Multi-access Edge Computing Offloading Method Oriented to Offshore Scenarios

As an important part of the future maritime information intelligent network, the maritime observation monitoring sensor network can provide a variety of observation and monitoring applications. Multi-access edge computing (MAEC) can effectively guarantee a low-delay and high-reliability data transmission for maritime observation monitoring sensor networks and supply various related maritime applications. In this paper, a multi-access edge computing offloading method for offshore scenarios is proposed. A multi-user multi-hop unicast (MMU) offloading model is established for the limited resources of edge computing. Orthogonal frequency division multiple access (OFDMA) technology is used to alleviate the congestion of data unloading. At the same time, the pending tasks have a non-negligible queuing delay on some offloading nodes. In addition, the mixed integer nonlinear optimization problem is separated and the transmission power is effectively allocated by using sub-optimal method. The offloading decision is made by improving the traditional artificial fish swarm algorithm (AFSA). Simulation results show that, the proposed algorithm has a faster convergence speed and can reduce the network delay by nearly 19% comparing with the traditional scheme.