Swipe to navigate through the articles of this issue
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
With the rapid development in ubiquitous smart sensors, wireless sensor networks have started to evolve into numerous applications including healthcare, medical, agriculture, transportation, industry, internet of things, and smart cities. However, satisfying Quality of Service (QoS) requirements of the diverse application domains remains a challenging issue due to heterogeneous traffic flows, dynamic network conditions, and resource-constrained nature of sensor nodes. In this regard, application-specific QoS provisioning techniques have received considerable research attention at the network layer. This paper presents a systematic review on the QoS mechanisms that have been employed by routing protocols and also highlights the performance issues of each mechanism. Afterwards, the survey presents a comparative analysis of computational intelligence based QoS-aware routing protocols with their strengths and limitations. Finally, this survey discusses various potential directions for future research in the field of QoS provisioning at network layer.
Please log in to get access to this content
To get access to this content you need the following product:
Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks, 52(12), 2292–2330. CrossRef
Bhandary, V., Malik, A., & Kumar, S. (2016). Routing in wireless multimedia sensor networks: A survey of existing protocols and open research issues. Journal of Engineering, 2016, 1–27. CrossRef
Mendes, L. D., & Rodrigues, J. J. (2011). A survey on cross-layer solutions for wireless sensor networks. Journal of Network and Computer Applications, 34(2), 523–534. CrossRef
Aswale, S., & Ghorpade, V. R. (2015). Survey of QoS routing protocols in wireless multimedia sensor networks. Journal of Computer Networks and Communications, 2015, 1–29. CrossRef
Hamid, Z., & Hussain, F. B. (2014). QoS in wireless multimedia sensor networks: A layered and cross-layered approach. Wireless Personal Communications, 75(1), 729–757. CrossRef
Gungor, V. C., & Hancke, G. P. (2009). Industrial wireless sensor networks: Challenges, design principles, and technical approaches. IEEE Transactions on Industrial Electronics, 56(10), 4258–4265. CrossRef
Liao, Y., Leeson, M. S., & Higgins, M. D. (2016). Flexible quality of service model for wireless body area sensor networks. Healthcare Technology Letters, 3(1), 12–15. CrossRef
Khalid, M., Ullah, Z., Ahmad, N., Arshad, M., Jan, B., Cao, Y., & Adnan, A. (2017). A survey of routing issues and associated protocols in underwater wireless sensor networks. Journal of Sensors, 2017, 1–17. CrossRef
Munir, S. A., Ren, B., Jiao, W., Wang, B., Xie, D., & Ma, J. (2007). Mobile wireless sensor network: Architecture and enabling technologies for ubiquitous computing. In 21st IEEE International conference on advanced information networking and applications workshops, AINAW’07 (Vol. 2, pp. 113–120).
Saleem, M., Di Caro, G. A., & Farooq, M. (2011). Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions. Information Sciences, 181(20), 4597–4624. CrossRef
Guo, W., & Zhang, W. (2014). A survey on intelligent routing protocols in wireless sensor networks. Journal of Network and Computer Applications, 38, 185–201. CrossRef
Kumar, J., Tripathi, S., & Tiwari, R. K. (2016). A survey on routing protocols for wireless sensor networks using swarm intelligence. International Journal of Internet Technology and Secured Transactions, 6(2), 79–102. CrossRef
Ehsan, S., & Hamdaoui, B. (2012). A survey on energy-efficient routing techniques with QoS assurances for wireless multimedia sensor networks. IEEE Communications Surveys & Tutorials, 14(2), 265–278. CrossRef
Hasan, M. Z., Al-Rizzo, H., & Al-Turjman, F. (2017). A survey on multipath routing protocols for QoS assurances in real-time wireless multimedia sensor networks. IEEE Communications Surveys & Tutorials, 19(3), 1424–1456. CrossRef
Alanazi, A., & Elleithy, K. (2015). Real-time QoS routing protocols in wireless multimedia sensor networks: Study and analysis. Sensors, 15(9), 22209–22233. CrossRef
Asif, M., Khan, S., Ahmad, R., Sohail, M., & Singh, D. (2017). Quality of service of routing protocols in wireless sensor networks: A review. IEEE Access, 5, 1846–1871. CrossRef
Bhatnagar, S., Deb, B., & Nath, B. (2001). Service differentiation in sensor networks. In Proceedings of wireless personal multimedia communications.
Afsar, M. M., & Tayarani-N, M. H. (2014). Clustering in sensor networks: A literature survey. Journal of Network and Computer Applications, 46, 198–226. CrossRef
Yetgin, H., Cheung, K. T. K., El-Hajjar, M., & Hanzo, L. H. (2017). A survey of network lifetime maximization techniques in wireless sensor networks. IEEE Communications Surveys & Tutorials, 19(2), 828–854. CrossRef
Xu, L., Collier, R., & O’Hare, G. M. (2017). A survey of clustering techniques in WSNs and consideration of the challenges of applying such to 5G IoT scenarios. IEEE Internet of Things Journal, 4(5), 1229–1249. CrossRef
Korkmaz, T., & Krunz, M. (2001). Multi-constrained optimal path selection. In IEEE INFOCOM Institute of Electrical Engineers Inc (Vol. 2, pp. 834–843).
