Abstract
In a Wireless Sensor Network (WSN), due to energy constraints and remote deployment in harsh environment, centralized routing is difficult. In a WSN, if more sensors are active better paths are available. But it causes more energy consumption. Conventional shortest path routing causes repeated use of some nodes which causes power failure of those nodes and the routing holes pop up. In our research, we propose an efficient collaborative routing on the improvisation of ant colony meta-heuristics. We construct the best possible routing by building load balanced virtual circuits dynamically. We consider on-demand load condition to the network and span virtual circuits between source-destination pairs using collaborative ants. To validate our method we do experiments, and we also compare our method to a relevant agent based routing technique for WSNs. We find that, our method works better.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Amiri, E., Keshavaraz, H., Alizadeh, M., Zamani, M., Khodadadi, T.: Energy efficient routing in Wireless Sensor Networks based on fuzzy ant colony optimization. Int. J. Distrib. Sens. Netw. 2014, 1–17 (2014). Hindawi
Intanagonwiwat, C., Govindan, R., Balakrisnan, D.: Directed diffusion: a scalable and robust communication paradigm for sensor networks. In: Proceedings of ACM Mobicom, MA, USA, pp. 56–57 (2000)
Bonabeau, E., Dorigo, M.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York (1999)
Braginsky, D., Estrin, D.: Rumour routing algorithm for sensor networks. In: Proceedings of the Workshop on Sensor Networks and Applications (WSNA), GA, USA (2002)
Camilo, T., Carreto, C., Silva, J.S., Boavida, F.: An energy-efficient ant-based routing algorithm for Wireless Sensor Networks. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds.) ANTS 2006. LNCS, vol. 4150, pp. 49–59. Springer, Heidelberg (2006)
Ding, P.N., Liu, X.: Data gathering communication in wireless sensor networks using ant colony optimization. In: Proceedings of IEEE International Conference on Robotics and Biomimetics (ROBIO) (2004)
Doerner, K., Gutjahr, W.-J., Hartl, R.F., Strauss, C., Stummer, C.: Pareto ant colony optimization: a meta-heuristic approach to multiobjective portfolio selection. Ann. Oper. Res. 131, 79–99 (2004). Springer-Verlag
Dorigo, M., Stutzle, T.: Ant Colony Optimization. MIT Press, Cambridge (2004)
Okedem, S., Karaboga, D.: Routing in Wireless Sensor Networks using an Ant Colony Optimization (ACO) router chip. Sensors 9(1), 909–921 (2009). MDPI, Switzerland
Pei, Z., Deng, Z., Yang, B., Cheng, X.: Application-oriented Wireless Sensor Network communication protocols and hardware platforms: a survey. In: Proceedings of IEEE International Conference on Industrial Technology, pp. 1–6 (2008)
Saleem, M., Khayam, S.A., Farooq, M.: A Formal performance modelling framework for bio-inspired ad-hoc routing protocols. In: Proceedings of the Annual Conference on Genetic and Evolutionary Computation (GECCO), GA, USA, pp. 103–110 (2008)
Stojmenovic, I.: The Handbook of Sensor Networks: Algorithms and Architectures. Wiley, Hoboken (2005)
Zhu, X.: Pheromone based energy aware directed diffusion algorithm for Wireless Sensor Network. In: Huang, D.-S., Heutte, L., Loog, M. (eds.) ICIC 2007. LNCS, vol. 4681, pp. 283–291. Springer, Heidelberg (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Rahman, M.S., Naznin, M., Ahamed, T. (2016). Efficient Routing in a Sensor Network Using Collaborative Ants. In: Tan, Y., Shi, Y., Li, L. (eds) Advances in Swarm Intelligence. ICSI 2016. Lecture Notes in Computer Science(), vol 9713. Springer, Cham. https://doi.org/10.1007/978-3-319-41009-8_36
Download citation
DOI: https://doi.org/10.1007/978-3-319-41009-8_36
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-41008-1
Online ISBN: 978-3-319-41009-8
eBook Packages: Computer ScienceComputer Science (R0)