基于Spark的PageRank算法优化及其军事应用研究

An Optimization Method of PageRank Based on Spark and its Application Research

本文以军事通信网络为研究对象,针对"从复杂军事通信网络"中发现核心军事通信网络节点即重要军事目标难度大的问题,通过分析传统PageRank算法无法体现军事领域中时间、权威性和虚假消息等干扰方面的问题,对PageRank算法进行了改进,可通过通信网络节点之间的通信信息自动排除部分虚假消息,从而获得最重要的节点和隐蔽节点;同时,进行了仿真试验验证。试验结果表明:该算法合理有效,可为开展相关应用研究提供支撑。

This paper takes the military communication network as the research object. In view of the difficulty of discovering the important military target of the core military communication network from the complex military communication network,the traditional PageRank algorithm can not reflect the time,authority and false information in the military field. We propose a PageRank optimization algorithm and some false messages can be automatically excluded by the communication information between communication network nodes to obtain the most important nodes and hidden nodes. At the same time,simulation experiments are carried out. The experimental results show that the algorithm is reasonable and effective,which can provide support for the related application research.