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An energy efficient service composition mechanism using a hybrid meta-heuristic algorithm in a mobile cloud environment

机译:一种在移动云环境中使用混合元启发式算法的节能服务组合机制

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摘要

By increasing mobile devices in technology and human life, using a runtime and mobile services has gotten more complex along with the composition of a large number of atomic services. Different services are provided by mobile cloud components to represent the non-functional properties as Quality of Service (QoS), which is applied by a set of standards. On the other hand, the growth of the energy-source heterogeneity in mobile clouds is an emerging challenge according to the energy saving problem in mobile nodes. In order to mobile cloud service composition as an NP-Hard problem, an efficient selection method should be taken by problem using optimal energy-aware methods that can extend the deployment and interoperability of mobile cloud components. Also, an energy-aware service composition mechanism is required to preserve high energy saving scenarios for mobile cloud components. In this paper, an energy-aware mechanism is applied to optimize mobile cloud service composition using a hybrid Shuffled Frog Leaping Algorithm and Genetic Algorithm (SFGA). Experimental results capture that the proposed mechanism improves the feasibility of the service composition with minimum energy consumption, response time, and cost for mobile cloud components against some current algorithms.
机译:通过增加技术和人类生活中的移动设备,使用运行时和移动服务与大量原子服务的组成相同。移动云组件提供不同的服务,以表示非功能性属性作为服务质量(QoS),由一组标准应用。另一方面,根据移动节点中的节能问题,移动云中的能量源异质性的生长是一种新兴挑战。为了使云服务组合为NP难题,应使用最佳的能量感知方法来采取有效的选择方法,可以扩展移动云组件的部署和互操作性。此外,需要一种能量感知服务组合机制来保护移动云组件的高节能方案。在本文中,应用了一种能量感知机制来利用混合混合青蛙跨越算法和遗传算法(SFGA)优化移动云服务组合物。实验结果捕获该机制提高了服务组合的可行性,以最小的能量消耗,响应时间和移动云分量对一些当前算法的能力。

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