Sensing flow execution engine for concurrent mobile sensing applications동시에 동작하는 모바일 센싱 애플리케이션을 위한 센싱 플로우 실행 엔진

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dc.contributor.advisorSong, June-Hwa-
dc.contributor.advisor송준화-
dc.contributor.authorJu, Young-Hyun-
dc.contributor.author주영현-
dc.date.accessioned2015-04-23T08:30:34Z-
dc.date.available2015-04-23T08:30:34Z-
dc.date.issued2014-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=568604&flag=dissertation-
dc.identifier.urihttp://hdl.handle.net/10203/197816-
dc.description학위논문(박사) - 한국과학기술원 : 전산학과, 2014.2, [ viii, 65 p. ]-
dc.description.abstractEmerging mobile sensing applications are changing the characteristics of smartphone workloads. Based on the embedded sensing capabilities of smartphones, mobile applications can identify users’ contexts such as location and activity anytime and anywhere, and provide autonomous, situation-aware services. Whereas typical mobile applications run alone in the foreground interacting with users, sensing applications concurrently run in the background, providing unobtrusive monitoring services. This new class of applications and their workloads bring new challenges on resource-limited smartphones. First, mobile sensing applications consume considerable amount of resources on smartphones for continuous sensing and processing. Such continuous, high resource consumption limits the number of services a user can run. Also, it can significantly reduce the smartphone’s battery lifetime. Second, greedy and contentious resource use by concurrent sensing applications could degrade the performance of other daily use of smartphones. Also, some sensing applications could starve due to the resource contention, resulting in serious degradation of their service qualities. Lastly, from the viewpoint of developers, it is very challenging to build sophisticated sensing logics from scratch without any programming support. It involves multi-lateral challenges including careful selection of machine learning algorithms, repetitive parameter tuning, and low-level resource optimization. To address these challenges, I have designed and developed SymPhoney, a sensing flow execution engine for emerging sensing applications. The engine provides an intuitive and flexible programming model that significantly lightens the burden of developers. More importantly, it effectively coordinates the execution of concurrent sensing flows, minimizing the degradation of their service qualities even under contention. Also, the engine executes the sensing flows in a highly efficient way. As its key approach, ...eng
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectmobile sensing-
dc.subject프로그래밍 모델-
dc.subject자원 효율성-
dc.subject자원 조율-
dc.subject모바일 엔진-
dc.subject모바일 센싱-
dc.subjectmobile engine-
dc.subjectresource coordination-
dc.subjectresource efficiency-
dc.subjectprogramming model-
dc.titleSensing flow execution engine for concurrent mobile sensing applications-
dc.title.alternative동시에 동작하는 모바일 센싱 애플리케이션을 위한 센싱 플로우 실행 엔진-
dc.typeThesis(Ph.D)-
dc.identifier.CNRN568604/325007 -
dc.description.department한국과학기술원 : 전산학과, -
dc.identifier.uid020057588-
dc.contributor.localauthorSong, June-Hwa-
dc.contributor.localauthor송준화-
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