DocumentCode :
1807332
Title :
Code offload with least context migration in the mobile cloud
Author :
Yong Li ; Wei Gao
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Tennessee at Knoxville, Knoxville, TN, USA
fYear :
2015
fDate :
April 26 2015-May 1 2015
Firstpage :
1876
Lastpage :
1884
Abstract :
Mobile Cloud Computing (MCC) is of particular importance to address the contradiction between the increasing complexity of user applications and the limited lifespan of mobile device´s battery, by offloading the computational workloads from local devices to the remote cloud. Current offloading schemes either require the programmer´s annotations, which restricts its wide application; or transmits too much unnecessary data, resulting bandwidth and energy waste. In this paper, we propose a novel method-level offloading methodology to offload local computational workload with as least data transmission as possible. Our basic idea is to identify the contexts which are necessary to the method execution by parsing application binaries in advance and applying this parsing result to selectively migrate heap data while allowing successful method execution remotely. Our implementation of this design is built upon Dalvik Virtual Machine. Our experiments and evaluation against applications downloaded from Google Play show that our approach can save data transmission significantly comparing to existing schemes.
Keywords :
cloud computing; mobile computing; program compilers; virtual machines; Dalvik virtual machine; Google Play; MCC; code offloading; data transmission; least context migration; local computational workload offloading; mobile cloud computing; parsing application binaries; Androids; Context; Humanoid robots; Instruction sets; Java; Registers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Communications (INFOCOM), 2015 IEEE Conference on
Conference_Location :
Kowloon
Type :
conf
DOI :
10.1109/INFOCOM.2015.7218570
Filename :
7218570
Link To Document :
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