针对传统机会网络路由协议未考虑到节点社会性的问题,根据机会社会网络中节点呈现出周期稳定性和规律性,利用节点累计的历史信息组成“社交效用向量”来预测网络拓扑结构的变化,提出了基于社交效用向量的机会网络路由算法.该算法中每个节点都携带各自的社交效用向量,根据节点与目标节点是否属于同一社区及节点的社交延迟度控制消息的转发次数,同时将连通时长、社交有效性用于决策消息转发,避免消息的碎片化.在真实数据集PMTR上进行仿真实验,从转发消息数、数据包平均延迟及投递成功率三方面将该算法与Epidemic、Prophet经典算法对比,分析了消息生存时间和节点缓存空间对路由性能的影响.仿真实验表明,该算法与Epidemic、Prophet算法相比,减小了延迟率和误码率,提高了投递成功率,同时在转发消息数方面略优于两种经典算法.
As the traditional opportunity network routing protocol does not consider the node social problems, a social utility vector was constructed by using the node accumulated history information to predict the change of network topology based on the periodic stability and regularity of the node in the opportunity social network. The opportunity network routing algorithm was therefore proposed based upon the social utility vector, in which each node carries respective social utility vector. According to whether the node and destination node belong to the same community and the forwarding number of messages controlled by the node social delay, the connectivity duration and social validity could be simultaneously used for the forwarding of decisiommaking messages to avoid their fragmentation. The simulation experiment was performed in the PMTR real data sets. By considering the below three aspects such as the forwarding number of messages, averaged delay of packets and success rate of deliver, the present algorithm would be compared with two classical Epidemic and Prophet algorithms. Additionally, the influences of the message survival time and the node cache space on the routing performance would be also discussed. Simulation results show that compared to Epidemic and Prophet, the proposed algorithm reduce the delay rate and bit error rate, and improve the success rate of delivery. At the same time, it is slightly better in the forwarding number of messages than the above two classical algorithms.