Skip to main content
SpringerLink
Log in

Real-time routing protocols for (m,k)-firm streams based on multi-criteria in wireless sensor networks

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

Even though some velocity based routing protocols for (m,k)-firm stream have been recently proposed in multimedia wireless sensor networks, there are still many perspective parameters to be considered for forwarding procedure. Moreover, since they are not correlated with each other, multi-criteria system for forwarding is desirable to select next hop. However, current existing protocols apply these parameters sequentially without any prioritization. To address this issue, in this paper, we propose two (m,k)-firm specific routing protocols based on fuzzy interference system and analytical hierarchical process in conjunction with the gray relational analysis. In each protocol, delivery ratio, energy, speed, (m,k)-firm stream requirement as well as current stream status are used to select the best appropriate next hop while considering given node’s constraints. Through the simulation results, we demonstrate that the proposed scheme gracefully maintains (m,k)-firm requirement while extending the network lifetime. Finally, superiority of the proposed approach to existing velocity based routing protocols is also proven through diverse simulation scenarios.

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
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Teixeira, T., Culurciello, E., Park, J. H., Lymberopoulos, D., Barton-Sweeney, A., & Savvides, A. (2006). Address-event imagers for sensor networks: Evaluation and modeling. In Proceedings of the international conference on information processing in sensor networks, pp. 458–466. ACM.

  2. Han, K., Liu, Y., & Vasilakos, A. V. (2013). Algorithm design for data communications in duty-cycled wireless sensor networks: A survey. IEEE Communications Magazine, 51(7), 107–113.

    Article  Google Scholar 

  3. Yao, Y., Cao, Q., & Vasilakos, A. V. (2015). Edal: An energy-efficient, delay-aware, and lifetime-balancing data collection protocol for heterogeneous wireless sensor networks. IEEE/ACM Transactions on Networking, 23(6), 810–823.

    Article  Google Scholar 

  4. Chilamkurti, N., Zeadally, S., Vasilakos, A., & Sharma, V. (2009). Cross-layer support for energy efficient routing in wireless sensor networks. Journal of Sensors, 2009, 1–9.

    Article  Google Scholar 

  5. Zeng, Y., Xiang, K., Li, D., & Vasilakos, A. V. (2013). Directional routing and scheduling for green vehicular delay tolerant networks. Wireless Networks, 19(2), 161–173.

    Article  Google Scholar 

  6. Xu, X., Ansari, R., Khokhar, A., & Vasilakos, A. V. (2015). Hierarchical data aggregation using compressive sensing (HDACS) in WSNs. ACM Transactions on Sensor Networks, 11(3), Article No. 45. doi:10.1145/2700264.

  7. Liu, X., Zhu, Y., Kong, L., Liu, C., Vasilakos, A. V., & Wu, M. (2015). Cdc: Compressive data collection for wireless sensor networks. IEEE Transactions on Parallel & Distributed Systems, 26(8), 2188–2197.

    Article  Google Scholar 

  8. Xiang, L., Leo, J., & Vasilakos, A. V. (2011). Compressed data aggregation for energy efficient wireless sensor networks. In Proceedings of IEEE international conference on sensor, mesh and ad hoc communications and networks, pp. 46–54. IEEE.

  9. Li, M., Li, Z., & Vasilakos, A. V. (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 

  10. Busch, C., Kannan, R., & Vasilakos, A. V. (2012). Approximating congestion + dilation in networks via “quality of routing” games. IEEE Transactions on Computers, 61(9), 1270–1283.

    Article  MathSciNet  Google Scholar 

  11. Yen, Y., Chao, H., Chang, R., & Vasilakos, A. V. (2011). Flooding-limited and multi-constrained qos multicast routing based on the genetic algorithm for manets. Mathematical and Computer Modeling, 53(11), 2238–2250.

    Article  Google Scholar 

  12. Liu, L., Song, Y., Zhang, H., Ma, H., & Vasilakos, A. V. (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 

  13. Song, Y., Liu, L., Ma, H., & Vasilakos, A. V. (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 

  14. Sengupta, S., Nasir, M., & Vasilakos, A. V. (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 

  15. Acampora, G., Gaeta, M., Loia, V., & Vasilakos, A. V. (2010). Interoperable and adaptive fuzzy services for ambient intelligence applications. ACM Transactions on Autonomous and Adaptive Systems, 5(2), 1–26.

