الگوریتم مسیریابی بر اساس بهینه سازی کلونی مورچه و نماینده موبایل

The current Internet can only provide “best effort” transport service, so it is becoming a very urgent task how to provide QoS guarantees for growing video on demand, multimedia conferencing and other multimedia applications based on the existing network architecture. This paper proposes a QoS routing algorithm based on mobile agent and ant colony (QR2A). The QR2A algorithm combines various constraints and network load conditions with the ant colony algorithm in the pheromone, while not only meets the QoS requirements, and solve the problem of network load balancing effectively, and the algorithm is less cost. Meanwhile, the paper also gives formal description, correctness and convergence analysis of QR2A algorithm. Finally practical effect of the algorithm is verified through by the simulation experiment.

The current Internet can only provide "best effort" transport service, so it is becoming a very urgent task how to provide QoS guarantees for growing video on demand, multimedia conferencing and other multimedia applications based on the existing network architecture[1-3]. This paper presents a QoS routing algorithm based on mobile agent and ant colony (QR2A). The QR2A algorithm combines various constraints and network load conditions with the ant colony algorithm in the pheromone, while not only meets the QoS requirements, and solve the problem of network load balancing effectively, and the

For providing QoS guarantee over the current network architecture, this paper proposes a new QoS routing algorithm based on ant algorithm and mobile agent(QR2A). In QR2A the state transition rule, the local updating rule for the amount of pheromone and the global updating rule for the amount of pheromone in ant algorithm are extended, which combines ants’ pheromone with the requested QoS constraints and load in network, while mobile agents are also used as ants in QR2A to search paths. QR2Aboth can gain paths satisfying QoS constraints and can solve effectively load balance in network, moreover its computational cost is lower. This paper not only gives formalization description but also analyses the correctness and convergence about QR2A. Finally some simulation experiments are made to validate the algorithm.