Abstract
To optimize the QoS of optical burst switching networks, a QoS routing optimization algorithm based on a multi-objective genetic algorithm is proposed. A Bayesian network model is used to locate the fault of optical burst switching network and obtain the fault location of the transmission link of optical burst switching network; In this position, the routing optimization algorithm based on a multi-objective genetic algorithm transforms the multi constrained network quality of service routing optimization problem into a constrained multi-objective routing optimization problem. Under multiple constraints, the best path of optical burst switching network service is obtained to realize the optical burst switching network quality of service routing optimization. The results show that after applying the proposed algorithm, the average delay of video, text and picture transmission in an optical burst switching network is less than 400ms. The proposed algorithm can improve the packet delivery rate of information transmission in an optical burst switching network, reduce the transmission delay, blocking probability and use cost of an optical burst switching network, and optimize the service quality of an optical burst switching network.
Highlights
The 21st century is an information age with networks as the core
Given the problems of the above algorithms, this paper proposes a multi-objective genetic algorithm-based routing optimization algorithm for optical burst switching network quality of service, which generates a set of optimal non-inferior paths whose performance is balanced between different performance goals
Based on the idea of multiobjective optimization, this paper transforms the multi constraint routing problem into a constrained multi-objective routing optimization problem, proposes a quality of service (QoS) routing optimization algorithm for optical burst switching networks based on multi-objective genetic algorithm, and analyzes the application effect of this multi-objective routing algorithm, It solves the problems existing in traditional algorithms and lays the foundation for optical burst switching network services
Summary
The 21st century is an information age with networks as the core. People's demand for information is increasing day by day. OBS network, as the basic technology of next-generation optical Internet, must provide differentiated services for various high-level services and provide good quality of service (QoS). It must focus on the following issues: first, how to solve the problem of high loss rate caused by the competition between data bursts (DB); second, how to reduce the end-to-end delay (including the assembly process) of DB. Given the problems of the above algorithms, this paper proposes a multi-objective genetic algorithm-based routing optimization algorithm for optical burst switching network quality of service, which generates a set of optimal non-inferior paths whose performance is balanced between different performance goals. QOS ROUTING OPTIMIZATION ALGORITHM BASED ON MULTI-OBJECTIVE GENETIC ALGORITHM FOR OBS NETWORKS
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