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An improved ant colony optimization-based approach with mobile sink for wireless sensor networks

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Abstract

Traditional wireless sensor networks (WSNs) with one static sink node suffer from the well-known hot spot problem, that of sensor nodes near the static sink bear more traffic load than outlying nodes. Thus, the overall network lifetime is reduced due to the fact some nodes deplete their energy reserves much faster compared to the rest. Recently, adopting sink mobility has been considered as a good strategy to overcome the hot spot problem. Mobile sink(s) physically move within the network and communicate with selected nodes, such as cluster heads (CHs), to perform direct data collection through short-range communications that requires no routing. Finding an optimal mobility trajectory for the mobile sink is critical in order to achieve energy efficiency. Taking hints from nature, the ant colony optimization (ACO) algorithm has been seen as a good solution to finding an optimal traversal path. Whereas the traditional ACO algorithm will guide ants to take a small step to the next node using current information, over time they will deviate from the target. Likewise, a mobile sink may communicate with selected node for a relatively long time making the traditional ACO algorithm delays not suitable for high real-time WSNs applications. In this paper, we propose an improved ACO algorithm approach for WSNs that use mobile sinks by considering CH distances. In this research, the network is divided into several clusters and each cluster has one CH. While the distance between CHs is considered under the traditional ACO algorithm, the mobile sink node finds an optimal mobility trajectory to communicate with CHs under our improved ACO algorithm. Simulation results show that the proposed algorithm can significantly improve wireless sensor network performance compared to other routing algorithms.

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References

  1. Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) A survey on sensor networks. IEEE Commun Mag 40(8):102–114. doi:10.1109/MCOM.2002.1024422

    Article  Google Scholar 

  2. Heinzelman W, Chandrakasan A, Balakrishnan H (2000) Energy-efficient communication protocol for wireless micro sensor networks. In: Proceedings of the 33rd IEEE Hawaii Conference on System Sciences, pp 1–10

  3. Mottaghi S, Zahabi MR (2014) Optimizing LEACH clustering algorithm with mobile sink and rendezvous nodes. Int J Electron Commun 69(2):507–514. doi:10.1016/j.aeue.2014.10.021

    Article  Google Scholar 

  4. Nazir B, Hasbullah H (2011) Mobile sink based routing protocol (MSRP) for prolonging network lifetime in clustered wireless sensor network. In: Proceedings of the 2010 International Conference on Computer Applications and Industrial Electronics. pp 624–629

  5. Jafri MR, Javaid N, Javaid A, Ali Z (2013) Maximizing the lifetime of multi-chain PEGASIS using sink mobility. J World Appl Sci 21(9):1283–1289. doi:10.5829/idosi.wasj.2013.21.9.175

    Article  Google Scholar 

  6. Lindsey S, Raghavendra CS (2002) PEGASIS: Power efficient gathering in sensor information systems. Proc IEEE Aerosp Conf 3:1125–1130

    Google Scholar 

  7. Chu WC, Ssu KF (2014) Sink discovery in location-free and mobile-sink wireless sensor networks. Comput Netw 67(5):123–140. doi:10.1016/j.comnet.2014.03.028

    Article  Google Scholar 

  8. Sharma S, Puthal D, Jena SK et al (2016) Rendezvous based routing protocol for wireless sensor networks with mobile sink. J Supercomput 73(3):1168–1188

    Article  Google Scholar 

  9. Wang J, Cao J, Ji S et al (2017) Energy-efficient cluster-based dynamic routes adjustment approach for wireless sensor networks with mobile sinks. J Supercomput 73(7):3277–3290

    Article  Google Scholar 

  10. Chen M, Xu X, Zhang S, Feng G (2012) Energy efficient routing protocol in mobile-sink wireless sensor networks. Telkomnika Indonesian J Electr Eng 10(8):2056–2062. doi:10.11591/telkomnika.v10i8.1640

    Article  Google Scholar 

  11. Shi L, Zhang B, Mouftah HT, Ma J (2012) DDRP: An efficient data-driven routing protocol for wireless sensor networks with mobile sinks. Int J Commun Syst 26(10):1341–1355. doi:10.1002/dac.2315

