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 ...
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ISBN:
(纸本)9781479935741
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.
post-deployment, in situ testing and validation techniques have become an important means of ensuring the reliability of mobile and embedded systems. However, these techniques do not take into consideration the amount...
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ISBN:
(纸本)9781467362672
post-deployment, in situ testing and validation techniques have become an important means of ensuring the reliability of mobile and embedded systems. However, these techniques do not take into consideration the amount of energy they consume, which is an issue of paramount concern for systems with limited energy budgets. In this paper we propose a new test suite minimization approach that allows developers to generate energy-efficient, minimized test suites. The approach is based on encoding minimization problems as integer linear programming problems. Our empirical evaluation shows that, compared to traditionally generated minimized test suites, the test suites generated by our approach are equally effective in terms of their test coverage, but can realize energy savings of up to 90 %.
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