    Article  Google Scholar 

  16. He, T., Stankovic, J. A., Lu, C., & Abdelzaher, T. (2003). Speed: A stateless protocol for real-time communication in sensor networks. In Proceedings of international conference on distributed computing systems, pp. 46–55. IEEE.

  17. Felemban, E., Lee, C. G., & Ekici, E. (2006). Mmspeed: Multipath multi-speed protocol for qos guarantee of reliability and timeliness in wireless sensor networks. IEEE Transactions on Mobile Computing, 5(6), 738–754.

    Article  Google Scholar 

  18. Zhao, L., Kan, B., Xu, Y., & Li, X. (2007). Ft-speed: A fault-tolerant, real-time routing protocol for wireless sensor networks. In Proceedings of international conference on wireless communications, networking and mobile computing, pp. 2531–2534. IEEE.

  19. Al-Jarrah, O., Salhieh, A., & Qaroush, A. (2010). Real-time power-aware routing protocol for wireless sensor network. In Proceedings of international conference on information systems, technology and management, pp. 156–166. Berlin: Springer.

  20. Kim, J., & Ravindran, B. (2009). Opportunistic real-time routing in multi-hop wireless sensor networks. In Proceedings of the ACM symposium on applied computing, pp. 2197–2201. ACM.

  21. Yaeghoobi, K. S. B., Tyagi, S. S., Soni, M. K., Mahdi, O., & Ebadati, E. (2014). Saerp: An energy efficiency real-time routing protocol in wsns. In Proceedings of 2014 international conference on optimization, reliability, and information technology, pp. 249–254. IEEE.

  22. Yuanyuan, Z., Sreenan, C. J., & Sitanayah, L. (2010). A real-time and robust routing protocol for building fire emergency applications using wireless sensor networks. In Proceedings of IEEE international conference on pervasive computing and communications workshops, pp. 358–363. IEEE.

  23. Xu, Y., Ren, F., He, T., Lin, C., Chen, C., & Das, S. K. (2013). Real-time routing in wireless sensor networks: A potential field approach. ACM Transactions on Sensor Networks, 9(3), 1–24.

    Article  Google Scholar 

  24. Rachamalla, S., & Kancharla, A. S. (2013). A survey of real-time routing protocols for wireless sensor networks. International Journal of Computer Science & Engineering Survey, 4(3), 35–44.

    Article  Google Scholar 

  25. Kim, K., & Sung, T. (2010). Network layer approaches for (m, k)-firm stream in wireless sensor networks. IEICE Transactions on Communications, E93-B(11), 3165–3168.

  26. Li, B., & Kim, K. (2012). A novel routing protocol for (m, k)-firm-based real-time streams in wireless sensor networks. In Proceedings of IEEE wireless communications and networking conference, pp. 1715–1719. IEEE, 2012.

  27. Li, B., & Kim, K. (2012). An (m, k)-firm real-time aware fault-tolerant mechanism in wireless sensor networks. International Journal of Distributed Sensor Networks, 2012, 1–24.

    Google Scholar 

  28. Li, J., & Kim, K. (2013). A real-time routing protocol for (m, k)-firm streams in wireless sensor networks. In Proceedings of IEEE international conference on intelligent sensors, sensor networks and information processing. IEEE.

  29. Li, J., & Kim, K. (2014). A novel routing protocol for (m, k)-firm-based real-time streams in wireless sensor networks. Wireless Networks, 20, 719–731.

    Article  Google Scholar 

  30. Kim, K., & Sung, T. (2013). Cross-layered approach for (m, k)-firm stream in wireless sensor networks. Wireless Personal Communications, 68(4), 1883–1902.

    Article  Google Scholar 

  31. Kim, K., & Sung, T. (2015). Modeling and routing scheme for (m, k)-firm streams in wireless multimedia sensor networks. Wireless Communications and Mobile Computing, 15(3), 475–483.

