基于改进哈里斯鹰优化算法的任务卸载策略OA

To address the challenges of resource constraints and system overhead in mobile edge computing systems when off-loading tasks for multiple users simultaneously,this study investigated the task offloading problem in CDMA-based edge com-puting networks.By employing the improved Harris hawk optimization algorithm(IHHO),the research established a mapping relationship between population characteristics and system objectives to jointly optimize system delay and energy consumption,thereby minimizing the overall system cost under constraints such as computing modes,maximum tolerable delay,and the ma-ximum number of devices a single server can accommodate.In solving the problem,the study considered practical factors such as"0-1"offloading of tasks,diversified computing modes,and the tendency of the traditional Harris hawk optimization algo-rithm to fall into local optima.Based on discrete coding and shuffle algorithm initialization,it designed an optimal offloading strategy.Simulation results demonstrate that the proposed algorithm significantly reduces task processing overhead under delay constraints,providing an effective solution for resource allocation in edge computing.