Optical multicast coding-link cost trade-off method based on improved nsga-Ⅱ

Abstract

The invention relates to an optical multicast coding-link cost compromise method based on improved NSGA-II, which belongs to the technical field of communication. Compared with the existing technology, the improvement of this method mainly includes the following parts: Arrange the coding cost in ascending order, and put the individuals with smaller coding cost into a higher level to solve the problem of optimizing the coding cost and optimizing the chain. The complexity of the road cost is different; the combination of crowding distance and Hamming distance realizes the discrimination between individuals, which is convenient to find a better solution; a learning-based crossover operator is used to guide the continuous evolution of the algorithm , to speed up the convergence rate. Adopting this method to solve the encoding-link cost trade-off problem in the optical multicast network, it is easy to find more compromise points and the number of different coding schemes corresponding to each compromise point, so as to realize the optical multicast network reaching the maximum Better scheduling of network coding while increasing multicast throughput.

Description

technical field [0001] The invention belongs to the technical field of communication, and relates to an optical multicast coding-link cost compromise method based on improved NSGA-II. Background technique [0002] With the rapid development of multicast services such as video conferencing, Internet TV, and multimedia distance education, the consumption of network bandwidth and the rapid increase of congestion, traditional communication networks are facing insufficient bandwidth resources, low network throughput, and rising service blocking rates. Serious problem, network resources are becoming increasingly strained. Due to the high-bandwidth and high-speed information transmission capabilities of optical networks, it temporarily solves the problem of insufficient bandwidth resources in traditional electric domain networks. However, with the sustained and rapid growth of broadband services and multicast applications in recent years, optical networks are once again facing man...

AI Technical Summary

Problems solved by technology

At present, many scholars adopt various intelligent optimization algorithms to solve, such as multi-objective genetic algorithm, particle swarm optimization algorithm, etc., but these methods still have a lack in the diversity of algorithm effectiveness and solutions. Therefore, the present invention based on this An improved NSGA-Ⅱ algorithm (Non-dominated sorting genetic algorithm Ⅱ, non-dominated sorting genetic algorithm Ⅱ) is proposed for the coding-link cost compromise problem.

Images