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Is Sensor Deployment Using Gaussian Distribution Energy Balanced?

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8285))

Abstract

Energy is one of the scarcest resources in wireless sensor network (WSN). One fundamental way of conserving energy is judicious deployment of sensor nodes within the network area so that energy flow remains balanced throughout the network. Node deployment using Gaussian distribution is a standard practice and is widely acceptable when random deployment is used. Initially, an analysis is done to establish that Gaussian distribution based node deployment is not energy balanced. Standard deviation has been identified as the parameter responsible for energy balancing. A deployment strategy is proposed for energy balancing using customized Gaussian distribution by discretizing the standard deviation. Performance of the deployment scheme is evaluated in terms of energy balance and network lifetime. Simulation results demonstrate that proposed deployment strategy significantly outperforms conventional Gaussian distribution based node deployment scheme in terms of the two performance metrics.

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References

  1. Halder, S., Ghosal, A., DasBit, S.: A Pre-determined Node Deployment Strategy to Prolong Network Lifetime in Wireless Sensor Network. Computer Communications 34(11), 1294–1306 (2011)

    Article  Google Scholar 

  2. Halder, S., Ghosal, A., Saha, A., DasBit, S.: Energy-Balancing and Lifetime Enhancement of Wireless Sensor Network with Archimedes Spiral. In: Hsu, C.-H., Yang, L.T., Ma, J., Zhu, C. (eds.) UIC 2011. LNCS, vol. 6905, pp. 420–434. Springer, Heidelberg (2011)

    Google Scholar 

  3. Wu, X., Chen, G., Das, S.K.: Avoiding Energy Holes in Wireless Sensor Networks with Nonuniform Node Distribution. IEEE Trans. on Parallel and Distributed Systems 19(5), 710–720 (2008)

    Article  Google Scholar 

  4. Wang, D., Xie, B., Agrawal, D.P.: Coverage and Lifetime Optimization of Wireless Sensor Networks with Gaussian Distribution. IEEE Trans. on Mobile Computing 7(12), 1444–1458 (2008)

    Article  Google Scholar 

  5. Wang, F., Wang, D., Liu, J.: Traffic-Aware Relay Node Deployment: Maximizing Lifetime for Data Collection Wireless Sensor Networks. IEEE Trans. on Parallel and Distributed Systems 22(8), 1415–1423 (2011)

    Article  Google Scholar 

  6. Azad, A.K.M., Kamruzzaman, J.: Energy-Balanced Transmission Policies for Wireless Sensor Networks. IEEE Trans. on Mobile Computing 10(7), 927–940 (2011)

    Article  Google Scholar 

  7. Boukerche, A., Efstathiou, D., Nikoletseas, S.E., Raptopoulos, C.: Exploiting Limited Density Information Towards Near-optimal Energy Balanced Data Propagation. Computer Communications 35(18), 2187–2200 (2012)

    Article  Google Scholar 

  8. Lin, K., Chenb, M., Zeadally, S., Rodrigues, J.J.P.C.: Balancing Energy Consumption with Mobile Agents in Wireless Sensor Networks. Future Generation Computer Systems 28(2), 446–456 (2012)

    Article  Google Scholar 

  9. Huang, R., Song, W.Z., Xu, M., Peterson, N., Shirazi, B., LaHusen, R.: Real-World Sensor Network for Long-Term Volcano Monitoring: Design and Findings. IEEE Trans. on Parallel and Distributed Systems 23(2), 321–329 (2012)

    Article  Google Scholar 

  10. Ahn, G.S., Miluzzo, E., Campbell, A.T., Hong, S.G., Cuomo, F.: Funneling-MAC: A Localized, Sink-Oriented MAC For Boosting Fidelity in Sensor Networks. In: Proc. of 4th ACM Int’l Conf. on Embedded Network and Sensor System, pp. 293–306 (2006)

    Google Scholar 

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© 2013 Springer International Publishing Switzerland

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Halder, S., Ghosal, A. (2013). Is Sensor Deployment Using Gaussian Distribution Energy Balanced?. In: Kołodziej, J., Di Martino, B., Talia, D., Xiong, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2013. Lecture Notes in Computer Science, vol 8285. Springer, Cham. https://doi.org/10.1007/978-3-319-03859-9_5

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  • DOI: https://doi.org/10.1007/978-3-319-03859-9_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03858-2

  • Online ISBN: 978-3-319-03859-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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