| Paper title: |
An energy efficient scheme for data gathering in wireless sensor networks using particle swarm optimization |
| Published in: | Issue 2, (Vol. 3) / 2009 |
| Publishing date: | 2009-10-20 |
| Pages: | 10-13 |
| Author(s): | Chakraborty Ayon, Chakraborty Kaushik, Mitra Swarup Kumar, Naskar K. Mrinal |
| Abstract. | Energy efficiency of sensor nodes is a sizzling issue, given the severe resource constraints of sensor nodes and pervasive nature of sensor networks. The base station being located at variable distances from the nodes in the sensor field, each node actually dissipates a different amount of energy to transmit data to the same. The LEACH [4] and PEGASIS [5] protocols provide elegant solutions to this problem, but may not always result in optimal performance. In this paper we have proposed a novel data gathering protocol for enhancing the network lifetime by optimizing energy dissipation in the nodes. To achieve our design objective we have applied particle swarm optimization (PSO) with Simulated Annealing (SA) to form a sub-optimal data gathering chain and devised a method for selecting an efficient leader for communicating to the base station. In our scheme each node only communicates with a close neighbor and takes turns in being the leader depending on its residual energy and location. This helps to rule out the unequal energy dissipation by the individual nodes of the network and results in superior performance as compared to LEACH and PEGASIS. Extensive computer simulations have been carried out which shows that significant improvement is over these schemes. |
| Keywords: | Wireless Sensor Network, Data Gathering Cycle, Greedy Algorithm, Swarm Intelligence, Simulated Annealing, Network Lifetime. |
| References: | 1. Clare, Pottie, and Agre, “Self-Organizing Distributed Sensor Networks”,In SPIE Conference on Unattended Ground Sensor Technologies and Applications, pages 229–237, Apr. 1999. 2. Yunxia Chen and Qing Zhao, “On the Lifetime of Wireless Sensor Networks”, Communications Letters, IEEE, Volume 9, Issue 11, pp:976–978, DigitalObjectIdentifier 10.1109/ LCOMM. 2005.11010., Nov. 2005. 3. S. Lindsey, C. S. Raghavendra and K. Sivalingam, “Data Gathering in Sensor Networks using energy*delay metric”, In Proceedings of the 15th International Parallel and Distributed Processing Symposium, pp 188-200, 2001. 4. W. Heinzelman, A. Chandrakasan, H. Balakrishnan, “EnergyEfficient Communication Protocol for Wireless Microsensor Networks”, IEEE Proc. Of the Hawaii International Conf. on System Sciences, pp. 1-10,January 2000 5. S. Lindsey, C.S. Raghavendra, “PEGASIS: Power Efficient Gathering in Sensor Information Systems”, In Proceedings of IEEE ICC 2001, pp. 1125-1130, June 2001. 6. Eberhart, R. C, Kennedy, J. “A new optimizer using particle swarm theory”, 1995 . 7. Kirkpatrick S, “Simulated Annealing“ , Sci, Vol 220, 1983. 8. N. Metropolis et. al. J. Chem. Phys. 21. 1087 (1953). 9. Zhi-Feng Hao, Zhi-Gang Wang; Han Huang, “A Particle Swarm Optimization Algorithm with Crossover Operator”, International Conference on Machine Learning and Cybernetics 2007, pp -19- 22, Aug. 2007. 10. Ayan Acharya, Anand Seetharam, Abhishek Bhattacharyya, Mrinal Kanti Naskar, “Balancing Energy Dissipation in Data Gathering Wireless Sensor Networks Using Ant Colony optimization” ,10th International Conference on Distributed Computing and Networking-ICDCN 2009, pp437-443, January 3-6, 2009 |
| Back to the journal content | |
