Swarm Intelligence is a meta-heuristic methodology used to solve numerical optimization problems by simulating swarm behaviors found in nature. These techniques demonstrate the desirable properties of interpretability, scalability, effectiveness, and robustness. There is a certain similarity between bio-inspired systems and routing in networks, especially in Wireless Sensor Networks (WSNs). We are working on the design for a Swarm Intelligence (SI) based routing protocol capable of being deployed on large-scale WSNs to ensure efficient energy usage and prolonging the network lifetime.
Xinlu Li, Brian Keegan, and Fredrick Mtenzi. Energy Efficient Hybrid Routing Protocol Based on the Artificial Fish Swarm Algorithm and Ant Colony Optimization for WSNs. Sensors, 18(10):3351, October 2018.
doi:10.3390/s18103351 / pdf
Indexing: SCI, EI.
Xinlu Li, Brian Keegan, and Fredrick Mtenzi. Clustering Opportunistic Ant-Based Routing Protocol for Wireless Sensor Networks. In Proceedings of the 7th International Conference on Computer Engineering and Networks (CENet2017), July 22-23, 2017, Shanghai, China, volume 299 of Proceedings of Science (PoS).
doi:10.22323/1.299.0038 / pdf
Xinlu Li, Brian Keegan, and Fredrick Mtenzi. Ant Colony Clustering Routing Protocol for Optimization of Large-Scale Wireless Sensor Networks. In Cristina Muntean and Pramod Pathak, editors, Proceedings of the 14th Information Technology and Telecommunications Conference (IT&T'2015), October 29-30, 2015, National College of Ireland, Dublin, Ireland, pages 2–9. ISSN 1649-1246