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Minimizing Context Migration in Mobile Code Offload
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DOI：10.1109/TMC.2016.2586056.png)
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Abstract
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Mobile Cloud Computing (MCC) is of particular importance to address the conflict 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. To further improve the efficiency of such offline parsing of application binaries, our scheme also conducts one-time parsing to all the mobile OS libraries and reuses these parsing results for different user applications. We have implemented our design over the Dalvik Virtual Machine of Android OS. Our experiments and evaluation against applications downloaded from Google Play show that our approach can save data transmission significantly comparing to existing schemes.
Keywords:
Mobile cloud computing
code offload
context migration
distributed shared memory
virtual machine
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