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Sparse power-efficient topologies for wireless ad hoc sensor networks

机译:用于无线ad Hoc传感器网络的稀疏功率高效拓扑

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We study the problem of power-efficient routing for multi-hop wireless ad hoc sensor networks. The guiding insight of our work is that unlike an ad hoc wireless network, a wireless ad hoc sensor network does not require full connectivity among the nodes. As long as the sensing region is well covered by connected nodes, the network can perform its task. We consider two kinds of geometric random graphs as base interconnection structures: unit disk graphs UDG(2, ????) and k-nearest-neighbor graphs NN(2, k) built on points generated by a Poisson point process of density ???? in R2. We provide subgraph constructions for these two models-UDG-SENS(2, ????) and NN-SENS(2, k) respectively-and show that there are values of the parameters ???? and k, ????s and ks respectively, above which these constructions have the following good properties: (i) they are sparse; (ii) they are power-efficient in the sense that the graph distance is no more than a constant times the Euclidean distance between any pair of points; (iii) they cover the space well; (iv) the subgraphs can be set up easily in a distributed fashion using local information at each node. We also describe a simple local algorithm for routing packets on these subgraphs.
机译:我们研究了多跳无线Ad Hoc传感器网络的高功率路由问题。我们的工作的指导洞察力是,与ad hoc无线网络不同,无线ad hoc传感器网络不需要节点之间的完全连接。只要传感区域被连接的节点覆盖很好,网络就可以执行其任务。我们考虑两种几何随机图作为基础互连结构:单位盘图UDG(2,???)和k最近邻图NN(2,K)构建在由泊松点的密度生成的点上? ???在R 2 中。我们分别为这两个模型提供的子图结构 - UDG-SET(2,????)和NN-SET(2,K) - 并且显示参数的值????和k,???? s 和k s ,这些结构具有以下良好性质:(i)它们是稀疏的; (ii)它们是高效的,因为图形距离不超过任何一对点之间的欧几里德距离的恒定时间; (iii)他们覆盖了空间; (iv)可以使用每个节点的本地信息在分布式时尚中轻松地设置子图。我们还描述了一种用于在这些子图上路由数据包的简单本地算法。

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