| A mobile Ad Hoc network is a multi-hop temporary autonomous system of mobile nodes equipped with wireless transceivers and receivers. It has extensive application prospect in military and civilian field. Recently, many modern network applications, such as transmission of multimedia data and real time collaborative work, require QoS provisions to work properly. However, due to the bandwidth constraint and dynamic topology of Ad Hoc networks, supporting QoS in Ad Hoc networks is a complex and challenging issue.It has been proved that if the QoS routing contains at least two additive metrics, is a NP-complete problem. Ant Colony Algorithm is a meta-heuristic algorithm. The advantages of algorithm are distributing computation, positive feedback, and constructive greed heuristic. In the last few years, ACA has empirically shown its effectiveness in the resolution of several different NP-hard problems. It was introduced to solve the routing problem in Ad Hoc networks. Applying the concept of ant colony algorithm into QoS routing, the ants are seemed as packets that are forwarded randomly from one node to another. The source node is seemed as the nest and the destination node is seemed as the food. Each node maintains a probabilistic routing table. The routing tables are also called pheromone tables. Packets find next hop with a higher probability those links associated with higher pheromone values. After a certain number of iterations, the path which has the highest pheromone was found. The main purpose of our paper is to improve the ACA. So, it can more adaptable to the dynamic changes of Ad Hoc network topology.In order to overcome the limitions of ant colony algorithm, a QoS routing based on bi-directional convergence ant colony algorithm for Ad Hoc networks is proposed. The algorithm has constrains of delay, delay_jitter, bandwidth, and packet_loss. The algorithm can judge the congestion by the average queue length quickly and avoid it. The simulation results show that the proposed algorithm outperforms the traditional on-demand routing algorithm and ARA in the aspects of average end-to-end delay and packet delivery ratio.Put forward a new hybrid algorithm GAAC for solving QoS routing problem in Ad Hoc networks. Firstly, it adopts genetic algorithm to give information pheromone to distribute. Secondly, it makes use of the ant colony algorithm to give the precision of the solution. The algorithm develops enough advantage of the two algorithms. Simulation results show the algorithm has a better performance than the algorithm only based on ant colony algorithm. |
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