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Economical Revenue Maximization in Cache Enhanced Mobile Edge Computing

机译:高速缓存的经济收入最大化增强移动边缘计算

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Mobile edge computing (MEC) has emerged as a potential paradigm to enhance the processing capabilities of mobile user equipments (MUEs), while edge caching has become a promising means of alleviating traffic in the backhual. In this paper, we formulate a stochastic optimization problem to maximize the average economical profit of MEC server by jointly optimizing offloading decision and caching decision making, and the allocation of radio, computing, and caching resources in a cellular network, with network stability taken into account. To tackle this problem, we develop an online algorithm referred to as dynamic joint computation offloading, resource allocation, and content caching algorithm (DJORC) based on Lyapunov optimization theory. Specifically, the proposed DJORC only needs the current states of the system, and without requiring any prior-knowledge. By further using 0-1 integer programming and linear programming, the closed-form solution of the formulated problem is obtained. Simulation results are presented to verify the performance of DJORC under different parameter settings, as well as the performance gains obtained by DJORC over other existing schemes.
机译:移动边缘计算(MEC)已成为增强移动用户设备(MUE)的处理能力的潜在范例,而边缘缓存已成为缓解后退交通的有希望的手段。在本文中,我们制定了一个随机优化问题,以通过联合优化卸载决策和缓存决策,以及蜂窝网络中的无线电,计算和缓存资源的分配来最大化MEC服务器的平均经济利润,采用网络稳定性帐户。为了解决这个问题,我们基于Lyapunov优化理论,在线开发一个由Lyapunov优化理论的动态联合计算卸载,资源分配和内容缓存算法(DJORC)的在线算法。具体地,所提出的DJORC仅需要系统的当前状态,而不需要任何先前知识。通过进一步使用0-1整数编程和线性编程,获得配制问题的闭合方案。提出了仿真结果以验证DJORC在不同参数设置下的性能,以及DJORC在其他现有方案中获得的性能增益。

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