KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
권호 표지
DOI QR코드

DOI QR Code

RRSEB: A Reliable Routing Scheme For Energy-Balancing Using A Self-Adaptive Method In Wireless Sensor Networks

  • Shamsan Saleh, Ahmed M. (Wireless Communications Cluster, MIMOS Berhad, Technology Park Malaysia) ;
  • Ali, Borhanuddin Mohd. (Department of Computer and Communication Systems Engineering, Universiti Putra Malaysia) ;
  • Mohamad, Hafizal (Wireless Communications Cluster, MIMOS Berhad, Technology Park Malaysia) ;
  • Rasid, Mohd Fadlee A. (Department of Computer and Communication Systems Engineering, Universiti Putra Malaysia) ;
  • Ismail, Alyani (Department of Computer and Communication Systems Engineering, Universiti Putra Malaysia)
  • Received : 2013.04.08
  • Accepted : 2013.07.05
  • Published : 2013.07.31
Download PDF
⟨ Previous Next ⟩

Abstract

Over recent years, enormous amounts of research in wireless sensor networks (WSNs) have been conducted, due to its multifarious applications such as in environmental monitoring, object tracking, disaster management, manufacturing, monitoring and control. In some of WSN applications dependent the energy-efficient and link reliability are demanded. Hence, this paper presents a routing protocol that considers these two criteria. We propose a new mechanism called Reliable Routing Scheme for Energy-Balanced (RRSEB) to reduce the packets dropped during the data communications. It is based on Swarm Intelligence (SI) using the Ant Colony Optimization (ACO) method. The RRSEB is a self-adaptive method to ensure the high routing reliability in WSNs, if the failures occur due to the movement of the sensor nodes or sensor node's energy depletion. This is done by introducing a new method to create alternative paths together with the data routing obtained during the path discovery stage. The goal of this operation is to update and offer new routing information in order to construct the multiple paths resulting in an increased reliability of the sensor network. From the simulation, we have seen that the proposed method shows better results in terms of packet delivery ratio and energy efficiency.

Keywords

References

  1. R. Zurawski, Embedded Systems Handbook: Networked Embedded Systems, 2nd ed. Boca Raton, Florida: CRC Press, 2009.
  2. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "Wireless sensor networks: a survey," Computer Networks, vol. 38, pp. 393-422, 2002. https://doi.org/10.1016/S1389-1286(01)00302-4
  3. F. Xia, "QoS Challenges and Opportunities in Wireless Sensor/Actuator Networks," Sensors, vol. 8, pp. 1099-1110, 2008.
  4. N. A. Pantazis and D. D. Vergados, "A survey on power control issues in wireless sensor networks," Communications Surveys & Tutorials, IEEE, vol. 9, pp. 86-107, 2007. https://doi.org/10.1109/COMST.2007.4444752
  5. S. C. Ergen and P. Varaiya, "On multi-hop routing for energy efficiency," Communications Letters, IEEE, vol. 9, pp. 880-881, 2005. https://doi.org/10.1109/LCOMM.2005.10007
  6. X. Wang, J.-J. Ma, S. Wang, and D.-W. Bi, "Cluster-based Dynamic Energy Management for Collaborative Target Tracking in Wireless Sensor Networks," Sensors, vol. 7, pp. 1193-1215, 2007. https://doi.org/10.3390/s7071193
  7. A. El-Hoiydi and J. Decotignie, "WiseMAC: An ultra low power MAC protocol for multi-hop wireless sensor networks," Algorithmic Aspects of Wireless Sensor Networks, pp. 18-31, 2004. http://link.springer.com/chapter/10.1007%2F978-3-540-27820-7_4
  8. M. Chen, T. Kwon, S. Mao, and Y. Yuan, "Reliable and energy-efficient routing protocol in dense wireless sensor networks," Int. J. of Sensor Networks - IJSNET, vol. 4, pp. 104-117, 2008. http://www.inderscience.com/info/offer.php?id=19256 https://doi.org/10.1504/IJSNET.2008.019256
  9. C. Jae-Hwan and L. Tassiulas, "Maximum lifetime routing in wireless sensor networks," IEEE ACM T. Network., vol. 12, pp. 609-619, 2004. https://doi.org/10.1109/TNET.2004.833122
  10. E. Bonabeau, M. Dorigo, and G. Theraulaz, "Swarm intelligence: from natural to artificial systems," Oxford University Press, USA, 1999.
  11. M. Dorigo, G. D. Caro, and L. M. Gambardella, "Ant algorithms for discrete optimization," Artificial life, vol. 5, pp. 137-172, 1999. https://doi.org/10.1162/106454699568728
  12. T. Camilo, C. Carreto, J. Silva, and F. Boavida, "An Energy-Efficient Ant-Based Routing Algorithm for ireless Sensor Networks," Ant Colony Optimization and Swarm Intelligence. vol. 4150: Springer Berlin / Heidelberg, 2006, pp. 49-59. http://link.springer.com/chapter/10.1007%2F11839088_5 https://doi.org/10.1007/11839088_5
  13. G. Singh, S. Das, S. V. Gosavi, and S. Pujar, "Ant colony algorithms for Steiner trees: an application to routing in sensor networks," Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications, V. Sugumaran, Ed. Oakland University, USA, 2008, pp. 1551-1575
  14. R. GhasemAghaei, A. M. Rahman, M. A. Rahman, and W. Gueaieb, "Ant colony-based many-to-one sensory data routing in Wireless Sensor Networks," in Proc. of Computer Systems and Applications, 2008. AICCSA 2008. IEEE/ACS International Conference on, 2008, pp. 1005-1010. http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4493668&abstractAccess=no&userType=inst
  15. W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "Energy-efficient communication protocol for wireless microsensor networks," in Proc. of 33rd Annual Hawaii International Conference on System Sciences (HICSS-33), Maui, Hawaii,USA, 2000, pp. 1-10.
  16. K. Matrouk and B. Landfeldt, "RETT-gen: A globally efficient routing protocol for wireless sensor networks by equalising sensor energy and avoiding energy holes," Ad. Hoc. Netw., vol. 7, pp. 514-536, 2009. https://doi.org/10.1016/j.adhoc.2008.07.002
  17. S. Lindsey and C. S. Raghavendra, "PEGASIS: Power-efficient gathering in sensor information systems," in Proc. of IEEE Aerospace Conference, Big Sky, MT, USA, 2002, pp. 1125-1130.
  18. C.-S. Ok, S. Lee, P. Mitra, and S. Kumara, "Distributed energy balanced routing for wireless sensor networks," Comput. Ind. Eng., vol. 57, pp. 125-135, 2009. https://doi.org/10.1016/j.cie.2009.01.013
  19. K. Sohraby, D. Minoli, and T. F. Znati, Wireless sensor networks: technology, protocols, and applications: Wiley-Blackwell, 2007.
  20. A. M. Shamsan Saleh, B. Mohd Ali, M. F. A. Rasid, and A. Ismail, "A Self-Optimizing Scheme for Energy Balanced Routing in Wireless Sensor Networks Using SensorAnt," Sensors, vol. 12, pp. 11307-11333, 2012. https://doi.org/10.3390/s120811307

Cited by

  1. A Reliability-Oriented Local-Area Model for Large-Scale Wireless Sensor Networks vol.2015, pp.None, 2013, https://doi.org/10.1155/2015/923692
  2. A Quantum Ant Colony Multi-Objective Routing Algorithm in WSN and Its Application in a Manufacturing Environment vol.19, pp.15, 2013, https://doi.org/10.3390/s19153334