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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.
Aiming at the problem that the traditional opportunistic network routing protocol does not consider the sociality of the nodes, the nodes in the opportunistic social networks show the periodic stability and regularity. The historical information of the nodes is used to compose the social utility vector to predict the network topological structure , This paper proposes a opportunistic network routing algorithm based on social utility vectors. Each node in the algorithm carries its own social utility vector, and according to whether the node and the target node belong to the same community and node, the number of times the social delay control message is forwarded, The communication duration and social validity are used in decision message forwarding to avoid the fragmentation of the message.A simulation experiment is carried out on the real data set PMTR to compare the algorithm with Epidemic, Prophet algorithm, the impact of message lifetime and node cache space on routing performance is analyzed.The simulation results show that the proposed algorithm can reduce the delay rate and bit error rate (BER) compared with Epidemic and Prophet algorithms and improve the success rate of delivery, At the same time slightly better than the number of messages forwarded two classical algorithms.