Skip to main content
SpringerLink
Log in

Research on routing protocol facing to signal conflicting in link quality guaranteed WSN

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

Wireless sensor networks (WSN), as a new type of environment monitoring system, has became a hot research topic in recent years. This paper mainly focuses on the problem of signal conflicting in WSN. The link quality (quality between two neighboring nodes) can be guaranteed by the layout of network, but, the end-to-end routing quality can not be guaranteed in the same way because of random signal conflicting (even if CSMA/CA is used in WSN). The end-to-end routing will have higher performance if the routing has lower signal conflicting probability. So, the main work of this paper is designing a routing protocol to find out the routing with the lowest signal conflicting probability. This paper proposed a Minimum conflicting probability routing protocol (MCR) in link quality guaranteed WSN. Firstly, MCR combines the degree value with workload of nodes, forming a new degree and cache based routing metric (DBM). Secondly, MCR finds out the best routing by the Random Walk theory on basis of DBM. The simulation results show that, MCR protocol is more effective to avoid the signal conflicting, it has a higher end-to-end reliability and a more stable network throughput than other routing protocols in the same link quality guaranteed WSN.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Yick, J, Mukherjee, B, & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks, 52, 2292–2330.

    Article  Google Scholar 

  2. Li, M., et al. (2013). A survey on topology control in wireless sensor networks: Taxonomy, comparative study, and open issues. Proceedings of the IEEE, 101(12), 2538–2557.

    Article  Google Scholar 

  3. Yanjun, Y., et al. (2013). EDAL: An energy-efficient, delay-aware, and lifetime-balancing data collection protocol for wireless sensor networks. In MASS, pp. 182–190.

  4. Yanjun, Y., et al. (2015). EDAL: An energy-efficient, delay-aware, and lifetime-balancing data collection protocol for heterogeneous wireless sensor networks. IEEE/ACM Transactions on Networking, 23(3), 810–823.

    Article  Google Scholar 

  5. Han, K., et al. (2013). Algorithm design for data communications in duty-cycled wireless sensor networks: A survey. IEEE Communications Magazine, 51(7), 107–113.

    Article  Google Scholar 

  6. Sheng, Z., et al. (2013). A survey on the IETF protocol suite for the internet of things: Standards, challenges, and opportunities. Wireless Communications, IEEE, 20(6), 91–98.

    Article  Google Scholar 

  7. Vasilakos, A., et al. (2012). Delay tolerant networks: Protocols and applications. Boca Raton: CRC Press.

    Google Scholar 

  8. Xiao, Y., et al. (2012). Tight performance bounds of multihop fair access for MAC protocols in wireless sensor networks and underwater sensor networks. IEEE Transactions on Mobile Computing, 11(10), 1538–1554.

    Article  Google Scholar 

  9. Zeng, Y., et al. (2013). Directional routing and scheduling for green vehicular delay tolerant networks. Wireless Networks, 19(2), 161–173.

    Article  Google Scholar 

  10. Xiang, L., et al. (2011). Compressed data aggregation for energy efficient wireless sensor networks. In SECON, pp. 46–54.

  11. Chilamkurti, N., et al. (2009). Cross-layer support for energy efficient routing in wireless sensor networks. Journal of Sensors.

  12. Cheng, H., et al. (2012). Nodes organization for channel assignment with topology preservation in multi-radio wireless mesh networks. Ad Hoc Networks, 10(5), 760–773.

    Article  Google Scholar 

  13. Sengupta, S., et al. (2012). An evolutionary multiobjective sleep-scheduling scheme for differentiated coverage in wireless sensor networks. IEEE Transactions on Systems, Man, and Cybernetics, Part C, 42(6), 1093–1102.

    Article  Google Scholar 

  14. Wei, G., et al. (2011). Prediction-based data aggregation in wireless sensor networks: Combining grey model and Kalman Filter. Computer Communications, 34(6), 793–802.

    Article  Google Scholar 

  15. Chen, M., et al. (2011). Body area networks: A survey. MONET, 16(2), 171–193.

    Google Scholar 

  16. Liu, X.-Y., et al. (2014). CDC: Compressive data collection for wireless sensor networks. IEEE Transactions on Parallel & Distributed Systems. doi:10.1109/TPDS.2014.2345257.

    Google Scholar 

  17. Wang, X., et al. (2012). A survey of green mobile networks: opportunities and challenges. MONET, 17(1), 4–20.

    Google Scholar 

  18. Youssef, M., et al. (2014). Routing metrics of cognitive radio networks: A survey. IEEE Communications Surveys and Tutorials, 16(1), 92–109.

