{"title":"Jade:面向 ad-hoc 网络移动设备的异构网络接口结合型高效能源感知计算卸载系统","authors":"Hao Qian, Daniel Andresen","doi":"10.1109/SNPD.2014.6888703","DOIUrl":null,"url":null,"abstract":"Mobile device users consistently desire faster results and longer battery life, which is frequently accomplished by of-floading computation to cloud-based servers. However, in common cases (Internet connectivity slow/unavailable, priva-cy/security issues), users have multiple devices with heterogeneous battery and computational capabilities independent of the cloud. Android provides mechanisms for creating mobile code, but lacks a native scheduling mechanism for determining where code should be executed. In this paper we present the results of an investigation into adding sophisticated scheduling capabilities to Android apps, which provides scheduling balancing energy and performance across networked mobile devices. Jade monitors and adapts to workload variation, communication costs, and energy status in a distributed ad-hoc network of Android mobile devices for supporting distributed computation. We show how the two goals can be integrated, and present several algorithms indicating a major advantage (over 75% improvement in energy use) can be achieved through the use of dynamic scheduling information for remote computational devices. We provide a detailed discussion of our system architecture and implementation, and briefly summarize the experimental results which have been achieved.","PeriodicalId":272932,"journal":{"name":"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":"{\"title\":\"Jade: An efficient energy-aware computation offloading system with heterogeneous network interface bonding for ad-hoc networked mobile devices\",\"authors\":\"Hao Qian, Daniel Andresen\",\"doi\":\"10.1109/SNPD.2014.6888703\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile device users consistently desire faster results and longer battery life, which is frequently accomplished by of-floading computation to cloud-based servers. However, in common cases (Internet connectivity slow/unavailable, priva-cy/security issues), users have multiple devices with heterogeneous battery and computational capabilities independent of the cloud. Android provides mechanisms for creating mobile code, but lacks a native scheduling mechanism for determining where code should be executed. In this paper we present the results of an investigation into adding sophisticated scheduling capabilities to Android apps, which provides scheduling balancing energy and performance across networked mobile devices. Jade monitors and adapts to workload variation, communication costs, and energy status in a distributed ad-hoc network of Android mobile devices for supporting distributed computation. We show how the two goals can be integrated, and present several algorithms indicating a major advantage (over 75% improvement in energy use) can be achieved through the use of dynamic scheduling information for remote computational devices. We provide a detailed discussion of our system architecture and implementation, and briefly summarize the experimental results which have been achieved.\",\"PeriodicalId\":272932,\"journal\":{\"name\":\"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"32\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SNPD.2014.6888703\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD.2014.6888703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Jade: An efficient energy-aware computation offloading system with heterogeneous network interface bonding for ad-hoc networked mobile devices
Mobile device users consistently desire faster results and longer battery life, which is frequently accomplished by of-floading computation to cloud-based servers. However, in common cases (Internet connectivity slow/unavailable, priva-cy/security issues), users have multiple devices with heterogeneous battery and computational capabilities independent of the cloud. Android provides mechanisms for creating mobile code, but lacks a native scheduling mechanism for determining where code should be executed. In this paper we present the results of an investigation into adding sophisticated scheduling capabilities to Android apps, which provides scheduling balancing energy and performance across networked mobile devices. Jade monitors and adapts to workload variation, communication costs, and energy status in a distributed ad-hoc network of Android mobile devices for supporting distributed computation. We show how the two goals can be integrated, and present several algorithms indicating a major advantage (over 75% improvement in energy use) can be achieved through the use of dynamic scheduling information for remote computational devices. We provide a detailed discussion of our system architecture and implementation, and briefly summarize the experimental results which have been achieved.