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Particle Swarm Optimization Based Placement of Data Acquisition Points in a Smart Water Metering Network

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Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016 (IntelliSys 2016)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 16))

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Abstract

A Particle Swarm Optimization (PSO) algorithm for the placement of Data Acquisition Points (DAPs) in a Smart Water Metering Networks is investigated. The PSO algorithm generates particles, which denote the coordinates of the DAPs and creates the topology file by appending these coordinates to the smart meter topology file. It then invokes the Java LinkLayerModel, which generates the link gain file of the network. Once that is done, the TOSSIM Python script is invoked to simulate the network and the packet delivery ratio (PDR) is calculated and designated as the fitness value for the particle. Updates of global best solution are carried out if necessary. This process continues until 50 iterations are reached. Results show that the PDR for 10 DAPs (0.97) in the PSO placement mechanism is better than that of the meter density based placement for 25 DAPs (0.96). It is, therefore, possible to deploy fewer DAPs while achieving even better PDR values. The PSO mechanism also shows more consistency as the meter density based has a higher relative error. In future, some distance based constraints will be incorporated in PSO approach to prevent the problem of smart meters. Multi-core software development techniques will be employed in order to speed up computation on multi-core architectures.

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References

  1. Malcolm, F., Gary, W., Zainuddin, G.: The Manager’s Non-revenue Water Handbook. USAID, Washington, DC (2008)

    Google Scholar 

  2. KPMG International: Sustainable insight-Water scarcity: a dive into global reporting trends. KPMG (2012)

    Google Scholar 

  3. Cardell-Oliver, R., Peach, G.: Making sense of smart metering data: a data mining approach for discovering water use patterns. J. Aust. Water Assoc. 40(2), 124–128 (2013)

    Google Scholar 

  4. McNabb, J.: Vulnerabilities of wireless water meter networks. J.N. Engl. Water Works Assoc. 126(1), 31–37 (2012)

    Google Scholar 

  5. Sensus Research, WATER 20/20: Bringing smart water network into focus. Sensus, North American Headquarters (2012)

    Google Scholar 

  6. Spinsante, S. et al.: Evaluation of the wireless M-bus standard for future smart water grids. In: The 9th International Wireless Communications and Mobile Computing Conference, pp. 1382–1387 (2013)

    Google Scholar 

  7. Shitumbapo, L.N., Nyirenda, C.N.: Simulation of a smart water metering network in Tsumeb East, Namibia. In: International Conference on Emerging Trends in Network and Computer Communication (ETNCC 2015), Windhoek, Namibia, pp. 44–49, 17–20 May 2015

    Google Scholar 

  8. Levis, P. et al.: TOSSIM: accurate and scalable simulation of entire TinyOS applications. In: Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, pp. 126–137. ACM (2003)

    Google Scholar 

  9. Fonseca, R., et al.: The Collection Tree Protocol (CTP). TinyOS TEP 123, 2 (2006)

    Google Scholar 

  10. Kennedy, J.: Particle swarm optimization. In: Sammut, C., Webb, G.I. (eds.) Encyclopedia of Machine Learning, pp. 760–766. Springer, New York (2011)

    Google Scholar 

  11. Alageswaran, R., Kiruthika, G. et al.: Design and implementation of dynamic sink node placement using particle swarm optimization for life time maximization of WSN applications. In: International Conference on Advances in Engineering, Science And Management (2012)

    Google Scholar 

  12. Dandekar, D.R., Deshmukh, P.R.: Energy balancing multiple sink optimal deployment in multi-hop wireless sensor networks. In: 3rd International Advance Computing Conference, pp. 408–412 (2013)

    Google Scholar 

  13. Zhang, B., Robert, S., Hakan, A.: Energy management for time critical energy harvesting wireless sensor networks. In: Stabilization, Safety, and Security of Distributed Systems, pp. 236–251. Springer, Heidelberg (2010)

    Google Scholar 

  14. http://www.map-of-namibia.com/. Accessed 31 Dec 2015

  15. Zuniga, M.: Building a network topology for TOSSIM. http://www.tinyos.net/tinyos-2.x/doc/html/tutorial/usc-topologies.html. Accessed 5 Nov 2015

  16. Takahama, T.: http://www.ints.info.hiroshima-cu.ac.jp/~takahama/download/PSO.html. Accessed 9 Sept 2015

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Correspondence to Clement N. Nyirenda .

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Nyirenda, C.N., Makwara, P., Shitumbapo, L. (2018). Particle Swarm Optimization Based Placement of Data Acquisition Points in a Smart Water Metering Network. In: Bi, Y., Kapoor, S., Bhatia, R. (eds) Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016. IntelliSys 2016. Lecture Notes in Networks and Systems, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-319-56991-8_66

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  • DOI: https://doi.org/10.1007/978-3-319-56991-8_66

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  • Publisher Name: Springer, Cham

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