    Article  Google Scholar 

  19. Li, P., et al. (2012). CodePipe: An opportunistic feeding and routing protocol for reliable multicast with pipelined network coding. In INFOCOM, pp. 100–108.

  20. Song, Y., et al. (2014). A biology-based algorithm to minimal exposure problem of wireless sensor networks. IEEE Transactions on Network and Service Management, 11(3), 417–430.

    Article  Google Scholar 

  21. Liu, L., et al. (2015). Physarum optimization: A biology-inspired algorithm for the steiner tree problem in networks. IEEE Transactions on Computers, 64(3), 819–832.

    MathSciNet  Google Scholar 

  22. Yen, Y.-S., et al. (2011). Flooding-limited and multi-constrained QoS multicast routing based on the genetic algorithm for MANETs. Mathematical and Computer Modelling, 53(11–12), 2238–2250.

    Article  Google Scholar 

  23. Liu, Y., et al. (2010). Multi-layer clustering routing algorithm for wireless vehicular sensor networks. IET Communications, 4(7), 810–816.

    Article  Google Scholar 

  24. Busch, C., et al. (2012). Approximating congestion + dilation in networks via “quality of routing” games. IEEE Transactions on Computers, 61(9), 1270–1283.

    Article  MathSciNet  Google Scholar 

  25. Xu, X., et al. (2015). Hierarchical data aggregation using compressive sensing (HDACS) in WSNs. ACM Transactions on Sensor Networks (TOSN), 11(3), 45–60.

    Article  Google Scholar 

  26. Li, P., et al. (2014). Reliable multicast with pipelined network coding using opportunistic feeding and routing. IEEE Transactions on Parallel and Distributed Systems, 25(12), 3264–3273.

    Article  Google Scholar 

  27. Meng, T., et al. (2015). Spatial reusability-aware routing in multi-hop wireless networks. IEEE TMC,. doi:10.1109/TC.2015.2417543.

    Google Scholar 

  28. Dvir, A., et al. (2011). Backpressure-based routing protocol for DTNs. ACM SIGCOMM Computer Communication Review, 41(4), 405–406.

    MathSciNet  Google Scholar 

  29. Kassotakis, I. E., Markaki, M. E., & Vasilakos, A. V. (2000). A hybrid genetic approach for channel reuse in multiple access telecommunication networks. IEEE Journal on Selected Areas in Communications, 18(2), 234–243.

    Article  Google Scholar 

  30. Duarte, P. B. F., Fadlullah, Z Md., Vasilakos, A. V., & Kato, N. (2012). On the partially overlapped channel assignment on wireless mesh network backbone: A game theoretic approach. IEEE Journal on Selected Areas in Communications, 30(1), 119–127.

    Article  Google Scholar 

  31. Attar, A., Tang, H., Vasilakos, A. V., Yu, F. R., & Leung, V. C. M. (2012). A survey of security challenges in cognitive radio networks: Solutions and future research directions. Proceedings of the IEEE, 100(12), 3172–3186.

    Article  Google Scholar 

  32. Jiang, T., et al. (2012). QoE-driven channel allocation schemes for multimedia transmission of priority-based secondary users over cognitive radio networks. IEEE Journal on Selected Areas in Communications, 30(7), 1215–1224.

    Article  Google Scholar 

  33. Marwaha, S., et al. (2004). Evolutionary fuzzy multi-objective routing for wireless mobile ad hoc networks. In Evolutionary Computation, 2004. CEC2004. Congress on 2, 1964–1971, 2004.

  34. Vasilakos, A., et al. (2003). Optimizing QoS routing in hierarchical ATM networks using computational intelligence techniques. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 33(3), 297–312.

    Article  Google Scholar 

  35. Yan, Z., et al. (2014). A survey on trust management for Internet of Things. Journal of Network and Computer Applications, 42, 120–134.

    Article  Google Scholar 

  36. Jing, Q., et al. (2014). Security of the Internet of Things: Perspectives and challenges. Wireless Networks, 20(8), 2481–2501.

    Article  Google Scholar 

  37. Fadlullah, Z Md, et al. (2010). DTRAB: Combating against attacks on encrypted protocols through traffic-feature analysis. IEEE/ACM Transactions on Networking (TON), 18(4), 1234–1247.

    Article  Google Scholar 

  38. Reza Rahimi, M., et al. (2012). MAPCloud: Mobile applications on an elastic and scalable 2-tier cloud architecture. In IEEE/ACM UCC 2012, pp. 83–90.

  39. Jiang, Y. Q., Li, T., Zhang, M., et al. (2015). WSN-based control system of Co-2 concentration in greenhouse. Intelligent Automation and Soft Computing, 21(3), 285–294.

