ASCENT: Adaptive self-configuring sensor networks topologies

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ASCENT: Adaptive self-configuring sensor networks topologies (2004)

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by Alberto Cerpa , Deborah Estrin

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446 - 15 self

BibTeX

@MISC{Cerpa04ascent:adaptive,
    author = {Alberto Cerpa and Deborah Estrin},
    title = {ASCENT: Adaptive self-configuring sensor networks topologies},
    year = {2004}
}

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Abstract

Advances in microsensor and radio technology will enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. The low per-node cost will allow these wireless networks of sensors and actuators to be densely distributed. The nodes in these dense networks will coordinate to perform the distributed sensing and actuation tasks. Moreover, as described in this paper, the nodes can also coordinate to exploit the redundancy provided by high density so as to extend overall system lifetime. The large number of nodes deployed in these systems will preclude manual configuration, and the environmental dynamics will preclude design-time preconfiguration. Therefore, nodes will have to self-configure to establish a topology that provides communication under stringent energy constraints. ASCENT builds on the notion that, as density increases, only a subset of the nodes are necessary to establish a routing forwarding backbone. In ASCENT, each node assesses its connectivity and adapts its participation in the multihop network topology based on the measured operating region. This paper motivates and describes the ASCENT algorithm and presents analysis, simulation, and experimental measurements. We show that the system achieves linear increase in energy savings as a function of the density and the convergence time required in case of node failures while still providing adequate connectivity.

Keyphrases

adaptive self-configuring sensor network topology design-time preconfiguration adequate connectivity dense network energy saving node failure overall system lifetime radio technology density increase high density large number environmental dynamic experimental measurement smart sensor convergence time linear increase wide range present analysis manual configuration distributed sensing operating region wireless network environmental monitoring application stringent energy constraint actuation task low per-node cost multihop network topology ascent algorithm

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