Relay Placement for Higher Order Connectivity in Wireless Sensor Networks

Abhishek Kashyap, S. Khuller, M. Shayman
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引用次数: 124

Abstract

Sensors typically use wireless transmitters to communicate with each other. However, sensors may be located in a way that they cannot even form a connected network (e.g, due to failures of some sensors, or loss of battery power). In this paper we consider the problem of adding the smallest number of additional (relay) nodes so that the induced communication graph is 2-connected. The problem is NP -hard. In this paper we develop O(1)-approximation algorithms that find close to optimal solutions in time O((kn)) for achieving k-edge connectivity of n nodes. The worst case approximation guarantee is 10, but the algorithm produces solutions that are far better than this bound suggests. We also consider extensions to higher dimensions, and the scheme that we develop for points in the plane, yields a bound of 2dMST where dMST is the maximum degree of a minimum-degree Minimum Spanning Tree in d dimensions using Euclidean metrics. In addition, our methods extend with the same approximation guarantees to a generalization when the locations of relays are required to avoid certain polygonal regions (obstacles). We also prove that if the sensors are uniformly and identically distributed in a unit square, the expected number of relay nodes required goes to zero as the number of sensors goes to infinity.
无线传感器网络中高阶连接的中继安置
传感器通常使用无线发射器相互通信。然而,传感器的位置可能无法形成连接网络(例如,由于某些传感器故障,或电池电量耗尽)。本文考虑添加最小数量的附加(中继)节点,使感应通信图是2连通的问题。这个问题是NP困难的。为了实现n个节点的k边连通性,我们开发了O(1)-近似算法,该算法在O((kn))时间内找到接近最优解。最坏情况下的近似保证是10,但算法产生的解远远好于这个界限。我们还考虑了向高维的扩展,我们为平面上的点开发的方案产生了2dMST的界,其中dMST是使用欧几里德度量在d维中最小度最小生成树的最大度。此外,当继电器的位置需要避开某些多边形区域(障碍物)时,我们的方法以相同的近似保证扩展到泛化。我们还证明了如果传感器均匀分布在一个单位正方形中,则随着传感器数量趋于无穷大,所需中继节点的期望数量趋于零。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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