Research Area: Edge Computing
Edge computing, an extension of cloud computing, is introduced to provide sufficient computing and storage resources for mobile devices. Moreover, a series of computing tasks in a mobile device are set as structured computing processes and flows to achieve effective management by the workflow. However, the execution uncertainty caused by performance degradation, service failure, and new service additions remains a huge challenge to the users service experience. In order to address the uncertainty, a software-defined network (SDN)-based edge computing framework and a dynamic resource provisioning (UARP) method are proposed in this paper. The UARP method is implemented in the proposed framework and addresses the uncertainty through the advantages of SDN. In addition, the nondominated sorting genetic algorithm-III is employed to optimize two goals, that is, the energy consumption and the completion time, to obtain balanced scheduling strategies. The comparative experiments are performed and the results show that the UARP method is superior to other methods in addressing the uncertainty, while reducing energy consumption and shortening the completion time.
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Author(s) Name: Xiaolong Xu,Hao Cao,Qingfan Geng,Xihua Liu,Fei Dai,Chuanjian Wang
Journal name: Concurrency and Computation
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Publisher name: Wiley
DOI: https://doi.org/10.1002/cpe.5674
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