基于节点相似性的容延/容断网络路由算法

Routing algorithm based on node similarity in delay /disruption tolerant networks

针对容延/容断网络(DTN)网络的时延高、割裂频繁,以及节点缓存和能量受限等网络特性,为提高容延网络的传输率,同时降低网络开销和网络时延,提出了一种基于节点相似性的容延网络路由算法(RABNS)。该算法利用历史相遇信息预测节点未来相遇概率,并且把历史相遇的节点录入为集合,利用集合的交集运算来评估一对相遇节点的相似性,并以此为判定条件控制网络中的副本数量。在模拟器The ONE上采用RandomWaypoint运动模型进行仿真,其中RABNS在消息投递率方面优于PROPHET,网络负载约为PROPHET的50%,较大程度上提高了网络资源利用率;平均时延稍高于Epidemic但低于PROPHET,节点缓存空间大小对算法的平均跳数影响不大,且RABNS的平均跳数约为PROPHET的一半。仿真结果表明,RABNS能有效地限制消息洪泛,获取更高的消息投递率、更低的网络开销和数据时延,因此尤其适用于节点存储空间有限的DTN环境和具有群居特性的社交容延网络中。

Delay /Disruption Tolerant Network( DTN) has characteristics of long delay, intermittent disruption, and limitation of buffer space and energy. To improve the delivery rate of messages, while reducing network overhead and the average latency, a new Routing Algorithm Based on Node Similarity( RABNS) in DTN was proposed. The algorithm used historical information to predict node encounter probability in future. The nodes which encountered historically were recorded as a collection, then the set intersection operation was applied to evaluate the similarity of a pair of nodes. And the similarity was used to control the number of copies in the network. Simulations were conducted on The ONE platform using RandomWaypoint motion model. In the simulation, RABNS performed better than PROPHET( Probabilistic ROuting Protocol using History of Encounters and Transitivity) in the message delivery rate. And the network overhead of RABNS was about half of PROPHET, which greatly improved the utilization of network resources. The average latency of RABNS was a little higher than Epidemic but lower than PPROPHET, the node cache size did not have a significant impact on average-hops, and its average-hops was about half of PROPHET. The simulation results show that RABNS can effectively limit the message flooding with higher message delivery rate, lower network overhead and average latency, therefore it is suitable for the DTN scenes with limited nodes' storage and also applicable in social DTN with gregarious characteristics.