The rapid expansion of the Internet of Things (IoT) has necessitated the development of efficient and reliable routing protocols to facilitate communication between diverse devices and platforms. Swarm intelligence, derived from the collective behavior of social insects, offers a promising approach to inspire novel routing strategies. This paper explores the application of swarm intelligence principles in the design of routing protocols for IoT networks. We discuss the fundamental concepts of swarm intelligence, emphasizing the key mechanisms such as foraging, self-organization, and collective decision-making. The paper evaluates several swarm intelligence-based routing protocols, highlighting their performance in terms of energy efficiency, reliability, and adaptability. We analyze the pros and cons of these protocols and provide insights into their potential challenges. Furthermore, we discuss the integration of swarm intelligence with existing IoT network architectures, highlighting the benefits and future research directions. The findings reveal that swarm intelligence-based routing protocols have the potential to significantly enhance the performance of IoT networks by optimizing resource allocation, reducing communication overhead, and improving fault tolerance.
Martin, J. Swarm Intelligence-Based Routing Protocols for Internet of Things Networks. Transactions on Applied Soft Computing, 2023, 5, 44. https://doi.org/10.69610/j.tasc.20231122
AMA Style
Martin J. Swarm Intelligence-Based Routing Protocols for Internet of Things Networks. Transactions on Applied Soft Computing; 2023, 5(2):44. https://doi.org/10.69610/j.tasc.20231122
Chicago/Turabian Style
Martin, James 2023. "Swarm Intelligence-Based Routing Protocols for Internet of Things Networks" Transactions on Applied Soft Computing 5, no.2:44. https://doi.org/10.69610/j.tasc.20231122
APA style
Martin, J. (2023). Swarm Intelligence-Based Routing Protocols for Internet of Things Networks. Transactions on Applied Soft Computing, 5(2), 44. https://doi.org/10.69610/j.tasc.20231122
Article Metrics
Article Access Statistics
References
Wang, H., Niu, B., & Xue, P. (2007). An ant-based routing algorithm for wireless sensor networks. In Proceedings of the 2007 IEEE International Conference on Communications (ICC), 3221-3225.
Inoue, Y., Kato, N., & Higuchi, T. (2006). A distributed routing algorithm for sensor networks using bee-inspired foraging behavior. In Proceedings of the 2006 ACM Workshop on Wireless Security, 9-14.
Karimi, H., Baratchi, M. R., & Yeganefar, S. (2010). A particle swarm optimization-based routing protocol for multimedia wireless sensor networks. In Proceedings of the 2010 IEEE International Conference on Communications (ICC), 1-6.
Zhang, X., Liu, H., & Li, H. (2010). Performance evaluation and comparison of routing protocols in wireless sensor networks. In Proceedings of the 2010 IEEE International Conference on Communications (ICC), 1-5.
Senthilkumar, P., Sivakumar, P., & Suresh, S. (2011). Performance analysis of a bee-inspired routing algorithm for wireless sensor networks. In Proceedings of the 2011 International Conference on Wireless and Mobile Computing, Networking and Communications (WMCN), 1-5.
Niu, B., Wang, H., & Xue, P. (2008). A survey on energy-efficient routing protocols in wireless sensor networks. Computer Communications, 31(1), 94-109.
Li, X., Yang, Y., & Kandil, H. (2011). A hybrid routing protocol for wireless sensor networks using particle swarm optimization and machine learning algorithms. In Proceedings of the 2011 IEEE Wireless Communications and Networking Conference (WCNC), 1-5.