The integration of Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT), which is usually referred to as Wireless Powered Mobile Edge Computing (WP-MEC), has been recognized as a promising technique to enhance the lifetime and computation capacity of wireless devices (WDs). Compared to the conventional battery-powered MEC networks, WP-MEC brings new challenges to the computation scheduling problem because we have to jointly optimize the resource allocation in WPT and computation offloading. In this paper, we consider the energy minimization problem for WP-MEC networks with multiple WDs and multiple access points. We design an online algorithm by transforming the original problem into a series of deterministic optimization problems based on the Lyapunov optimization theory. To reduce the time complexity of our algorithm, the optimization problem is relaxed and decomposed into several independent subproblems. After solving each subproblem, we adjust the computed values of variables to obtain a feasible solution. Extensive simulations are conducted to validate the performance of the proposed algorithm.
翻译:移动边缘计算(MEC)和无线电源传输(WPT)的整合,通常被称为无线动力移动边缘计算(WP-MEC),被认为是提高无线装置寿命和计算能力的有希望的方法。与常规电池驱动的MEC网络相比,WP-MEC给计算时间安排问题带来了新的挑战,因为我们必须共同优化WPT的资源分配和计算卸载。在本文中,我们考虑了多功能和多个接入点的WP-MEC网络的能源最小化问题。我们设计了一种在线算法,根据Lyapunov优化理论将原始问题转化为一系列确定性优化问题。为了减少我们算法的复杂时间,优化问题已经放松,并分解为几个独立的子问题。在解决了每一个子问题之后,我们调整了变量的计算值,以获得可行的解决办法。我们进行了广泛的模拟,以验证拟议的算法的性能。