Hybrid Genetic Ant Colony Algorithm In Ad-hoc Network

With the development of wireless communication technology, multimedia business such as video on demand and video conference based on wireless Ad Hoc networks have got applied. Ad Hoc networks are required to provide Quality of Service(QoS) guarantee to some service in communication such as the metric, bandwidth, delay. However, due to the dynamic topology of Ad Hoc networks, solving QoS in Ad Hoc networks is a difficult and challenging subject.In Ad Hoc networks the QoS routing problem is a mult-constrained NP problem. The traditional routing algorithm is hard to solve. So, in this paper, the genetic algorithm and ant colony algorithm are presented for solving QoS routing problem in Ad Hoc networks. Based on the idea of traveling, an initial population is presented in the genetic algorithm. This may reduce complexity and improve the efficiency of the algorithm. In the ant colony algorithm, the punitive idea is presented for updating global pheromone, which could effectively improve the rate of the algorithm convergence and avoid being influenced by the algorithm parameters. The simulation results demonstrate that the performances of two algorithms are superior to the traditional QoS routing algorithm in Ad Hoc networks.Ant colony algorithm has good feedback capacity. Genetic algorithm has the ability of doing a global search quickly. The combination of both the algorithms can make full use of each advantage. Firstly, it adopts genetic algorithm to generate preliminary partitioning results. Secondly, it converts them into initial pheromone distribution for ant algorithm. Last, it makes use of the ant colony algorithm to search for optimal partitioning scheme. The algorithm utilizes the advantages of the two algorithms and overcomes their disadvantages. The simulation results show the algorithm excels genetic algorithm and ant colony algorithm in performance and time.