Research And Simulated Implementation On The Traffic Grooming Schemes In Optical Networks Based On Swarm Intelligence

Traffic Grooming is one of the hottest problems in the area of optical networks. It is also a research topic with high scientific and commercial values.High efficient grooming of traffic can effectively reduce network cost.Hence it has aroused much attention from researchers since its appearance.With the explosive increase in network, traffic and the emergence of high performance optical network devices, each wavelength can be operated at very high speed in the optical networks. The huge bandwidth gap between the capacity of a wavelength and the bandwidth required by low-rate traffic streams should be deeply dicussed. Thus the concept of traffic grooming is introduced to solve this problem. Traffic grooming is a technology that can multiplex several low-speed traffic streams onto a high-speed wavelength channel.In order to use the network resource efficiently, low-speed traffic streams need to be efficiently groomed onto high-speed lightpaths, and it can improve the utilization of the network resource greatly.Traffic grooming problems have been proved NP-Hard problems, and should be solved with huristic or intelligent algorithms. In the static traffic grooming problem, we introduce the concept of QoS (Quality of Service);in order to minimize the network cost utilization rate and to maximize the QoS degree of the users at the same time, we set up a general framework based on the Game Theory and the idea of the layered graph, and then apply the intelligent computing algorithm-QIA (Quantum Immune Algorithm) to the framework to solve the problem. In the Quantum Immune algorithm, individuals in a population are represented by quantum bits (qubits).In the individual's updating, the quantum rotation gate strategy and dynamic adjusting rotation angle mechanism are applied to accelerate convergence. By using concentration adjusting operation and high quality gene reservation Strategy in immune system, information among the subpopulation is exchanged by adopting the quantum crossover operation for improvement of diversity of the population and avoiding prematurity. A QPSO (Quantum Particle Swarm Optimization Algorithm) is presented for the dynamic traffic grooming problem, which routes and assigns wavelengths for the new-coming connection request while taking QoS into consideration and minimizing the cost for the request as well.In order to check the feasibility and the validity of the prompted algorithms,a simulation environment is developed with VC++6.0 and several practical optical networks are tested and have got satisfying results.