机会网络中计算节点间相似度的路由算法

Routing Algorithm for Computing Similarity Between Nodes in Opportunistic Network

选择合适的邻居节点进行信息传递是机会网络实现高效转发的关键因素.由于节点的移动性带来的邻居节点选择困难、传输过程不稳定以及网络拓扑结构变化等因素,使得机会网络的传输成功率比较低.针对这一问题,利用节点之间的社会属性进行邻居节点的选择,提出一种基于节点相似度的路由算法(Opportunistic Network Routing Algorithm Based on Node Similarity)(ONNS).首先计算节点之间数据分组的编辑距离,再计算出两个节点的相似度,并按照一定的约束规则对节点间的相似度进行筛选,最终可以得到一条或多条相对比较可靠的传输路径.与传统的路由算法比较,仿真实验表明,相似度算法能够有效地提高传输成功率,降低传输延迟以及路由开销.

In opportunistic network, it is the key point to select the appropriate neighbor nodes for forwarding messages. Due to the difficulty of neighbor nodes selection, the instability of transmission process and the change of network topology caused by the mobili- ty of nodes, the deliver ratio of opportunity network is relatively low. In view of this problem, this paper uses the social attributes be- tween nodes to choose the neighbor nodes, and proposes an algorithm - Opportunistic Network Routing Algorithm Based on Node Similarity （ ONNS ）. First, the algorithm will calculate the edit distance of data packets between nodes, and then calculate the similari- ty between two nodes, and filters the similarity between nodes according to certain constraint rules. Ultimately, we can get one or more relatively reliable transmission paths. The simulation results showed that compared with the traditional routing algorithms, the similarity algorithm can effectively improve the delivery ratio, reduce the transmission delay and the routing overhead.