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Latency-energy optimization for joint WiFi and cellular offloading in mobile edge computing networks

机译:移动边缘计算网络联合WiFi和蜂窝卸载的延迟 - 能量优化

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摘要

Mobile terminals (MTs) within the coverage of both the WiFi and cellular network can offload computation tasks via the WiFi access point to efficiently release the cellular network congestion and reduce the load on base stations. In this paper, a novel scheme of joint WiFi and cellular offloading is proposed to optimally reduce the latency and energy consumption of MTs in task processing. Based on the statistical characteristics of MTs' task generation, our scheme serves as strategic guidance for computation offloading without frequent execution of the optimization algorithm. MTs with the different channel access priorities are also considered in our scheme. A balance factor is introduced to flexibly adjust the minimization between the energy consumption of MT and the processing latency of its tasks. We design an iterative algorithm combining the linear programming with the Alternating Optimization technique to efficiently solve the non-convex problem for computation tasks offloading decision. The numerical results demonstrate that our scheme can largely improve the system performance, and the superiority of our scheme is shown in all scenarios.
机译:在WiFi和蜂窝网络的覆盖范围内的移动终端(MTS)可以通过WiFi接入点卸载计算任务,以有效地释放蜂窝网络拥塞并减少基站上的负载。在本文中,提出了一种新颖的WiFi和蜂窝卸载方案,以最佳地降低任务处理中MT的延迟和能耗。基于MTS的任务生成的统计特征,我们的方案用于计算卸载的战略指导,而无需频繁执行优化算法。我们的计划中也考虑了不同频道访问优先级的MTS。引入平衡因子以灵活地调整MT的能量消耗与其任务的处理延迟之间的最小化。我们设计一种与交替优化技术结合线性编程的迭代算法,以有效地解决计算任务卸载决策的非凸面问题。数值结果表明,我们的方案可以在很大程度上提高系统性能,并且在所有场景中都显示了我们方案的优势。

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