DOI QR코드

DOI QR Code

A Genetic-Algorithm-Based Optimized Clustering for Energy-Efficient Routing in MWSN

  • Sara, Getsy S. (Department of Electronics and Communication Engineering, College of Engineering, Anna University) ;
  • Devi, S. Prasanna (Department of Computer Science, Apollo College of Engineering) ;
  • Sridharan, D. (Department of Electronics and Communication Engineering, College of Engineering, Anna University)
  • Received : 2012.04.30
  • Accepted : 2012.08.27
  • Published : 2012.12.31

Abstract

With the increasing demands for mobile wireless sensor networks in recent years, designing an energy-efficient clustering and routing protocol has become very important. This paper provides an analytical model to evaluate the power consumption of a mobile sensor node. Based on this, a clustering algorithm is designed to optimize the energy efficiency during cluster head formation. A genetic algorithm technique is employed to find the near-optimal threshold for residual energy below which a node has to give up its role of being the cluster head. This clustering algorithm along with a hybrid routing concept is applied as the near-optimal energy-efficient routing technique to increase the overall efficiency of the network. Compared to the mobile low energy adaptive clustering hierarchy protocol, the simulation studies reveal that the energy-efficient routing technique produces a longer network lifetime and achieves better energy efficiency.

References

  1. S. Deng, J. Li, and L. Shen, "Mobility-Based Clustering Protocol for Wireless Sensor Networks with Mobile Nodes," IET Wireless Sensor Syst., vol. 1, no. 1, 2011, pp. 39-47. https://doi.org/10.1049/iet-wss.2010.0084
  2. A. Nayebi and H. Sarbazi-Azad, "Performance Modeling of the LEACH Protocol for Mobile Wireless Sensor Networks," J. Parallel Distr. Comput., vol. 71, no. 6, 2011, pp. 812-821. https://doi.org/10.1016/j.jpdc.2011.02.004
  3. A. Roy and S.K. Das, "QM2RP: A QOS-Based Mobile Multicast Routing Protocol Using Multi-objective Genetic Algorithm," Wireless Netw. vol. 10, 2004, pp. 271-286. https://doi.org/10.1023/B:WINE.0000023861.10684.f1
  4. C.E. Perkins., Ad Hoc Networking, Addison-Wesley Professional, 2008, pp. 225-226.
  5. M. Buttner et al., "X-MAC: A Short Preamble MAC Protocol for Duty-Cycled Wireless Sensor Networks," Technical Report CU-CS-1008-06, May 2006, pp: 1-11.
  6. J. Polastre, J. Hill, and D. Culler, "Versatile Low Power Media Access for Wireless Sensor Networks," SenSys, ACM, Nov. 2004, pp. 95-100.
  7. F. Liu, C.-Y. Tsui, and Y.J. (Angela) Zhang, "Joint Routing and Sleep Scheduling for Lifetime Maximization of Wireless Sensor Networks," IEEE Trans. Wireless Commun., vol. 9, no. 7, July 2010, pp. 2256-2267.
  8. C. Cano et al., "Analytical Model of the LPL with Wake Up After Transmissions MAC Protocol for MWSN," Proc. ISWCS, 2009, pp. 146-150.
  9. C. Bettstetter, H. Hartenstein, and X. Perez-Costa, "Stochastic Properties of the Random Waypoint Mobility Model," Wireless Netw.: Special Issue Modeling Anal. Mobile Netw., vol. 10, Kluwer Academic Publishers, 2004, pp. 555-567.
  10. E. Hyytia and J. Virtamo, "Random Waypoint Mobility Model in Cellular Networks," Springer Wireless Netw., vol. 13, 2007, pp. 177-188. https://doi.org/10.1007/s11276-006-4600-3
  11. B.A. Attea and E.A. Khalil, "A New Evolutionary Based Routing Protocol for Clustered Heterogeneous Wireless Sensor Networks," Appl. Soft Comput., doi:10,1016/j.soc.2011.04.007.
  12. K. Deb, "Optimization for Engineering Design: Algorithms and Examples," New Delhi: Prentice-Hall of India Private Limited, 2005, pp. 290-319.
  13. MATLAB: www.mathworks.com/products/matlab
  14. M.K. Marina and S. Das, "On-Demand Multipath Distance Vector Routing in Ad Hoc Networks," Proc. Int. Conf. Netw. Protocols, 2001.
  15. G.S. Sara et al., "Energy Efficient Clustering and Routing in Mobile Wireless Sensor Network Routing Protocol," Int. J. Wireless Mobile Netw. (IJWMN), vol. 2, no.4, Nov. 2010, pp: 106-114. https://doi.org/10.5121/ijwmn.2010.2409
  16. C.E. Perkins and E.M. Royer, "Ad Hoc On Demand Distance Vector Routing," Mobile Comput. Syst. Appl. (WMCSA), 1999, pp. 90-100.
  17. OMNET++ Simulator: http://www.omnetpp.org
  18. IRIS motes: http://www.memsic.com/products/wireless-sensor-networks/wireless-modules.html
  19. G. Anastasi et al., "Energy Conservation in Wireless Sensor Networks: A Survey," Ad Hoc Netw. vol. 7, 2009, pp. 537-568. https://doi.org/10.1016/j.adhoc.2008.06.003
  20. S.A. Munir et al., "Mobile Wireless Sensor Network: Architecture and Enabling Technologies for Ubiquitous Computing," Proc. 21st Int. Conf. Adv. Inf. Netw. Appl. Workshop (AINAW), 2007.
  21. X. Min et al., "Energy Efficient Clustering Algorithm for Maximizing Lifetime of Wireless Sensor Networks," Int. J. Electron. Commun. (AEU), vol. 64, no. 4, 2010, pp. 289-298. https://doi.org/10.1016/j.aeue.2009.01.004