Oyman, E. I., & Ersoy, C. (2004). Multiple sink network design problem in large scale wireless sensor networks. IEEE International Conference on Communications, 6, 3663–3667.
Nazir, B., & Hasbullah, H. (2010). Mobile sink based routing protocol (MSRP) for prolonging network lifetime in clustered wireless sensor network. In International conference on computer applications and industrial electronics (ICCAIE) (pp. 624–629).
Wang, Z. M., Basagni, S., Melachrinoudis, E., & Petrioli, C. (2005). Exploiting sink mobility for maximizing sensor networks lifetime. In Proceedings of the 38th Annual Hawaii international conference on system sciences, HICSS’05 (pp. 287a–287a).
Radi, M., Dezfouli, B., Bakar, K. A., & Lee, M. (2012). Multipath routing in wireless sensor networks: Survey and research challenges. Sensors, 12(1), 650–685. CrossRef
Kulkarni, R. V., Forster, A., & Venayagamoorthy, G. K. (2011). Computational intelligence in wireless sensor networks: A survey. IEEE Communications Surveys & Tutorials, 13(1), 68–96. CrossRef
Dorigo, M., & Di Caro, G. (1999). Ant colony optimization: A new meta-heuristic. In Proceedings of the IEEE congress on evolutionary computation- CEC99 (Vol. 2, pp. 1470–1477).
Cai, W., Jin, X., Zhang, Y., Chen, K., & Wang, R. (2006). ACO based QoS routing algorithm for wireless sensor networks. In International conference on ubiquitous intelligence and computing (pp. 419–428). Berlin: Springer.
Cobo, L., Quintero, A., & Pierre, S. (2010). Ant-based routing for wireless multimedia sensor networks using multiple QoS metrics. Computer Networks, 54(17), 2991–3010. CrossRef
Zuo, Y., Ling, Z., & Yuan, Y. (2013). A hybrid multi-path routing algorithm for industrial wireless mesh networks. EURASIP Journal on Wireless Communications and Networking, 2013(1), 82. CrossRef
Tong, M., Chen, Y., Chen, F., Wu, X., & Shou, G. (2015). An energy-efficient multipath routing algorithm based on ant colony optimization for wireless sensor networks. International Journal of Distributed Sensor Networks, 11(6), 642189. CrossRef
Malik, S. K., Dave, M., Dhurandher, S. K., Woungang, I., & Barolli, L. (2017). An ant-based QoS-aware routing protocol for heterogeneous wireless sensor networks. Soft Computing, 21(21), 6225–6236. CrossRef
Wang, J., Cao, J., Sherratt, R. S., & Park, J. H. (2017). An improved ant colony optimization-based approach with mobile sink for wireless sensor networks. The Journal of Supercomputing, 74(12), 6633–6645. CrossRef
Kennedy, J. (2011). Particle swarm optimization. In: C. Sammut & G. I. Webb (Eds.), Encyclopedia of machine learning (pp. 760–766). Boston, MA: Springer
Parsopoulos, K. E., & Vrahatis, M. N. (2002). Particle swarm optimization method in multiobjective problems. In: Proceedings of the 2002 ACM symposium on applied computing (pp. 603–607). ACM.
Liu, M., Xu, S., & Sun, S. (2012). An agent-assisted QoS-based routing algorithm for wireless sensor networks. Journal of Network and Computer Applications, 35(1), 29–36. CrossRef
Hu, Y. F., Ding, Y. S., Ren, L. H., Hao, K. R., & Han, H. (2015). An endocrine cooperative particle swarm optimization algorithm for routing recovery problem of wireless sensor networks with multiple mobile sinks. Information Sciences, 300, 100–113. CrossRef
Yang, J., Liu, F., Cao, J., & Wang, L. (2016). Discrete particle swarm optimization routing protocol for wireless sensor networks with multiple mobile sinks. Sensors, 16(7), 1081. CrossRef
Wang, J., Cao, Y., Li, B., Kim, H. J., & Lee, S. (2017). Particle swarm optimization based clustering algorithm with mobile sink for WSNs. Future Generation Computer Systems, 76, 452–457. CrossRef
Karaboga, D., Okdem, S., & Ozturk, C. (2012). Cluster based wireless sensor network routing using artificial bee colony algorithm. Wireless Networks, 18(7), 847–860. CrossRef
Ari, A. A. A., Yenke, B. O., Labraoui, N., Damakoa, I., & Gueroui, A. (2016). A power efficient cluster-based routing algorithm for wireless sensor networks: Honeybees swarm intelligence based approach. Journal of Network and Computer Applications, 69, 77–97. CrossRef
Kalyanmoy, D. (2001). Multi objective optimization using evolutionary algorithms (p. 124). New York: Wiley. MATH
Norouzi, A., & Zaim, A. H. (2014). Genetic algorithm application in optimization of wireless sensor networks. The Scientific World Journal. https://doi.org/10.1155/2014/286575.
