A low-jitter and high-throughput scheduling based on genetic algorithm in slotted WDM networks

Jingjing Zhang; Yaohui Jin; Yikai Su; Buwei Xu; Chunlei Zhang; Yi Zhu; Weisheng Hu

doi:10.1117/12.576516

8 February 2005 A low-jitter and high-throughput scheduling based on genetic algorithm in slotted WDM networks

Jingjing Zhang, Yaohui Jin, Yikai Su, Buwei Xu, Chunlei Zhang, Yi Zhu, Weisheng Hu

Proceedings Volume 5626, Network Architectures, Management, and Applications II; (2005) https://doi.org/10.1117/12.576516
Event: Asia-Pacific Optical Communications, 2004, Beijing, China

Abstract

Slotted WDM, which achieves higher capacity compared with conventional WDM and SDH networks, has been discussed a lot recently. The ring network for this architecture has been demonstrated experimentally. In slotted WDM ring network, each node is equipped with a wavelength-tunable transmitter and a fixed receiver and assigned with a specific wavelength. A node can send data to every other node by tuning wavelength accordingly in a time slot. One of the important issues for it is scheduling. Scheduling of it can be reduced to input queued switch when synchronization and propagation are solved and many schemes have been proposed to solve these two issues. However, it’s proved that scheduling of such a network taking both jitter and throughput into consideration is NP hard. Greedy algorithm has been proposed to solve it before. The main contribution of this paper lies in a novel genetic algorithm to obtain optimal or near optimal value of this specific NP hard problem. We devise problem specific chromosome codes, fitness function, crossover and mutation operations. Experimental results show that our GA provides better performances in terms of throughput and jitter than a greedy heuristic.

Citation Download Citation

Jingjing Zhang, Yaohui Jin, Yikai Su, Buwei Xu, Chunlei Zhang, Yi Zhu, and Weisheng Hu "A low-jitter and high-throughput scheduling based on genetic algorithm in slotted WDM networks", Proc. SPIE 5626, Network Architectures, Management, and Applications II, (8 February 2005); https://doi.org/10.1117/12.576516

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KEYWORDS

Matrices

Wavelength division multiplexing

Genetic algorithms

Genetics

Network architectures

Wavelength division multiplexing networks

Chemical elements

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