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Distributed Algorithms for Constructing Approximate Minimum Spanning Trees in Wireless Sensor Networks

机译:在无线传感器网络中构造近似最小生成树的分布式算法

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摘要

While there are distributed algorithms for the MST problem, these algorithms require relatively large number of messages and time; this makes these algorithms impractical for resource-constrained networks such as ad hoc wireless sensor networks. In such networks, a sensor has very limited power, and any algorithm needs to be simple, local, and energy efficient for being practical. Motivated by these considerations, we design and analyze a class of simple and local distributed algorithms called Nearest Neighbor Tree (NNT) algorithms for energy-efficient construction of MSTs in a wireless ad hoc setting. We assume that the nodes are uniformly distributed in a unit square and show provable bounds on the performance with respect to both the quality of the spanning tree produced and the energy needed to construct them. In particular, we show that NNT produces a close approximation to the MST, and they can be maintained dynamically with polylogarithmic number of rearrangements under node insertions/deletions. We also perform extensive simulations of our algorithms. We tested our algorithms on both uniformly random distributions of nodes, and on a realistic distributions of nodes in an urban setting. Simulations validate the theoretical results and show that the bounds are much better in practice.
机译:尽管存在用于MST问题的分布式算法,但是这些算法需要相对大量的消息和时间。这使得这些算法对于资源受限的网络(例如ad hoc无线传感器网络)不切实际。在这样的网络中,传感器的功率非常有限,并且任何算法都必须简单,本地且具有能源效率才能实用。基于这些考虑,我们设计和分析了一类简单且本地的分布式算法,称为“最近邻居树”(NNT),用于在无线ad hoc环境中高效构造MST。我们假设节点均匀地分布在一个单位正方形中,并且在性能方面相对于生成的生成树的质量和构造它们所需的能量都显示出可证明的界限。特别是,我们表明NNT产生的近似值与MST接近,并且可以使用节点插入/删除下的重数对数动态维护NNT。我们还对算法进行了广泛的仿真。我们在节点的均匀随机分布和城市环境中的节点的实际分布上测试了我们的算法。仿真验证了理论结果,并表明在实践中界限要好得多。

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