DSEA: A Traffic Control Method of Information Center Networking Based on Multi-objective Genetic Algorithms

DSEA: A Traffic Control Method of Information Center Networking Based on Multi-objective Genetic Algorithms

연구 분야: Networking

학회: Journal of Network and Systems Management

As the host-centric TCP/IP network is hard to fulfill the new network requirements, the Information Center Networking (ICN) emerged. The communication mode of ICN increases the volatility and complexity of the traffic, so how to efficiently carry out traffic scheduling of this complex network has undoubtedly become the key and core problem in ICN. Delay and throughput are indispensable indicators to measure the network performance. However, there is no one to synchronously optimize and balance delay and throughput in the existing work. To solve this problem, based on the multi-objective genetic algorithm Non-dominated Sorting-based Algorithm II, we propose Density Sorting-Based Evolutive Algorithm (DSEA) to optimize the delay and throughput at the same time. The simulation results show that, compared with the existing multi-objective genetic algorithms, DSEA has better performance in evaluation indexes Generational Distance, Inverted Generational Distance, Hypervolume, and Pareto front. And it can reduce the delay by 30.01%, improve the throughput by 43.37% under the premise of a good balance between the two indicators.