    Article  Google Scholar 

  12. Wang C-F, Shih J-D, Pan B-H, Wi T-Y (2014) A network lifetime enhancement method for sink relocation and its analysis in wireless sensor networks. IEEE Sens J 14(6):1932–1943. doi:10.1109/JSEN.2014.2306429

    Article  Google Scholar 

  13. Xie S, Wang Y (2014) Construction of tree network with limited delivery latency in homogeneous wireless sensor networks. Wirel Pers Commun 78(1):231–246. doi:10.1007/s11277-014-1748-5

    Article  Google Scholar 

  14. Shen J, Tan H-W, Wang J, Wang J-W, Lee S-Y (2015) A novel routing protocol providing good transmission reliability in underwater sensor networks. J Intern Technol 16(1):171–178. doi:10.6138/JIT.2014.16.1.20131203e

    Article  Google Scholar 

  15. Zhang Y, He S, Chen J (2016) Near optimal data gathering in rechargeable sensor networks with a mobile sink. IEEE Trans Mobile Comput 16(6):1718–1729

    Article  Google Scholar 

  16. Deng R, He S, Chen J (2014) Near-optimal online algorithm for data collection by multiple sinks in wireless sensor networks. IEEE International Conference on Communications, pp 2803–2808

  17. Zhang X, Bao H, Ye J, Yan K, Zhang H (2013) A data gathering scheme for WSN/WSAN based on partitioning algorithm and mobile sinks. In: Proceedings of the IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing. pp 1968–1973

  18. Liu X, Zhao H, Yang X, Li X (2013) SinkTrail: A proactive data reporting protocol for wireless sensor networks. IEEE Trans Comput 62(1):151–162. doi:10.1109/TC.2011.207

    Article  MathSciNet  MATH  Google Scholar 

  19. Andziulis A, Dzemydienė D, Steponavičius R, Jakovlev S (2011) Comparison of two heuristic approaches for solving the production scheduling problem. Inf Technol Control 40(2):118–122. doi:10.5755/j01.itc.40.2.426

    Article  Google Scholar 

  20. Neumann F, Witt C (2010) Ant colony optimization and the minimum spanning tree problem. Theor Comput Sci 411(25):2406–2413. doi:10.1016/j.tcs.2010.02.012

    Article  MathSciNet  MATH  Google Scholar 

  21. López-Ibáñez M, Blum C (2010) Beam-ACO for the travelling salesman problem with time windows. Comput Oper Res 37(9):1570–1583. doi:10.1016/j.cor.2009.11.015

    Article  MathSciNet  MATH  Google Scholar 

  22. Wang J, Cao J, Li B, Lee S, Sherratt RS (2015) Bio-inspired ant colony optimization based clustering algorithm with mobile sinks for applications in consumer home automation networks. IEEE Trans Consum Electron 61(4):438–444. doi:10.1109/TCE.2015.7389797

    Article  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (61402234, 61672290). This work was also supported by the National Research Foundation of Korea(NRF) Grant funded by the Korea government(MSIP) (No. 2016R1A2B4011069).

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Authors and Affiliations

  1. School of Information Engineering, Yangzhou University, Yangzhou, China

    Jin Wang & Jiayi Cao

  2. Department of Biomedical Engineering, The University of Reading, Reading, UK

    R. Simon Sherratt

  3. Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, Korea

    Jong Hyuk Park

Authors
  1. Jin Wang
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  2. Jiayi Cao
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  3. R. Simon Sherratt
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  4. Jong Hyuk Park
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Correspondence to Jong Hyuk Park.

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Wang, J., Cao, J., Sherratt, R.S. et al. An improved ant colony optimization-based approach with mobile sink for wireless sensor networks. J Supercomput 74, 6633–6645 (2018). https://doi.org/10.1007/s11227-017-2115-6

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  • DOI: https://doi.org/10.1007/s11227-017-2115-6

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