[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-detail-219432-en":53,"doc-seo-219432-105":76},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":5,"data":54},{"doc_id":55,"user_id":56,"nickname":57,"user_avatar":58,"doc_module":9,"category_id":50,"category_name":51,"doc_title":59,"doc_description":60,"doc_content":61,"file_id":62,"file_url":63,"file_type":64,"file_size":65,"view_count":66,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":67,"language":68,"language_code":69,"site_id":70,"html_lang":69,"table_of_contents":71,"faqs":72,"seo_title":73,"seo_description":60,"update_tm":74,"read_time":75},219432,962088006270,"eBook King","https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","Leveraging Service Clouds for Power and QoS Management for Mobile Devices","QoS and power management for mobile devices is addressed through a service-cloud-based framework that jointly optimizes energy savings and quality-of-service constraints. The approach uses a function-pool prediction model to forecast power and QoS behavior of tasks activated on mobile devices, then formulates a cost function and decision algorithm for selecting the best execution platforms. Service and data migration policies and service migration infrastructure reduce communication latency. A facial recognition case study validates results, reaching 66.7% energy savings and a 54.3% response-time reduction.","Leveraging Service Clouds for Power and QoS Management for Mobile Devices\nYunqi Ye, Liangliang Xiao, I-Ling Yen, Farokh Bastani\nDepartment of Computer Science\nUniversity of Texas at Dallas\n{yxy078000, xll052000, ilyen, bastani}@utdallas.edu\nAbstract. We propose a QoS and power management (QPM) framework for mobile devices making use of the service cloud. Several techniques for the realization of the QPM framework have been developed. First, we develop a function pool based prediction model to predict the power and QoS behaviors of the task activated by a mobile device. Based on the prediction, we design the cost function and the decision algorithm for selecting the best platforms for executing the services/applications in order to achieve optimal energy saving while satisfying QoS requirements. Several service and data migration policies have been designed for a service to be migrated and executed on a mobile device to achieve power and QoS gains. We apply the QPM framework and associated techniques to a facial recognition case study system to validate our approach. Experimental results show that, in the best case, the QPM framework can achieve 66.7% energy saving for the mobile device and at the same time, reduce the response time by 54.3%.\nKeywords: mobile device, service cloud, power management, quality of service (QoS), data migration, service migration.\nIntroduction\nMobile devices are becoming the primary platforms for many users to roam around and to access the service cloud. With the advances in mobile devices and the supporting environment, the user tasks issued on mobile devices are increasing in complexity and sophistication. However, limited battery life of the mobile device is a major concern, especially when recharging is not available. According to a survey from ChangeWave \u0013 REF _Ref283917888 \\n \\h \u0014[1]\u0015 on Apple’s iPhone 3GS in 2009, short battery life is considered as the most disliked feature by 41% of the respondents. A Nokia poll in 2009 \u0013 REF _Ref283917917 \\n \\h \u0014[2]\u0015 also shows that the battery life is the most important feature for a music phone, instead of sound quality. In critical applications, loss of power can adversely impact mission success and cause severe consequences.\nThere have been a lot of works addressing the power management issues. For example, the dynamic power management (DPM) approaches \u0013 REF _Ref283917930 \\n \\h \u0014[3]\u0015 try to turn off the devices when they are idle. In the dynamic voltage and frequency scaling (DVFS) approaches [4, 5, 6], the processor can work under various performance-states (p-state) that provide tradeoffs between execution performance and energy consumption. These works focus on power management on local devices and can save 9-50% energy at the cost of reduced performance.