  Mobile-edge computing (MEC) is an emerging paradigm to meet the
ever-increasing computation demands from mobile applications. By offloading the
computationally intensive workloads to the MEC server, the quality of
computation experience, e.g., the execution latency, could be greatly improved.
Nevertheless, as the on-device battery capacities are limited, computation
would be interrupted when the battery energy runs out. To provide satisfactory
computation performance as well as achieving green computing, it is of
significant importance to seek renewable energy sources to power mobile devices
via energy harvesting (EH) technologies. In this paper, we will investigate a
green MEC system with EH devices and develop an effective computation
offloading strategy. The execution cost, which addresses both the execution
latency and task failure, is adopted as the performance metric. A
low-complexity online algorithm, namely, the Lyapunov optimization-based
dynamic computation offloading (LODCO) algorithm is proposed, which jointly
decides the offloading decision, the CPU-cycle frequencies for mobile
execution, and the transmit power for computation offloading. A unique
advantage of this algorithm is that the decisions depend only on the
instantaneous side information without requiring distribution information of
the computation task request, the wireless channel, and EH processes. The
implementation of the algorithm only requires to solve a deterministic problem
in each time slot, for which the optimal solution can be obtained either in
closed form or by bisection search. Moreover, the proposed algorithm is shown
to be asymptotically optimal via rigorous analysis. Sample simulation results
shall be presented to verify the theoretical analysis as well as validate the
effectiveness of the proposed algorithm.
