Group Of Intelligent Optimization Algorithms In Qos Routing Optimization

With the development of the technology computer information and communication, the requirement of instantaneity of network from users is increasing. Internet has communicated using the protocol of TCP/IP in network layer, and has solved interconnection between different networks. But the serves provided only fit for data transmission and still have a lot of insufficiencies in multimedia transmission.QoS (Quality of Service) technology is an effective method to solve multimedia transmission. Recently IP QoS is considered as an important research subject. Network routing optimization has been a focused problem. The problem of QoS network routing optimization is a Combinatorial Optimization and NP hard which has been confirmed by the research.QoS network routing generally searches for the shortest route from the source node to the destination asked by the business requirement while insure the QoS, such as delay, delay jitter and packet loss. QoS network routing of Internet directly affects the transmission speed and the real-time of the user getting the information from Internet. Therefore, the research on QoS network routing has become the research emphases on field. Intelligent optimization algorithm is a group of methods to search for the shortest route, which simulated life-habit of social animal. In recent years, some intelligent optimization algorithms appeared in succession, such as ant colony algorithm, particle swarm optimization and artificial fish, etc. The kind of algorithm is becoming popular with the experts from all over the world because their ideas are simple and they are also easily to implement. This thesis researched the application of QoS network routing based on the characteristic of it and its necessity and the feasibility to solve QoS network routing using intelligent optimization.Firstly, this thesis analyzes the research meaning and state, introduces the insufficiencies in solving QoS network routing problems and development of intelligent optimization algorithm, and also proposes three intelligent optimization algorithms on solving TSP problems and QoS network routing problems.Secondly, use three algorithms in simulations to solve TSP problems. This thesis uses data from standard test database, do a lot of simulations, and analyze the experiment results. Then the chaotic ACO, ACO with improved information updating rules, intelligent artificial fish algorithm, and newly intelligent water drop algorithm which designs the code, object function, solution space in details. Also, the parameters in AOC are changed several times to compare. Lastly, Based on these three algorithms succeeded in solving TSP problem, this thesis mainly designs the application of these algorithms in QoS network routing optimization. Undirected graph is used to model in computer networks, the application designs, including code design, object function, solution space establishment, simulations and result analysis, of the 3 intelligent algorithms are introduced. Meanwhile, two improved ACO with different parameter values are used to simulate and compare, both of which have good results.