边缘计算中基于混沌理论的任务调度优化策略

Task scheduling optimization strategy based on chaos theory in edge computing

针对边缘场景中,多用户低效通信而导致的边缘服务资源无效占用及用户卸载能耗较高等问题,提出了优化预期成功任务卸载能耗的目标.在保证最低通信质量的前提下,考虑传输质量以及拥塞情况对于任务卸载性能的影响,构造用户与基站成功建立通信的机遇函数.综合考虑异构基站的服务能力限制,通过排队论为卸载任务的排队机制建模,并为用户实现更可靠传输以及接受更空闲的服务资源设置高效的任务分配策略.采用基于混合罚函数的混沌搜索任务分配算法,利用混沌现象的伪随机及遍历特性,搜索并获取决策最优解.仿真结果表明:所提方案可加速收敛,有效降低用户卸载能耗,并提升通信质量.

For edge scenarios,inefficient multiuser communication results in invalid occupation of edge service resources and high energy consumption for user offloading,the objective of optimizing the energy consumption for expected successful task offloading was proposed.On the premise of ensuring the minimum communication quality,considered the impact of transmission quality and congestion on task offloading performance,and the opportunity function for the successful establishment of communication between the user and the base station was constructed. Comprehensive consideration of the service capacity limitations of heterogeneous base stations,the queuing theory was used to model the queuing mechanism of offloading tasks,and efficient task assignment strategies were set up for users to realize more reliable transmission and accept idler service resources. The chaotic search task allocation algorithm based on the mixed penalty function was adopted,and the pseudo-random and ergodic characteristics of chaos were used to search and obtain the optimal solution of decision. The simulation results show that the proposed scheme can accelerate convergence,effectively reduce user offloading energy consumption,and improve the communication quality.