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GA-Based Resource Augmentation Negotation for Energy-Optimised Mobile Ad-hoc Cloud

机译:基于GA的能源优化移动自组织云的资源增强协商

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Mobile and cloud computing are two areas which are rapidly expanding in terms of use case and functionality. An ad-hoc mobile cloud can be constructed upon local devices, where devices work together and share resources, aspects such as energy and costs may be minimised. This paper builds on previous work which proposed an end-to-end system whereby user applications may be profiled for their resource consumption locally and then if augmentation is required, they may negotiate with a local mobile ad-hoc cloud for optimum energy and resource utilisation. The contribution of this paper focuses upon a novel and adapted Genetic Algorithm approach to resource negotiation in order to further enable energy-optimised resource augmentation for Mobile Ad-hoc clouds.
机译:移动和云计算是两个在用例和功能方面迅速扩展的领域。可以在本地设备上构建临时移动云,其中设备可以协同工作并共享资源,可以最大程度地减少能源和成本等方面。本文以先前的工作为基础,该工作提出了一个端到端系统,通过该系统,可以针对用户应用程序本地分析其资源消耗情况,然后如果需要扩充,则可以与本地移动自组织云进行协商以实现最佳的能源和资源利用。本文的贡献集中于一种新颖且经过改进的遗传算法方法来进行资源协商,以进一步实现移动自组织云的能源优化资源增强。

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