A Strategy Of Dynamic Update Bluetooth Scatternet Based On Improved Ant Colony Algorithm

Ant colony algorithm and Tabu algorithm are artificial intelligence algorithm, which were summarized by human being from natural phenomenon. But slow convergence speed and easily fall into local optimal solution are two big problems of Ant colony algorithm. In order to solve these problems, scholars put forward solutions, such as Elite strategy of ant colony algorithm, and the MMAS (MAX-MIN Ant System) algorithm. Tabu search algorithm is a heuristic search algorithm is used to jump out of the local optimal solution algorithm.In this thesis, it uses the tabu search table to store the optimal path of each road, and the information on the table of the better path to control the concentration. Experimental results show that the improved algorithm can effectively improve the performance of the algorithm.Bluetooth technology is a free wireless access technology. People can use Bluetooth for data communication anytime, anywhere. From 1994, Bluetooth protocol has 20 years history.The Bluetooth protocol are constantly refined and improved, but up to now, it has not defined how to organize bluetooth scatternet. Bluetooth protocol just defines how to communicate among piconet.This thesis provides a new method to organize bluetooth scatternet. This method combines ant colony algorithm and bluetooth scatternet organically. For bluetooth scatternet has been set up, if no nodes increase and decrease, bluetooth scatternet is basically stable and unchanged. The method of organize bluetooth scatternet in this thesis, can organizes bluetooth scatternet quickly. It uses the thought of pheromones in the ant colony algorithm to monitor the state of the network, and then adjusts the bluetooth scattergun dynamically. This thesis regards master nodes and bridge nodes in bluetooth scatternet as their pheromones, as long as the packet is forwarded through the master nodes and bridge nodes, the pheromone of the nodes will be deepened. It uses the pheromone of the master nodes and bridge nodes to judge the network topology, and the network which need to be adjusted, it will be adjusted. It will adjust the higher and lower nodes to achieve a relatively balanced load relative to the entire network and reach to a state of equilibrium.