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.
Similar content being viewed by others
References
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Kim, K., & Sung, T. (2013). Cross-layered approach for (m, k)-firm stream in wireless sensor networks. Wireless Personal Communications, 68(4), 1883–1902.
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.
Mendel, J. M. (1995). Fuzzy logic systems for engineering: A tutorial. Proceedings of the IEEE, 83(3), 347–377.
Saaty, T. (2000). Fundamentals of decision making and priority theory with the analytic hierarchy process. RWS Publications.
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.
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.
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.
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.
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.
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.
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.
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.
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
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.
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.
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
Corresponding author
Ethics declarations
Conflicts of interest
The authors declare that they have no conflict of interest.
Rights and permissions
About this article
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
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11276-016-1222-2