Proceedings of the IEEE 38th Annual Computer Software and Applications
(COMPSAC '14), IEEE Computer Society, 2014
Edward Y.Y. Kan 2 , W.K. Chan 3 , and T.H. Tse 4
[paper from IEEE Xplore | paper from IEEE digital library | technical report TR-2014-06]
Applications written by end-user programmers are hardly energy-optimized
by these programmers.
The end users of such applications thus suffer significant energy issues.
In this paper, we propose CrowdAdaptor,
a novel approach toward locating energy-efficient configurations to
execute the applications hosted in virtual machines on handheld devices.
CrowdAdaptor innovatively makes use of the development artifacts
(test cases) and the very large installation base of the same
application to distribute the test executions and performance data
collection of the whole test suites against many different virtual
machine configurations among these installation bases.
It synthesizes these data,
continuously discovers better energy-efficient configurations,
and makes them available to all the installations of the same applications.
We report a multi-subject case study on the ability of the framework
to discover energy-efficient configurations in three power models.
The results show that CrowdAdaptor can achieve up to 50% of energy
savings based on a conservative linear power model.
Keywords: Mobile energy consumption; Test harness; Post-deployment validation; Energy optimization; Energy saving
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