Improving NSGA-II for Multi-Constrained QoS Routing

With the development of 5G technology, the traffics which need multiple quality of service (QoS) constraints greatly increase. The existing QoS routing algorithms either support a single QoS constraint or support multiple constraints are mixed with fixed weights. The latter is essentially a single-constrained QoS algorithm. Few studies can provide the quality of service guaranteed under the true sense of multiple constraints, by which only one solution can be provided. In this paper, we propose NSGAII-MCR: a multi-constrained QoS routing algorithm based on non-dominated sorting genetic algorithm II (NSGA-II). In NSGAII-MCR, three representative constraints are selected: delay, bandwidth, and packet loss rate. The validity of the routing is guaranteed by a designed encoding and decoding scheme and a novel individual generation method. Meantime, the original NSGA-II crossover and mutation operators are modified. We further enhance the selection strategy to improve the diversity of solutions and the robustness of NSGAII-MCR. At last, multiple optional routes in the Pareto-optimal front are obtained. The experiment demonstrates that the proposed NSGAII-MCR can achieve high success rate by up to 95%. Compared with the benchmarking methods, NSGAII-MCR can support more constraints and finds more multi-constrained routes.

QoS Routing Algorithm Based on Entropy Granularity in the Network Transmission

With the rapid development of computer networks, more hosts are connected to the Internet where they could communicate with each other. The need for network service has exceeded the service capacity of the network, and the Quality of Service (QoS) is gradually declining. Based on existing Shortest Path First (SPF) algorithm, this paper proposes a new QoS required transmission path approach by considering the overhead balance of network resources. This paper uses the entropy granularity as the main line in the application of routing protocols. Firstly, it researches the optimization of routing algorithms for network load balancing resources, routing algorithms based on link traffic distributing weights, link weight optimization based on adaptive genetic algorithm and computational intelligence based on entropy granularity theory. This research proposes a method to apply entropy granularity to Open Shortest Path First (OSPF) routing, including the implementation of the method. After that, a case study is presented by using some examples.