cloud service topology reconfiguration process. A set of algorithms are presented to address the Service Topology Reconfiguration Problem (STRP) in several mobile cloud representative application scenarios, i.e., they are modeled as finite horizon scenarios, infinite horizon scenarios, and large state space scenarios to represent ad hoc, long-term, and large-scale mobile cloud service composition scenarios, respectively.","PeriodicalId":373443,"journal":{"name":"2015 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering","volume":"18 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"MoSeC: Mobile-Cloud Service Composition\",\"authors\":\"Huijun Wu, Dijiang Huang\",\"doi\":\"10.1109/MobileCloud.2015.29\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile Cloud computing has shown its capability to support mobile devices for provisioning computing, storage and communication resources. Many existing research has proposed to offload computation tasks from mobile devices to clouds in order to reduce energy consumption, where the offloading service model is usually one-to-one. Due to the development of mobile sensing and location-based mobile cloud services, the cloud edge has been extended to the mobile devices and sensors. As a result, the one-to-one model is not sufficient to model the dynamic changes of mobile cloud-based services. Thus, a many-to-many (or multi-site) mobile cloud service composition is highly desired. In this research, MoSeC is presented to model the many-to-many mobile cloud service composition, where there are multiple surrogates, such as cloud computing nodes, mobile devices, or sensors, and their services (i.e., computation, storage, sensing, etc.) can be composed to fulfill functions required by a mobile service requestor. MoSeC takes into considerations the surrogates' changes due to their mobility and resource constraints. Moreover, MoSeC takes into considerations several service metrics for service mapping (or allocation) through a mobile cloud service topology reconfiguration process. A set of algorithms are presented to address the Service Topology Reconfiguration Problem (STRP) in several mobile cloud representative application scenarios, i.e., they are modeled as finite horizon scenarios, infinite horizon scenarios, and large state space scenarios to represent ad hoc, long-term, and large-scale mobile cloud service composition scenarios, respectively.\",\"PeriodicalId\":373443,\"journal\":{\"name\":\"2015 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering\",\"volume\":\"18 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MobileCloud.2015.29\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MobileCloud.2015.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mobile Cloud computing has shown its capability to support mobile devices for provisioning computing, storage and communication resources. Many existing research has proposed to offload computation tasks from mobile devices to clouds in order to reduce energy consumption, where the offloading service model is usually one-to-one. Due to the development of mobile sensing and location-based mobile cloud services, the cloud edge has been extended to the mobile devices and sensors. As a result, the one-to-one model is not sufficient to model the dynamic changes of mobile cloud-based services. Thus, a many-to-many (or multi-site) mobile cloud service composition is highly desired. In this research, MoSeC is presented to model the many-to-many mobile cloud service composition, where there are multiple surrogates, such as cloud computing nodes, mobile devices, or sensors, and their services (i.e., computation, storage, sensing, etc.) can be composed to fulfill functions required by a mobile service requestor. MoSeC takes into considerations the surrogates' changes due to their mobility and resource constraints. Moreover, MoSeC takes into considerations several service metrics for service mapping (or allocation) through a mobile cloud service topology reconfiguration process. A set of algorithms are presented to address the Service Topology Reconfiguration Problem (STRP) in several mobile cloud representative application scenarios, i.e., they are modeled as finite horizon scenarios, infinite horizon scenarios, and large state space scenarios to represent ad hoc, long-term, and large-scale mobile cloud service composition scenarios, respectively.