EkbataniFard, G. H., Monsefi, R., Akbarzadeh-T, M. R., & Yaghmaee, M. H. (2010). A multi-objective genetic algorithm based approach for energy efficient QoS-routing in two-tiered wireless sensor networks. In 5th IEEE International symposium on wireless pervasive computing (ISWPC) (pp. 80–85).
Murugeswari, R., Radhakrishnan, S., & Devaraj, D. (2016). A multi-objective evolutionary algorithm based QoS routing in wireless mesh networks. Applied Soft Computing, 40, 517–525. CrossRef
Magaia, N., Horta, N., Neves, R., Pereira, P. R., & Correia, M. (2015). A multi-objective routing algorithm for wireless multimedia sensor networks. Applied Soft Computing, 30, 104–112. CrossRef
Faheem, M., Tuna, G., & Gungor, V. C. (2018). QERP: quality-of-service (QoS) aware evolutionary routing protocol for underwater wireless sensor networks. IEEE Systems Journal, 12(3), 2066–2073. CrossRef
Minhas, M. R., Gopalakrishnan, S., & Leung, V. C. (2009). Multiobjective routing for simultaneously optimizing system lifetime and source-to-sink delay in wireless sensor networks. In 29th IEEE international conference on distributed computing systems workshops (pp. 123–129).
Gaddour, O., Koubâa, A., Baccour, N., & Abid, M. (2014). OF-FL: QoS-aware fuzzy logic objective function for the RPL routing protocol. In 12th International symposium on modeling and optimization in mobile, ad hoc, and wireless networks (WiOpt) (pp. 365–372).
Revathi, T., & Muneeswaran, K. (2017). Multi-constraint multi-objective QoS aware routing heuristics for query driven sensor networks using fuzzy soft sets. Applied Soft Computing, 52, 532–548. CrossRef
Thrun, S., & Littman, M. L. (2000). Reinforcement learning: An introduction. AI Magazine, 21(1), 103.
Kaelbling, L. P., Littman, M. L., & Moore, A. W. (1996). Reinforcement learning: A survey. Journal of Artificial Intelligence Research, 4, 237–285. CrossRef
Liang, X., Balasingham, I., & Byun, S. S. (2008). A reinforcement learning based routing protocol with QoS support for biomedical sensor networks. In First international symposium on applied sciences on biomedical and communication technologies, ISABEL’08 (pp. 1–5).
Jin, Z., Ma, Y., Su, Y., Li, S., & Fu, X. (2017). A Q-learning-based delay-aware routing algorithm to extend the lifetime of underwater sensor networks. Sensors, 17(7), 1660. CrossRef
Corde, S., Chifu, V. R., Salomie, I., Chifu, E. S., & Iepure, A. (2016). Bird mating optimization method for one-to-n skill matching. In IEEE 12th International conference on intelligent computer communication and processing (ICCP) (pp. 155–162).
Faheem, M., & Gungor, V. C. (2018). Energy efficient and QoS-aware routing protocol for wireless sensor network-based smart grid applications in the context of industry 4.0. Applied Soft Computing, 68, 910–922. CrossRef
Shokouhifar, M., & Jalali, A. (2017). Optimized sugeno fuzzy clustering algorithm for wireless sensor networks. Engineering Applications of Artificial Intelligence, 60, 16–25. CrossRef
Amiri, E., Keshavarz, H., Alizadeh, M., Zamani, M., & Khodadadi, T. (2014). Energy efficient routing in wireless sensor networks based on fuzzy ant colony optimization. International Journal of Distributed Sensor Networks, 10(7), 768936. CrossRef
Tian, J., Gao, M., & Ge, G. (2016). Wireless sensor network node optimal coverage based on improved genetic algorithm and binary ant colony algorithm. Eurasip Journal on Wireless Communications and Networking, 2016(1), 104. CrossRef
Lu, J., Wang, X., Zhang, L., & Zhao, X. (2014). Fuzzy random multi-objective optimization based routing for wireless sensor networks. Soft Computing, 18(5), 981–994. CrossRef
- A survey on QoS mechanisms in WSN for computational intelligence based routing protocols
- Publication date
- Springer US
The Journal of Mobile Communication, Computation and Information
Print ISSN: 1022-0038
Electronic ISSN: 1572-8196