Design And Simulated Implementation Of Routing Algorithm In Green Network

With the energy and environmental problems are becoming more and more serious, the energy saving has become the focus issue in all fields of people’s lives. In recent years, due to the routers, servers, switches and other network equipments account for a growing proportion in energy consumption and carbon dioxide emissions, therefore, the construction of green network which aiming at saving energy has gradually become the focus of domestic and international concern.Take into account the limitations of current research in energy-saving algorithms, this thesis proposes a green network routing mechanism which jointly considers of IP layer and optical layer and supports multi-granularity. First of all, design the reasonable structures of node and link to build a network model, and depict the different types of network service request. Second, depict the mathematical model according to the network model and the service requests. Third, design an efficient and reasonable auxiliary graph structure to improve the performance of the routing algorithm. At last, design unicast routing algorithm and multicast routing algorithm in green network separately. Due to the uncertainty of the network service request, design unicast routing algorithm facing certain requests and uncertain requests in green network separately. The implementation of unicast routing algorithm facing certain requests in green network is based on the self-adaptive step glowworm swarm optimization algorithm. And implement unicast routing algorithm facing uncertain requests in green network using mutative scale chaos particle swarm optimization algorithm based on self logical mapping function. For the multicast situation, design one-to-many multicast routing algorithm and many-to-many multicast routing algorithm according to different scenarios. The implementation of one-to-many multicast routing algorithm facing certain requests and many-to-many multicast routing algorithm facing uncertain requests in green network is based on quantum-inspired estimation of distribution algorithm based on comprehensive learning. The implementation of one-to-many multicast routing algorithm facing uncertain requests in green network is based on hybrid optimization algorithms based on particle swarm optimization and genetic algorithm. And implement many-to-many multicast routing algorithm facing certain requests in green network using the heuristic algorithm based on estimation of distribution.Finally, test the routing algorithms presented in this thesis on network topologies with different scale. According to the result of performance evaluation, the routing algorithms presented in this thesis are able to generate solutions under the premise of meeting the QoS requirements, and they can effectively reduce network energy consumption and have better performance.