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Energy-Aware Georouting with Guaranteed Delivery in Wireless Sensor Networks with Obstacles

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Abstract

We propose, end-to-end (EtE), a novel EtE localized routing protocol for wireless sensor networks that is energy-efficient and guarantees delivery. To forward a packet, a node s in graph G computes the cost of the energy weighted shortest path (SP) between s and each of its neighbors in the forward direction towards the destination which minimizes the ratio of the cost of the SP to the progress (reduction in distance towards the destination). It then sends the message to the first node on the SP from s to x: say node x′. Node x′ restarts the same greedy routing process until the destination is reached or an obstacle is encountered and the routing fails. To recover from the latter scenario, local minima trap, our algorithm invokes an energy-aware Face routing that guarantees delivery. Our work is the first to optimize energy consumption of Face routing. It works as follows. First, it builds a connected dominating set from graph G, second it computes its Gabriel graph to obtain the planar graph G′. Face routing is invoked and applied to G′ only to determine which edges to follow in the recovery process. On each edge, greedy routing is applied. This two-phase (greedy–Face) EtE routing process reiterates until the final destination is reached. Simulation results show that EtE outperforms several existing geographical routing on energy consumption metric and delivery rate. Moreover, we prove that the computed path length and the total energy of the path are constant factors of the optimal for dense networks.

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Notes

  1. http://www.gps.gov/index.html

  2. http://ec.europa.eu/transport/galileo/index_en.htm

  3. The link layer may raise to the network layer the information which is necessary for the computation of the cost for each neighbor. Basically, the transmission power is sufficient to perform this cost. The evaluation of the required transmission power to reach a given neighbor is the difficult part of this task. Based on received signal strength indicator (RSSI) and link quality indicator (LQI) it is possible to perform this as shown in recent works [14].

  4. In such a Poisson Point Process, the total number of nodes is probabilistic and is obtained from a Poisson Law of intensity λ with \({\lambda}=\frac{\delta} {\pi R^2}.\)

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Acknowledgments

This research was partially supported by NSERC Canada, a grant from CPER Nord-Pas-de-Calais/FEDER TAC COMDOM, from an INRIA ARC program CARMA and from the French National Research Agency RNRT SVP (Supervise and Protect). http://svp.irisa.fr/.

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Authors and Affiliations

  1. University of California, Riverside, CA, USA

    Essia Hamouda

  2. INRIA Lille – Nord Europe, LIFL, Université Lille 1, Villeneuve d’Ascq Cédex, France

    Nathalie Mitton, Bogdan Pavkovic & David Simplot-Ryl

  3. Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia

    Bogdan Pavkovic

Authors
  1. Essia Hamouda
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  2. Nathalie Mitton
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  3. Bogdan Pavkovic
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  4. David Simplot-Ryl
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Correspondence to Essia Hamouda.

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Hamouda, E., Mitton, N., Pavkovic, B. et al. Energy-Aware Georouting with Guaranteed Delivery in Wireless Sensor Networks with Obstacles. Int J Wireless Inf Networks 16, 142–153 (2009). https://doi.org/10.1007/s10776-009-0105-1

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