Agent-based Framework for Energy Efficiency in Wireless Sensor Networks

Wireless sensor networks are consisted of hundreds or thousands of small sensors that have limited resources. Energy-efficient techniques are the main issue of wireless sensor networks. This paper proposes an energy efficient agent-based framework in wireless sensor networks. We adopt biologically inspired approaches for wireless sensor networks. Agent operates automatically with their behavior policies as a gene. Agent aggregates other agents to reduce communication and gives high priority to nodes that have enough energy to communicate. Agent behavior policies are optimized by genetic operation at the base station. Simulation results show that our proposed framework increases the lifetime of each node. Each agent selects a next-hop node with neighbor information and behavior policies. Our proposed framework provides self-healing, self-configuration, self-optimization properties to sensor nodes. Keywords—Agent, Energy Efficiency, Genetic algorithm, Wireless Sensor Networks.

[1]  Hongliang Ren,et al.  Biologically Inspired Approaches for Wireless Sensor Networks , 2006, 2006 International Conference on Mechatronics and Automation.

[2]  Mark T. Keane,et al.  An Energy-Efficient, Multi-Agent Sensor Network for Detecting Diffuse Events , 2007, IJCAI.

[3]  Victor C. M. Leung,et al.  Mobile Agent Based Wireless Sensor Networks , 2006, J. Comput..

[4]  Junichi Suzuki,et al.  MONSOON: A Coevolutionary Multiobjective Adaptation Framework for Dynamic Wireless Sensor Networks , 2008, Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008).

[5]  Matt Welsh,et al.  Decentralized, adaptive resource allocation for sensor networks , 2005, NSDI.

[6]  A. S. Thoke,et al.  International Journal of Electrical and Computer Engineering 3:16 2008 Fault Classification of Double Circuit Transmission Line Using Artificial Neural Network , 2022 .

[7]  Junichi Suzuki,et al.  BiSNET: A biologically-inspired middleware architecture for self-managing wireless sensor networks , 2007, Comput. Networks.

[8]  J. Suzuki,et al.  Exploring self-star properties in cognitive sensor networking , 2008, 2008 International Symposium on Performance Evaluation of Computer and Telecommunication Systems.

[9]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[10]  David L. Hall,et al.  Customer-Driven Sensor Management , 2006, IEEE Intelligent Systems.

[11]  Chenyang Lu,et al.  Rapid Development and Flexible Deployment of Adaptive Wireless Sensor Network Applications , 2005, 25th IEEE International Conference on Distributed Computing Systems (ICDCS'05).