TTN:移动自组织网络中数据报告的时间到网络方法

P. Sitbon, W. Feng, N. Bulusu
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引用次数: 1

摘要

对于移动无线自组织网络(manet)中的许多应用来说,形成端到端数据路径并不总是必要的;相反,主要路由目标通常是只知道一个数据源的数据收集或分发。必须仔细选择路由算法,以适应使用它们的应用程序的需要。我们的重点是manet中的数据收集应用,其中需要有限的移动信息以可扩展的方式路由数据。为了实现这一目标,我们采用了容忍延迟网络(DTN)的概念,在DTN中,数据向具有高延迟期望和很少了解路由拓扑的目的地前进。具体来说,我们提出了时间到网络(TTN)转发,这是一种将移动节点生成的数据转发到网络端点的方法,这种方法可以降低传输延迟,而无需高网络成本。通过将出行模式划分为行程,我们能够仅使用每辆车的估计目的地到达时间将TTN应用于车辆网络。我们使用来自TRANSIMS模拟器的真实道路网络的移动数据来评估TTN。结果表明,我们的算法产生的集合到网络延迟与更通用的算法相似,但成本更低,效率更高。此外,我们在实验中建立了传递延迟的下界,并将其与TTN进行了比较。这也有助于规范对特定于我们的流动性模型的结果的解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TTN: A time-to-network approach to data reporting in mobile ad hoc networks
For many applications in mobile wireless ad hoc networks (MANETs), forming an end-to-end data path is not always necessary; instead, the primary routing goal is often data collection or dissemination where only a data source is known. Routing algorithms must be carefully chosen in order to suit the needs of applications employing them. Our focus is on data collection applications in MANETs where limited mobility information is required to route data in a scalable manner. To address this goal, we employ the concepts of delay-tolerant networking (DTN) in which data makes progress toward a destination with high latency expectations and little knowledge of routing topology. Specifically, we present time-to-network (TTN) forwarding, a method of forwarding data generated by mobile nodes to a network endpoint in such a way that delivery latency is lowered without high networking cost. By segmenting mobility patterns into trips, we are able to apply TTN to a vehicular network using only an estimated destination arrival time for each vehicle. We evaluate TTN using mobility data from the TRANSIMS simulator for a real road network. Results show that our algorithm produces collection-to-network latencies similar to more generic algorithms but at a lower cost and with higher efficiency. Furthermore, we establish a lower bound for delivery latency in our experiments and compare it to TTN. This also helps normalize the interpretation of results specific to our mobility model.
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