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Timetable-aware opportunistic DTN routing for vehicular communications in battlefield environments

机译:战场环境中用于车辆通信的可感知时间表的机会性DTN路由

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Delay tolerant network (namely DTN) is regarded as a promising technology for communications in challenging environments for its resilience and adaptability. However, efficient and reliable routing algorithm design is still one of many difficulties it faces in achieving broad and fruitful applications. Due to reasons like electromagnetic inference, lack of infrastructure and constantly moving, communication among vehicles in battlefield environments is difficult and makes a prospective field for DTN to bring effective improvements. In this paper, a timetable-aware opportunistic DTN routing algorithm combining limited message copies and biased message spray is proposed for this scenario. Firstly, a mobility model named timetable based aggregation and spread (ASMM) is abstracted, which captures both the integrity and individuality in vehicles’ typical moving behavior on military missions. Then, from the time and coordination information contained in the preset timetables, the meeting chances for different node groups can be predicted. This meeting opportunity is used as a utility for message transmission evaluation in our proposed routing algorithm called GenericSpray. GenericSpray is able to make more accurate and motivated message transferring decisions by exploiting contact opportunity prediction in choosing among possible message carriers and deciding appropriate number of copies to spray. To investigate its performance, both ASMM and GenericSpray are implemented on The ONE, a specialized DTN simulation platform. Results of simulation experiments indicate that GenericSpray outperforms all other classical DTN routing algorithms chosen as contrast, in terms of delivery ratio, delivery delay and transmission overhead.
机译:时延容忍网络(即DTN)因其弹性和适应性而被认为是在充满挑战的环境中进行通信的有前途的技术。但是,高效可靠的路由算法设计仍然是实现广泛而富有成果的应用所面临的众多困难之一。由于电磁推理,缺乏基础设施以及不断移动等原因,战场环境中的车辆之间的通信非常困难,这为DTN带来有效的改进提供了广阔的前景。在本文中,针对这种情况,提出了一种将时间表限制的消息副本和有偏差的消息喷雾相结合的可感知时间表的机会性DTN路由算法。首先,抽象出一种称为基于时间表的汇总和扩展(ASMM)的移动性模型,该模型可以捕获车辆在军事任务中典型的移动行为的完整性和个性性。然后,根据预设时间表中包含的时间和协调信息,可以预测不同节点组的开会机会。在我们提出的名为GenericSpray的路由算法中,此会议机会被用作消息传输评估的实用程序。通过利用联系机会预测来选择可能的消息载体并确定要喷涂的适当副本数,GenericSpray能够做出更准确,更积极的消息传递决策。为了研究其性能,ASMM和GenericSpray都在专用DTN模拟平台The ONE上实现。仿真实验结果表明,在传送比率,传送延迟和传送开销方面,GenericSpray优于所有其他经典DTN路由算法。

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