{"title":"Using quality of computation to enhance quality of service in mobile computing systems","authors":"Dominik Schäfer, Janick Edinger, Tobias Borlinghaus, Justin Mazzola Paluska, C. Becker","doi":"10.1109/IWQoS.2017.7969146","DOIUrl":null,"url":null,"abstract":"Mobile devices are ubiquitous but their resources are limited. However, they must be capable to run computationally intensive software, for example for image stitching, face recognition, and simulation-based artificial intelligence. As a solution, mobile devices can use nearby resources to offload computation. Distributed computing environments provide such features but ignore the nature of mobile devices, such as mobility, network, or battery changes. This leads to long delays, which reduce the quality of experience for the user. In this paper, we present Mobile Tasklets, a mobile extension of our distributed computing middleware. The design of Mobile Tasklets includes context monitoring, context-aware scheduling mechanisms, and an Android API for application integration. We identify the challenges of the integration of mobile devices into our distributed computing environment. We evaluate Mobile Tasklets in a real-world testbed with different context settings.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"263 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWQoS.2017.7969146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Mobile devices are ubiquitous but their resources are limited. However, they must be capable to run computationally intensive software, for example for image stitching, face recognition, and simulation-based artificial intelligence. As a solution, mobile devices can use nearby resources to offload computation. Distributed computing environments provide such features but ignore the nature of mobile devices, such as mobility, network, or battery changes. This leads to long delays, which reduce the quality of experience for the user. In this paper, we present Mobile Tasklets, a mobile extension of our distributed computing middleware. The design of Mobile Tasklets includes context monitoring, context-aware scheduling mechanisms, and an Android API for application integration. We identify the challenges of the integration of mobile devices into our distributed computing environment. We evaluate Mobile Tasklets in a real-world testbed with different context settings.