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HIQCO: A Hierarchical Optimization Method for Computation Offloading and Resource Optimization in Multi-Cell Mobile-Edge Computing Systems

机译:HIQCO:多单元移动边缘计算系统中的计算卸载和资源优化的分层优化方法

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Mobile-Edge Computing (MEC) addresses the shortcomings of mobile devices in terms of computing performance and energy efficiency by offloading computation tasks to the edge of the network. In this paper, a multi-cell MEC system is considered, where each small cell connects to a common MEC server, and the problem of minimizing system overhead in the MEC system is solved by jointly optimizing the computation offloading decisions, communication and computational resources. This problem is a mixed integer nonlinear programming problem (MINLP). Owning to the combined nature and complexity of this problem, we adopt a method to transform the original problem into two sub-problems: (i) joint optimization computation offloading decision and channel assignment problem (JO-CODCA) and (ii) joint optimization transmission power and computational resource allocation problem (JO-TPCRA). For the transformed sub-problems, we propose a hierarchical optimization method (HIQCO) that combines immune algorithm (IA), quasi-convex optimization and convex optimization techniques. Experimental results show that the proposed HIQCO give better performance comparing with the other compared algorithms in terms of system overhead.
机译:移动边缘计算(MEC)通过将计算任务卸载到网络边缘来解决移动设备的缺点。在本文中,考虑了多小区MEC系统,其中每个小单元连接到公共MEC服务器,并通过联合优化计算卸载决策,通信和计算资源来解决MEC系统中的系统开销的问题。此问题是混合整数非线性编程问题(MINLP)。拥有这个问题的综合性质和复杂性,我们采用了一种方法来将原始问题转换为两个子问题:(i)联合优化计算卸载决策和通道分配问题(jo-codca)和(ii)联合优化传输权力和计算资源分配问题(jo-tpcra)。对于转换的子问题,我们提出了一种分层优化方法(HIQCO),其结合免疫算法(IA),准凸优化和凸优化技术。实验结果表明,与系统开销方面的其他比较算法,所提出的Hiqco提供更好的性能。

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