基于改进蚁群算法的天基资源调度研究与仿真

Research and Simulation of Space-based Resource Scheduling Based on Improved Ant Colony Algorithm

天基信息网中卫星资源有限,在轨升级难度大,链路间通信时延高,导致大规模并发任务处理效率低下.针对任务简单并发且每个任务由一个节点处理的情况,构建基于动态优先级的任务模型,对天基信息网计算与存储资源构建基于模糊聚类理论的资源模型.提出基于改进蚁群算法的天基资源调度策略,引入负载均衡因子,改变信息素更新规则,调整任务分配策略,结合Min-Min算法促进任务执行及资源分配.仿真结果表明,本文算法和对比算法相比,任务完成时间缩短29.2%,任务累积价值高出37.9%,资源负载均衡度缩小75.5%,资源利用率高出22.4%,验证了本文算法的优异性.

The satellite resources of the space-based information network are limited.It is difficult to upgrade in orbit and the delay of inter-link communication is high,which results in inefficient processing of large-scale concurrent tasks.A dynamic priority-based task model is constructed for situations where the task is simple and concurrent and each task is handled by one node.A resource model based on fuzzy clustering theory is constructed for computing and storage resources in space-based information network.Space-based resource scheduling strategy based on improved ant colony algorithm is proposed.Load balancing factor is introduced.Pheromone update rule is changed.Task allocation strategy is adjusted.Min-Min-algorithm is combined to promote task execution and resource allocation.Simulation results show that compared with the comparison algorithm,the task completion time is 29.2%shorter,the task cumulative value is 37.9%higher,the resource load equilibrium degree is 75.5%smaller,and the resource utilization rate is 22.4%higher,which verifies the excellence of the algorithm.