Task urgency-based resource allocation algorithm in industrial Internet of things
In the industrial Internet of things,the generation of tasks is observed to exhibit both continuity and period-icity,along with stringent latency requirements.These characteristics posed challenges to system's cost-efficiency.To address these challenges,a cost minimization resource allocation algorithm based on the urgency of tasks was pro-posed.By employing a genetic algorithm,the task offloading strategy and the system's resource allocation strategy were optimized.For offloaded tasks,they were scheduled according to their level of urgency.Additionally,the opti-mal transmission power for each task was calculated to meet latency constraints.Simulation results indicate that the proposed algorithm effectively reduces the overall energy cost of the system.
万方数据
维普
