arXiv cs/02090122002-09-05cs.NI

一种基于锥的无线多跳网络分布式拓扑控制算法分析

Analysis of a Cone-Based Distributed Topology Control Algorithm for Wireless Multi-hop Networks

Erran L. Li, Joseph Y. Halpern, Paramvir Bahl, Yi-Min Wang, Roger Wattenhofer

备注：: 10 pages
发表信息：: ACM PODC, 2001

摘要：

无线多跳网络的拓扑结构可以通过改变每个节点处的传输功率来控制。本文详细分析了一种基于锥的分布式拓扑控制算法。在[16]中介绍的该算法不假设节点具有可用的GPS信息;相反，它仅依赖于方向信息。粗略地说，该算法的基本思想是节点$u$以所需的最小功率$p_{u,α}$进行发送，以确保在$u$周围的每个度锥$α$中，存在$u$可以以功率$p_{u,α}$到达的某个节点。我们表明，采取$α= 5π/6$是一个必要和充分条件，以保证网络的连通性。更精确地，如果当每个节点以最大功率通信时存在从$s$到$t$的路径，则如果$α<= 5π/6$，则在包含所有边$(u,v)$的最小对称图$G_α$中仍然存在路径，使得$u$可以使用功率$p_{u,α}$与$v$通信。另一方面，如果为$α> 5π/6$，则不一定保留连接性。我们还提出了一组优化，进一步降低功耗，并证明他们保持网络连接。在故障和移动性的存在下的动态重配置进行了讨论。仿真结果验证了算法和优化的有效性。

英文摘要：

The topology of a wireless multi-hop network can be controlled by varying the transmission power at each node. In this paper, we give a detailed analysis of a cone-based distributed topology control algorithm. This algorithm, introduced in [16], does not assume that nodes have GPS information available; rather it depends only on directional information. Roughly speaking, the basic idea of the algorithm is that a node $u$ transmits with the minimum power $p_{u,α}$ required to ensure that in every cone of degree $α$ around $u$, there is some node that $u$ can reach with power $p_{u,α}$. We show that taking $α= 5π/6$ is a necessary and sufficient condition to guarantee that network connectivity is preserved. More precisely, if there is a path from $s$ to $t$ when every node communicates at maximum power, then, if $α<= 5π/6$, there is still a path in the smallest symmetric graph $G_α$ containing all edges $(u,v)$ such that $u$ can communicate with $v$ using power $p_{u,α}$. On the other hand, if $α> 5π/6$, connectivity is not necessarily preserved. We also propose a set of optimizations that further reduce power consumption and prove that they retain network connectivity. Dynamic reconfiguration in the presence of failures and mobility is also discussed. Simulation results are presented to demonstrate the effectiveness of the algorithm and the optimizations.

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