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Dense, Concentric, and Non-uniform Multi-hop Sensor Networks

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Theoretical Aspects of Distributed Computing in Sensor Networks

Abstract

In this chapter, we consider a large-scale sensor network, in a circular field, modeled as concentric coronas centered at a sink node. The tiny wireless sensors, severely limited by battery energy, alternate between sleep and awake periods, whereas the sink is equipped with high transmission power and long battery life. The traffic from sensors to the sink follows multi-hop paths in a many-to-one communication pattern. We consider two fundamental and strictly related problems, the localization and the energy hole problems. We first survey on recent algorithms most extensively studied in the literature and summarize their pros and cons with respect to our assumptions. Then we present our solutions tailored for dense and randomly deployed networks. In our localization protocol, the sensors learn their coarse-grain position with respect to the sink, and hence the sink acts as a reference point for the network algorithms, in particular the routing algorithm. For this role of the sink, the network may incur in a special energy hole problem, known as the sink hole problem. From this perspective, the localization and energy hole problems are strictly related. Our solution for the energy hole problem adopts a non-uniform sensor distribution, compatible with the proposed localization solutions, that adds more sensors to the coronas with heavier traffic. In conclusion, we show that the network model under consideration can solve the localization and energy hole problems by properly tuning some network parameters, such as network density.

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Notes

  1. 1.

    Since the behavior of the sensor does not depend on which awake period it is, ν could be omitted from the algorithm description. Indeed this is required just for the analysis purpose.

  2. 2.

    Recall that \((L,k)\) denotes the greatest common divisor between L and k.

  3. 3.

    Obviously, q is limited to the maximum number of sensors that can be deployed in the reachable area. On the one hand, we will see later that the network can achieve very high energy efficiency even with a small q, e.g., \(q = 2\). On the other hand, the size of a sensor could be insignificant compared with a real field for deployment. Therefore this restriction is not a concern.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Center for Research is Wireless Mobility Networking (CReWMaN), University of Texas at Arlington, Arlington, TX, USA

    Sajal K. Das

  2. Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy

    Alfredo Navarra & Cristina M. Pinotti

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  1. Sajal K. Das
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  2. Alfredo Navarra
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  3. Cristina M. Pinotti
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Correspondence to Sajal K. Das .

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Editors and Affiliations

  1. Computer Technology Institute, N. Kazantzaki Street 1, Rion, Patras, 265 04, Greece

    Sotiris Nikoletseas

  2. Centre Universitaire d'Informatique, Université de Genève, rte de Drize 7, Carouge, 1227, Switzerland

    José D.P. Rolim

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Das, S.K., Navarra, A., Pinotti, C.M. (2011). Dense, Concentric, and Non-uniform Multi-hop Sensor Networks. In: Nikoletseas, S., Rolim, J. (eds) Theoretical Aspects of Distributed Computing in Sensor Networks. Monographs in Theoretical Computer Science. An EATCS Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14849-1_17

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