Real-time applications such as video and audio streaming popularly in the public network require the guarantee of Quality of Services(QoS). But most of the current QoS routing optimization algorithm such as Ant Colony Optimization suffered from scalability problem and local optimum problem and was used in the continuous space. So in this paper, Discrete-Mapping Chaotic Ant Swarm Optimization (DM-CASO) is introduced into the QoS discrete routing area so as to improving QoS routing performance in the network. This paper firstly establish the multi-constrained QoS routing model, then propose a new path update method in the discrete space through the introduction of discrete mapping, finally introduce the natural selection and mutation ideas to effectively jump out of the local optimum. The simulation results show that the proposed algorithm can solve the problem of finding the optimal path and achieve a better effect in the success rate of finding optimal path.

With the development of network, users'services put forward diverse demands on the network QoS (Quality of Service), the QoS routing is the optimization problem under the satisfaction of multiple QoS constraints. This paper firstly sets up a multi-constrained QoS routing model and constructs the fitness value function by transforming the QoS constraints with a penalty function. Secondly, we merge and discrete the iterative formula of PSO (Particles Swarm Optimization) to tailor it to non-continuous search space routing problem. Finally, the natural selection and mutation ideas of Genetic Algorithm are applied to the PSO to improve the PSO algorithm, which makes the particles more diversity. The simulation results show that the proposed algorithm can not only successfully solve the multi-constrained QoS routing problem and increase entire network performance, it also achieves a better effect in the success rate of the search.