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本文根据分布式网络系统开放动态的特征,结合粒子群算法和蚁群算法在组合优化中的应用。选择整个信任网络中信任程度最高的实体作为基准,从该信任实体开始出发进行访问请求,依据反馈信息时刻调整实体的信任值。即通过信任网络中实体信任值的选择性优化,对基本动态信任模型进行改进,从而给出一种更优化的动态网络推荐信任模型,提供安全高效的查找信任路径,提高整体资源共享与协同的访问效率。
In this paper, according to the dynamic characteristics of distributed network system open, combined with particle swarm optimization and ant colony algorithm in combinatorial optimization. Select the entity with the highest degree of trust in the entire trust network as a benchmark, start from the trusted entity to make an access request, and adjust the entity’s trust value at any moment according to the feedback information. That is to say, through the selective optimization of the entity trust value in the trust network, the basic dynamic trust model is improved to provide a more optimized dynamic network recommendation trust model, which can provide a safe and efficient search for trust paths and improve the overall resource sharing and coordination Access efficiency.