Artificial Bee Colony Algorithm And Its Application In Dynamic Deployment Of Wireless Sensor Networks

Artificial bee colony algorithm is one of the swarm intelligence optimization algorithm based on the study of the honey bee’s group behavior, through the individual’s local searching behavior, we finally realize the global optimization, compared with other optimization algorithms, the artificial bee colony algorithm is simple, easier to control, and has faster convergence speed and good robustness.With the development of modern computer technology, wireless communication technology and embedded technology, the wireless sensor networks were produced. The sensors that constitute the networks have many types, they can detect temperature, salinity, humidity, sound, pressure, electromagnetic phenomena, etc. and they are widely used in environmental monitoring, disaster relief, military and other fields.Although the sensors of the wireless sensor networks are of different types, they all can realize the date collection, processing, and transmission. In order to ensure the normal work of the wireless sensor networks, the seamless coverage and information communication is the networks’primary goal. Sometimes the place monitored by the networks is vast, we try to monitor the place with sensors as less as we can, namely to improve the coverage area of a single sensor node.This thesis mainly studies the application of artificial bee colony algorithm for dynamic deployment in wireless sensor networks. Firstly, we establish the mathematical model of the wireless sensor networks, and prove that when the sensors’communication radius is greater than or equal to3times of the sensors’monitoring radius, the regular hexagonal node coverage model can obtain the maximum coverage area in the two dimensional plane, also we give an accurate formula for solving the number of sensor nodes we need to cover the place of whose area is L×W. Secondly, the artificial bee colony algorithm was applied for the dynamic deployment of wireless sensor networks, in order to improve the sensor networks’coverage rate, through analysing the principle of original artificial bee colony algorithm and the optimal sensor deployment in theory, we improve the original artificial bee colony algorithm in three points:introducing the distance factor to improve the onlooker bee selection probability formula, changing the working mode of the scout bee to avoid worse coverage rate and changing the limit l for scout bee to increase the chance to get better solution. Results show that the improved artificial bee colony algorithm has faster convergent speed and higher coverage rate compared with the original artificial bee colony algorithm.