应用于全光网络恢复优化的自适应性免疫算法

针对全光网的网络恢复问题, 提出了一种基于免疫进化算法的恢复路由优化算法。算法以全光网络的虚拓扑为主要研究对象, 通过对网络虚拓扑的全局优化, 完成网络受损业务恢复。算法在优化过程中引用自适应参数进行调节, 避免了传统进化算法中可能出现的早熟或局部收敛等现象。同时, 算法中还着重考虑了网络资源的利用率问题, 使网络资源利用率最大化, 尽量减少失效造成的业务阻塞。仿真计算结果表明, 该算法在MESH结构全光网络的业务恢复中体现良好的性能优越性。

An Adaptive Immune Evolutionary Algorithm Using in Restoration Optimization of All-Optical Network

This paper introduced a new evolutionary algorithm — adaptive immune evolutionary algorithm (AIEA) for restoration optimization of all-optical network (AON), aim to design the virtual topology, globally optimize re-routing and throughput in the AON. By introducing adjusting parameters, the process of the algorithm can be adapted to the AON dynamically, so as to improve throughput and avoid premature or local convergence. Besides, the algorithm considers optimization of resource utilization in AON at the same time so as to decrease the blocking probability when failures happen in the networks. The results show AIEA has the best optimized performance in performance of optimization restoration in AON of MESH topology networks.