    Article  Google Scholar 

  40. Akylidiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). A survey on sensor networks. IEEE Personality Communications Magazine, 40(8), 102–114.

    Article  Google Scholar 

  41. Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless micro sensor networks. IEEE Transactions on Wireless Communications, 1(4), 660–670.

    Article  Google Scholar 

  42. AL-khdour, T., & Baroudi, U. (2010). An energy-efficient distributed schedule-based communication protocol for wireless sensor networks. Arabian Journal for Science and Engineering, 35(2B), 153–168.

    MathSciNet  Google Scholar 

  43. Perumal, P. S., Uthariaraj, V. R., & Christo, V. R. E. (2015). WSN lifetime analysis: Intelligent UAV and arc selection algorithm for energy conservation in isolated wireless sensor networks. KSII Transactions on Internet and Information Systems, 9(3), 901–920.

    Google Scholar 

  44. Badia-Melis, R., Ruiz-Garcia, L., & Garcia-hierro, J. (2015). Refrigerated fruit storage monitoring combining two different wireless sensing technologies: RFID and WSN. Sensors, 15(3), 4781–4795.

    Article  Google Scholar 

  45. Dima, S. M., Panagiotou, C., & Tsitsipis, D. (2014). Performance evaluation of a WSN system for distributed event detection using fuzzy logic. Ad Hoc Networks, 23, 87–108.

    Article  Google Scholar 

  46. Busson, A., & Chelius, G. (2014). Capacity and interference modeling of CSMA/CA networks using SSI point processes. Telecommunication Systems, 57(1), 25–39.

    Article  Google Scholar 

  47. Bai, R., & Singhal, M. (2006). DOA: DSR over AODV routing for mobile ad hoc networks. IEEE Transactions on Mobile Computing, 5(10), 1403–1416.

    Article  Google Scholar 

  48. Jain, J., Gupta, R., & Bandhopadhyay, T. K. (2014). Scalability enhancement of AODV using local link repairing. International Journal of Electronics, 101(9), 1230–1243.

    Article  Google Scholar 

  49. Yadav, A., Singh, Y. N., & Singh, R. R. (2015). Improving routing performance in AODV with link prediction in mobile adhoc network. Wireless Personal Communications, 83(1), 603–618.

    Article  MathSciNet  Google Scholar 

  50. Liu, T., Liu, K. (2007). Improvements on DSDV in mobile ad hoc networks. In Proceedings of 3rd international conference on wireless communications, networking and mobile computing (WiCOM 2007), Shanghai, China, pp. 1637–1640.

  51. Xie, P., Cui, J.-H., & Lao, L. (2005). VBF: Vector-based forwarding protocol for underwater sensor networks. In Proceedings of IFIP (Networking’06), Coimbra, Portugal, May 2006. A longer version is available as UCONN CSE Technical Report: UbiNet-TR05-03, February 2005.

  52. Das, B. K., & Lindsay, J. M. (2015). Quantum random walk approximation in banach algebra. Journal of Mathematical Analysis and Applications, 430(1), 465–482.

    Article  MathSciNet  MATH  Google Scholar 

  53. Gao, F. (2015). Laws of iterated logarithm for transient random walks in random environments. Frontiers of Mathematics in China, 10(4), 857–874.

    Article  MathSciNet  MATH  Google Scholar 

  54. Devroye, L., Lugosi, G., & Neu, G. (2015). Random-walk perturbations for online combinatorial optimization. IEEE Transactions on Information Theory, 61(7), 4099–4106.

    Article  MathSciNet  Google Scholar 

  55. Naimi, S., Busson, A., & Veque, V. (2014). Anticipation of ETX metric to manage mobility in ad hoc wireless networks. In 13th international conference on ad-hoc networks and wireless. Benidorm, Spain, 2014, 8487:29–42.

  56. Wang, Y., Jin, Z. G., & Su, Y. S. (2014). Simulator-to-emulator: analysis and design of experiment platform for underwater sensor networks. Applied Mechanics and Materials, 473, 219–225.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Information Science and Engineering, Northeastern University, Shenyang, 110819, China

    Jian Zhu, Jun Liu, Zhao Hai & Bi Yuan-Guo

Authors
  1. Jian Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jun Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhao Hai
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Bi Yuan-Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jian Zhu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhu, J., Liu, J., Hai, Z. et al. Research on routing protocol facing to signal conflicting in link quality guaranteed WSN. Wireless Netw 22, 1739–1750 (2016). https://doi.org/10.1007/s11276-015-1053-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-015-1053-6

Keywords

Search

Navigation