Minimum-delay energy-efficient source to multisink routing in wireless sensor networks
Minimum-delay energy-efficient source to multisink routing in wireless sensor networks
复制标题
无线传感器网络中的最小延迟节能源到多接收器路由
DOI：
10.1016/j.sigpro.2007.05.011
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
Chang
中科院分区：
文献类型：
--
作者：
Shun;Chien Chen;Chang
提出了一种简单、可扩展的无线传感器网络多链路路由方案。无线传感器网络是一门快速发展的学科，新技术不断涌现，新应用不断开发。除了提供光和温度测量外，无线传感器节点还具有诸如安全监视、环境监测和野生动物观察等应用。传感器网络中的一个潜在问题是如何有效地将分组从单源传输到多宿，即，从单个传感器节点收集数据并将其传递给对数据感兴趣的多个客户端。这种情况下的困难是找到最小成本的多个传输路径。许多路由算法已经被提出来解决这个问题。大多数当前算法都致力于降低功耗，但可能会引入很大的延迟。本文提出了一种新的多路径路由算法，称为基于跳数的路由（HCR）算法，它同时考虑了能量成本和传输延迟。引入跳数向量（HCV）来支持路由决策。此外，额外的修剪向量（PV）可以进一步提高路由性能。该算法还提供了一个维护机制来处理故障节点的后果。节点的故障导致不准确的HCV。因此，一个有效的校正算法是必要的。一个辅助树（A-TREE）是用来促进限制洪水。这种校正机制比全尺寸溢流更有效地校正有限的不准确的HCV。最后，研究了失效节点的影响，并提出了一种提高HCR鲁棒性的算法--Lazy-Ranking。
This paper proposes a simple and scalable approach to multisink routing scheme in wireless sensor networks. Wireless sensor network is a rapidly growing discipline, with new technologies emerging and new applications under development. In addition to providing light and temperature measurements, wireless sensor nodes have applications such as security surveillance, environmental monitoring, and wildlife watching. One potential problem in a sensor network is how to transmit packets efficiently from single-source to multi-sinks, i.e., to gather data from a single sensor node and deliver it to multiple clients who are interested in the data. The difficulty of such a scenario is finding the minimum-cost multiple transmission paths. Many routing algorithms have been proposed to solve this problem. Most current algorithms address the reduction of power consumption, and potentially introduce a large delay. This paper proposes a novel multi-path routing algorithm, called hop count based routing (HCR) algorithm, which considers energy cost and transmission delay simultaneously. A hop count vector (HCV) is introduced to support routing decision. Moreover, an additional pruning vector (PV) can further enhance routing performance. The proposed algorithm also provides a maintenance mechanism to handle the consequence of faulty nodes. A failure of a node leads to an inaccurate HCV. Therefore, an efficient correction algorithm is necessary. An Aid-TREE (A-TREE) is applied to facilitate restricted flooding. This correction mechanism is more efficient than full-scale flooding for correcting the limited inaccurate HCVs. Finally, the impact of failed nodes is studied, and an algorithm, called Lazy-Grouping, is proposed to enhance the robustness of HCR.