IJRCS – Volume 3 Issue 1 Paper 6

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IMPROVEMENT OF NETWORK LIFETIME USING MOBILE SENSOR RELOCATION  

Author’s Name : Priyanka G | Keerthana S

Volume 03 Issue 01  Year 2016  ISSN No:  2349-3828  Page no: 19-22

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 Abstract:

The big challenge in wireless sensor network is maximizing network lifetime. The Minimization of Energy consumption is important to improve the network lifetime. Sensor nodes nearer to sink consume more energy than other nodes in the network. The nodes nearer to sink drains fast and causes death of the network. The Mobile Sensor Relocation concept is introduced to improve the network lifetime. In Mobile Sensor Relocation, the sensor nodes in high consumption position are relocated with lower consumption position based on energy threshold using Distributed Consumption Rate Algorithm. The energy threshold is calculated using adaptive energy threshold algorithm. so we can use this approach to extend network lifetime by reducing rotation overhead and  energy consumption.

Keywords:  

Wireless Sensor Networks; Mobile node Relocation; Duty Cycling; Network Lifetime

References:

  1. A. A. Somasundara, A. Ramamoorthy, and M. B. Srivastava, “Mobile element scheduling with dynamic deadlines,” IEEE Trans. Mobile Comput., vol. 6, no. 4, pp. 395–410, Apr. 2007.
  2. J. Luo and J.-P. Hubaux, “Joint mobility and routing for lifetime elongation in wireless sensor networks,” in Proc. IEEE 24th Annu. Joint Conf. IEEE Comput. Commun. Soc., 2005, pp. 1735–1746.
  3. D. Jea, A. A. Somasundara, and M. B. Srivastava, “Multiple Controlled Mobile Elements (Data Mules) For Data Collection In Sensor Networks,” in Proc. 4th IEEE Int.Conf. Distrib.Comput. Sensor Syst., 2005, pp. 244–257.
  4. S. Jain, R. Shah, W. Brunette, G. Borriello, and S. Roy, “Exploiting Mobility For Energy Efficient Data Collection In Wireless Sensor Networks,” Mobile Netw.Appl., vol. 11, no. 3, pp. 327–339, 2006.
  5. G. Xing, T. Wang, Z. Xie, and W. Jia, “Rendezvous Planning In Mobility-Assisted Wireless Sensor Networks,” in Proc. 28th IEEE Int. Real-Time Syst. Symp., 2007, pp. 311–320.
  6. L. Li and J. Halpern, “A Minimum-Energy Path-Preserving Topology-Control Algorithm,” IEEE Trans. Wireless Commun., vol. 3, no. 3, pp. 910–921, May 2004.
  7. Y. Shen, Y. Cai, X. Li, and X. Xu, “The Restricted Shortest-Path Based Topology Control Algorithm In Wireless Multihop Networks,” IEEE Commun. Lett., vol. 11, no. 12, pp. 937–939, Dec. 2007.
  8. D. K. Goldenberg, J. Lin, and A. S. Morse, “Towards mobility as a network control primitive,” in Proc. 5th ACM Int. Symp. Mobile Ad Hoc Netw. Comput., 2004, pp. 163–174.
  9. C. Tang and P. K. McKinley, “Energy optimization under informed mobility,” IEEE Trans. Parallel Distrib. Syst., vol. 17, no. 9, pp. 947–962, Sep. 2006.
  10. F. El-Moukaddem, E. Torng, and G. Xing, “Maximizing Data Gathering Capacity Of Wireless Sensor Networks Using Mobile Relays,” in Proc. IEEE Mobile Adhoc Sensor Syst., 2010, pp. 312–321.
  11. Y. Liu, Z. Luo, K. Xu, and L. Chen, “A Reliable Clustering Algorithm Base On Leach Protocol In Wireless Mobile Sensor Networks,” in Proc. Int. Conf. Mech. Electr. Technol., 2010, pp. 692–696.
  12. F. El-Moukaddem, E. Torng, and G. Xing, “Maximizing network topology lifetime using mobile node rotation,” in IEEE Trans. Parallel Distrib. Syst., vol. 26, no. 7, (2015) pp. 1958–1969.