数据高速公路

K. Gomez, D. Miorandi, D. Lowe
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引用次数: 0

摘要

高效路由算法的设计是密集自组织无线网络中的一个重要问题。先前的理论工作已经表明,可以通过创建一组数据“高速公路”来实现利益,这些高速公路可以在网络上从源(s)到接收(s)传输数据包。然而,目前设计这些高速公路的方法需要先验的全球网络拓扑知识,随之而来的是通信负担和可扩展性问题,特别是关于节点故障后的重新配置。在本章中,我们描述了一种生物启发的方法,通过使用局部卷积和激活抑制过滤器的分布式反应扩散模型来生成这些数据高速公路。其结果是数据高速公路的分布式出现,可以对其进行调优,以提供适当的高速公路分离和到数据接收器的连接。在本章中,我们介绍了在密集无线传感器网络中生成数据高速公路的基本模型、算法和协议。通过omnet++进行的大量仿真验证了所提出的方法。
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Data Highways
The design of efficient routing algorithms is an important issue in dense ad hoc wireless networks. Previous theoretical work has shown that benefits can be achieved through the creation of a set of data "highways" that carry packets across the network, from source(s) to sink(s). Current approaches to the design of these highways however require a-priori knowledge of the global network topology, with consequent communications burden and scalability issues, particularly with regard to reconfiguration after node failures. In this chapter, we describe a bio-inspired approach to generating these data highways through a distributed reaction-diffusion model that uses localized convolution with activation-inhibition filters. The result is the distributed emergence of data highways that can be tuned to provide appropriate highway separation and connection to data sinks. In this chapter, we present the underlying models, algorithms, and protocols for generating data highways in a dense wireless sensor network. The proposed methods are validated through extensive simulations performed using OMNeT++.
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