Optimization of Wireless Sensor Networks Using the ANT COLONY OPTIMIZATION

This paper proposes an ant colony optimization-based routing algorithm for wireless sensor networks. The algorithm incorporates link quality into pheromone formation and supports multiple routes, which are characteristics of an ant colony algorithm. When routing is chosen, the probability of the node being chosen as the next hop is calculated based on the pheromone concentration on the route. Because ant colony optimization is self-organizing, dynamic, and multi-path, it is ideal for wireless sensor network routing. This algorithm has a low routing cost, good self-adaptation, and can handle multiple paths. It has the ability to balance the network's energy consumption and extend the network's survival time. The thesis performs a comparative analysis of the simulation experiment and experimental results, demonstrating that the ant colony algorithm can find the optimal routing in a wireless sensor network and achieves the design goal of a wireless sensor network routing algorithm.