基于鸟群人工鱼群算法的区块链移动边缘计算卸载模型.

The rapid increase in the number of computing intensive tasks has led to an overload of SMD (Smart Mobile Devices) computing tasks. By using MEC(Mobile Edge Computing Servers) and idle ED (Edge Devices) in the network, SMD with limited computing power can offload computing tasks to MEC and ED collaboration, and enhance system security based on the DPoR (Delegated Proof of Reputation) consensus mechanism. This study proposes a blockchain mobile edge computing offloading model based on BS AFSA (Bird Swarm Artificial Fish Swarm Algorithm), which transforms the task offloading problem into an optimization objective function to reduce the computational overhead. The improved BS AFSA is used to optimize the task delay and energy consumption, and the behavior parameters in the algorithm are constructed and the crowding factor is improved to elevate the local search accuracy in the later iteration. The simulation results show that compared with other benchmark algorithms, the proposed algorithm reduces the possibility of falling into local optimum and effectively reduces the total system cost of the joint offloading scheme. [ABSTRACT FROM AUTHOR]