학술논문

Quantum inspired genetic algorithm for energy efficient clustering in wireless sensor networks
Document Type
Conference
Source
2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES) Power Electronics, Intelligent Control and Energy Systems (ICPEICES),IEEE International Conference on. :1-6 Jul, 2016
Subject
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Sensors
Analytical models
Lead
Transmitters
Wireless sensor networks
Intelligent control
Sociology
Clustering
Wireless Sensor Networks
Genetic Algorithm
Quantum Inspired Genetic Algorithm
Language
Abstract
Clustering has been one of the most commonly used strategies for maximizing the lifetime of wireless sensor networks (WSNs). Clustering in WSNs is the process of grouping the sensors based on some criteria and optimal clustering in WSNs is known to be a NP-Hard problem. Evolutionary algorithms (e.g. genetic algorithm) have been extensively utilized for addressing this problem. In this paper, energy efficient clustering problem has been dealt with using a relatively new meta-heuristic technique known as quantum inspired genetic algorithm. The simulation results and analysis clearly indicate that the proposed approach outperforms genetic algorithm based clustering technique and leads to significant increase in network lifetime.