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Sparse power-efficient topologies for wireless ad hoc sensor networks

机译:无线ad hoc传感器网络的省电拓扑稀疏

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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自组织传感器网络的节能路由问题。我们工作的指导性见解是,与自组织无线网络不同,无线自组织传感器网络不需要节点之间的完全连接。只要感测区域被连接的节点很好地覆盖,网络就可以执行其任务。我们将两种几何随机图视为基础互连结构:单位磁盘图UDG(2,Â)和k最近邻图NN(2,k)建立在密度泊松点过程生成的点上在R 2 中。我们分别为这两个模型(UDG-SENS(2,)和NN-SENS(2,k))提供子图构造-并显示参数Â和k,Ã的值 s 和k s ,它们的构造在其上具有以下良好的性能:(i)它们是稀疏的; (ii)从图形距离不超过任何一对点之间的欧几里得距离的常数的意义上讲,它们是省电的; (iii)它们很好地覆盖了整个空间; (iv)可以使用每个节点上的本地信息以分布式方式轻松设置子图。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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