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为了优化战场环境下延迟容忍网络(DTN)的服务性能,提出了一种符合战斗车队移动模式和业务特点的基于时间表的DTN机会预测路由算法.首先,鉴于战场车辆移动兼具个体性和整体性且需遵循预定行动计划的要求,设计了能较好反映车队行动特点的集结G展开移动模型.然后,针对现有DTN路由算法中存在的副本转发数量多和投递延迟大等问题,利用车辆行动计划时间表来预测节点之间的相遇机会,并适当限制了消息副本的转发数量,从而有效提高数据的传输效率和网络性能.仿真结果表明,相比于典型DTN路由算法,基于时间表的DTN机会预测路由算法在投递率、投递时延和传输开销等性能指标上均有明显改善.
In order to optimize service performance of DTN in battlefield environment, a schedule-based DTN opportunistic routing algorithm is proposed, which is in line with the battle mode and service features of fleet.Firstly, considering that battlefield vehicles have both individuality and overall movement In order to meet the requirements of scheduled action plan, a set-up moving model of G-Gomotor that can reflect the characteristics of fleet operations is designed.Then, aiming at the problems of large number of delivery and delay in existing DTN routing algorithms, Action plan schedule to predict the chances of encountering nodes and appropriately limit the number of copies of the message to effectively improve data transmission efficiency and network performance.The simulation results show that compared with the typical DTN routing algorithm, DTN opportunity prediction routing algorithm in the delivery rate, delivery delay and transmission overhead and other performance indicators have significantly improved.