  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.
