Resource Allocation for OFDM-based Maritime Edge Computing Networks

Abstract

Unmanned Surface Vehicles (USVs) can support various maritime applications, such as ocean environment monitoring and target tracking applications. Mobile Edge Computing (MEC) is a promising technology to improve the computing capacities and energy efficiencies of the USVs with latency sensitive computation tasks. In this paper, an OFDM-based maritime broadband MEC system model is developed, where a command surface vehicle provides edge computing service to the surrounding USVs, and the task offloading and resource allocation are formulated as an optimization problem with a goal of minimizing the USVs energy consumption, constrained by the task execution delay requirement and allowable transmit power. First, the optimal transmit power allocation scheme for each USV is obtained based on the water filling algorithm to improve the transmission rate of the OFDM-based wireless link. Second, the sub-problem of the task offloading transmission time allocation is solved by means of the CVX optimization toolbox. Simulation results show that the proposed offloading algorithm can effectively reduce the energy consumption of the maritime MEC system and adapt to a dense USVs MEC environment.