\nCloud computing is a promising paradigm, enabling accesses to a pool of configurable computing resources such as networks, servers, storage, applications and services. Service oriented computing (SOC) has brought added values to this paradigm. SOC can deliver an integrated suite of functionalities to end users through discovery and composition of loosely and tightly coupled services. All the computing resources, smart devices, applications, data and information sources in the cloud can be wrapped as services, creating a service cloud that can provide much richer capabilities than a single device. With the service cloud, the mobile users can offload tasks to the cloud for execution so that the local computation can be totally eliminated, which has the potential of achieving very significant energy saving. In fact, for some computation-intensive services, it is possible to save energy as well as reduce processing latency if they are executed in the cloud. However, task offloading involves communication costs for request uploading and response downloading. For some communication-intensive services, the power consumed for communication may exceed potential savings if executed in the service cloud. Thus","cbCaiuyf9ducooxn","https://ap.wps.com/l/cbCaiuyf9ducooxn","docx",105860,6,9,"English","en",105,"# Introduction\n## Problem motivation: battery limits and QoS impact\n## Related work: local power management and DVFS\n## Service clouds and task offloading tradeoffs\n## Proposed QPM framework overview\n## Key components: prediction, platform selection, migration","[{\"question\":\"What is the main goal of the proposed QPM framework?\",\"answer\":\"To manage mobile-device power while satisfying QoS requirements by selecting execution platforms and applying migration policies in a service-cloud setting.\"},{\"question\":\"How does the framework predict power and QoS?\",\"answer\":\"It uses a function pool based prediction model to forecast the power and QoS behaviors of tasks activated on the mobile device under different configurations and environments.\"},{\"question\":\"How are services and data handled when the execution platform lacks availability?\",\"answer\":\"Service and associated data are migrated using the service and data allocation module so that the service/application can run on the chosen platform.\"}]","Leveraging Service Clouds for Power and QoS Management for Mobile Devices | DOCX",1788867283,3,{"code":4,"msg":77,"data":78},"ok",{"site_id":70,"language":69,"slug":79,"title":59,"keywords":80,"description":60,"schema_data":81,"social_meta":136,"head_meta":138,"extra_data":140,"updated_unix":74},"leveraging-service-clouds-for-power-and-qos-management-for-mobile-devices","",{"@graph":82,"@context":135},[83,98,118],{"@type":84,"itemListElement":85},"BreadcrumbList",[86,90,93,95],{"item":87,"name":88,"@type":89,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":91,"name":10,"@type":89,"position":92},"https://docshare.wps.com/template/",2,{"item":94,"name":51,"@type":89,"position":75},"https://docshare.wps.com/template/general/",{"item":96,"name":59,"@type":89,"position":97},"https://docshare.wps.com/template/leveraging-service-clouds-for-power-and-qos-management-for-mobile-devices/219432/",4,{"url":96,"name":59,"@type":99,"image":100,"author":105,"headline":59,"publisher":107,"fileFormat":110,"inLanguage":69,"description":60,"dateModified":111,"datePublished":112,"encodingFormat":110,"isAccessibleForFree":113,"interactionStatistic":114},"DigitalDocument",{"url":101,"@type":102,"width":103,"height":104},"https://docshare.wps.com/thumbnails/leveraging-service-clouds-for-power-and-qos-management-for-mobile-devices/219432.png","ImageObject",442,249,{"name":57,"@type":106},"Person",{"url":87,"name":108,"@type":109},"DocShare","Organization","application/vnd.openxmlformats-officedocument.wordprocessingml.document","2026-09-27","2026-09-08",true,{"@type":115,"interactionType":116,"userInteractionCount":66},"InteractionCounter",{"@type":117},"ViewAction",{"@type":119,"mainEntity":120},"FAQPage",[121,127,131],{"name":122,"@type":123,"acceptedAnswer":124},"What is the main goal of the proposed QPM framework?","Question",{"text":125,"@type":126},"To manage mobile-device power while satisfying QoS requirements by selecting execution platforms and applying migration policies in a service-cloud setting.","Answer",{"name":128,"@type":123,"acceptedAnswer":129},"How does the framework predict power and QoS?",{"text":130,"@type":126},"It uses a function pool based prediction model to forecast the power and QoS behaviors of tasks activated on the mobile device under different configurations and environments.",{"name":132,"@type":123,"acceptedAnswer":133},"How are services and data handled when the execution platform lacks availability?",{"text":134,"@type":126},"Service and associated data are migrated using the service and data allocation module so that the service/application can run on the chosen platform.","https://schema.org",{"og:url":96,"og:type":137,"og:title":59,"og:site_name":108,"og:description":60},"article",{"robots":139,"canonical":96},"index,follow",{"doc_id":55,"site_id":70}]