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	Refactoring android java code for on-demand computation offloading
	Zhang, Ying ; Huang, Gang ; Liu, Xuanzhe ; Zhang, Wei ; Mei, Hong ; Yang, Shunxiang
	2012
英文摘要	Computation offloading is a promising way to improve the performance as well as reducing the battery power consumption of a smartphone application by executing some parts of the application on a remote server. Supporting such capability is not easy for smartphone application developers due to (1) correctness: some code, e.g., that for GPS, gravity, and other sensors, can run only on the smartphone so that developers have to identify which parts of the application cannot be offloaded; (2) effectiveness: the reduced execution time must be greater than the network delay caused by computation offloading so that developers need to calculate which parts are worth offloading; (3) adaptability: smartphone applications often face changes of user requirements and runtime environments so that developers need to implement the adaptation on offloading. More importantly, considering the large number of today's smartphone applications, solutions applicable for legacy applications will be much more valuable. In this paper, we present a tool, named DPartner, that automatically refactors Android applications to be the ones with computation offloading capability. For a given Android application, DPartner first analyzes its bytecode for discovering the parts worth offloading, then rewrites the bytecode to implement a special program structure supporting ondemand offloading, and finally generates two artifacts to be deployed onto an Android phone and the server, respectively. We evaluated DPartner on three real-world Android applications, demonstrating the reduction of execution time by 46%-97% and battery power consumption by 27%-83%. Copyright ? 2012 ACM.; EI; 10; 233-247; 47
语种	英语
DOI标识	10.1145/2398857.2384634
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/461439]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhang, Ying,Huang, Gang,Liu, Xuanzhe,et al. Refactoring android java code for on-demand computation offloading. 2012-01-01.

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