    Article  Google Scholar 

  32. Mendel, J. M. (1995). Fuzzy logic systems for engineering: A tutorial. Proceedings of the IEEE, 83(3), 347–377.

    Article  Google Scholar 

  33. Saaty, T. (2000). Fundamentals of decision making and priority theory with the analytic hierarchy process. RWS Publications.

  34. Chan, J., & Tong, T. (2007). Multi-criteria material selections and end-of-life product strategy: Grey relational analysis approach. Material & Design, 28(5), 1539–1546.

    Article  Google Scholar 

  35. Amri, S., Kaddachi, M. L., & Trad, A. (2014). Energy-efficient multi-hop hierarchical routing protocol using fuzzy logic (emhr-fl) for wireless sensor networks. In World congress on computer applications and information systems, pp. 1–6. IEEE.

  36. Arabi, Z. (2010). Herf: A hybrid energy efficient routing using a fuzzy method in wireless sensor networks. In International Conference on Intelligent and Advanced Systems (ICIAS), pp. 1–6. IEEE.

  37. Jaradat, T., Benhaddou, D., Balakrishnan, M., & Al-Fuqaha, A. (2013). Energy efficient cross-layer routing protocol in wireless sensor networks based on fuzzy logic. In International conference on wireless communications and mobile computing conference, pp. 177–182. IEEE.

  38. AlShawi, I. S., Lianshan, Y., Wei, P., & Bin, L. (2012). A fuzzy-gossip routing protocol for an energy efficient wireless sensor networks. In IEEE sensors, pp. 1–4. IEEE.

  39. Azim, M. A., Kibria, M. R., & Jamalipour, A. (2008). Designing an application-aware routing protocol for wireless sensor networks. In IEEE global telecommunications conference, pp. 1–4. IEEE.

  40. Lohani, D., & Varma, S. (2013). Itinerary planning using grey relational analysis for mobile agent based wireless sensor networks. In International conference on contemporary computing, pp. 29–34. IEEE.

  41. Wu, X., Cho, J., d’Auriol, B., & Lee, S. (2007). Energy-aware routing for wireless sensor networks by ahp. Lecture Notes in Computer Science, 4761, 446–455.

    Article  Google Scholar 

  42. Min, W., & Shining, L. (2010). An energy-efficient load-balanceable multipath routing algorithm based on ahp for wireless sensor networks. In IEEE international conference on intelligent computing and intelligent systems, pp. 251–256. IEEE

  43. Hamdaoui, M., & Ramanathan, P. (1995). A dynamic priority assignment technique for streams with (m, k)-firm deadlines. IEEE Transactions on Computers, 44(12), 1443–1451.

    Article  MATH  Google Scholar 

  44. Joe, H., Lee, J., Woo, D., & Kim, H. (2009). Demo abstract: A high-fidelity sensor network simulator using accurate cc2420 model. In International conference on information processing in sensor networks. IEEE.

Download references

Acknowledgments

This work was supported by Basic Science Research Program (2015R1D1A1A01056979) and BK21 Plus Program (Research Team for Software Platform on Unmanned Aerial Vehicle, 21A20131600012) through the National Research Foundation of Korea (NRF) funded by the Ministry of Education. Also, it was supported by Research Incentive Fund (RIF) by Zayed University, Abu Dhabi, UAE.

Author information

Authors and Affiliations

  1. Department of Informatics, Engineering Research Institute, Gyeongsang National University, Jinju, Gyeongnam, 52828, Korea

    Mohammad Abdul Azim, Beom-Su Kim & Ki-Il Kim

  2. College of Technological Innovation, Zayed University, Abu Dhabi, United Arab Emirates

    Babar Shah

Authors
  1. Mohammad Abdul Azim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Beom-Su Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Babar Shah
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ki-Il Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ki-Il Kim.

Ethics declarations

Conflicts of interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Azim, M.A., Kim, BS., Shah, B. et al. Real-time routing protocols for (m,k)-firm streams based on multi-criteria in wireless sensor networks. Wireless Netw 23, 1233–1248 (2017). https://doi.org/10.1007/s11276-016-1222-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-016-1222-2

Keywords

Search

Navigation