基于数据挖掘的复杂光通信网络节点调度方法

Node scheduling method for complex optical communication network based on Data Mining

为解决当前光通信节点调度中存在的调度效率低,网络覆盖率低的缺陷,提出基于数据挖掘的复杂光通信网络节点调度方法。结合当前光通信网络节点调度的研究进展,找出光通信网络节点调度方法的不足,结合光通信链路方式构建复杂光通信网络模型,利用学习自动机计算方法实现复杂光通信网络节点调度。实验结果表明:当网络节点数量为500个时,设计方法网络覆盖率为0.942%,当网络节点数量相同时,设计方法耗时在6 s以内,综上可知设计方法提高了网络覆盖率和节点调度效率,获得了理想的复杂光通信网络节点调度结果。

In order to solve the problems of low scheduling efficiency and low network coverage in current optical communication node scheduling, a node scheduling method based on data mining for complex optical communication network is proposed. Combined with the current research progress of optical communication network node scheduling, find out the shortcomings of optical communication network node scheduling method, combined with optical communication link mode to build a complex optical communication network model, using learning automata calculation method to achieve complex optical communication network node scheduling. The experimental results show that: when the number of network nodes is 500, the network coverage of the design method is 0.942%, and when the number of network nodes is the same, the design method takes less than 6 s. In conclusion, the design method improves the network coverage and node scheduling efficiency, and obtains the ideal node scheduling results of complex optical communication network.