1st International ICST Conference on Communications and Networking in China

Research Article

An Efficient Composite Scheduling Algorithm for Optical Burst Switching Networks

  • @INPROCEEDINGS{10.1109/CHINACOM.2006.344727,
        author={Ruyan  Wang and Jiaofa  Chang and Keping  Long and Xiaolong  Yang},
        title={An Efficient Composite Scheduling Algorithm for Optical Burst Switching Networks},
        proceedings={1st International ICST Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2007},
        month={4},
        keywords={},
        doi={10.1109/CHINACOM.2006.344727}
    }
    
  • Ruyan Wang
    Jiaofa Chang
    Keping Long
    Xiaolong Yang
    Year: 2007
    An Efficient Composite Scheduling Algorithm for Optical Burst Switching Networks
    CHINACOM
    IEEE
    DOI: 10.1109/CHINACOM.2006.344727
Ruyan Wang1,2,3,4,*, Jiaofa Chang1,2,*, Keping Long1,2,*, Xiaolong Yang1,2,*
  • 1: Special Research Centre for Optical Internet & Wireless Information Networks
  • 2: Chongqing University of Posts and Telecommunications, Chongqing 400065, CHINA
  • 3: School of Communication and Information Engineering
  • 4: University of Electronic Science and Technology of China, Chengdu 610054, CHINA
*Contact email: wangry@cqupt.edu.cn, cjfwinner@tom.com, longkp@cqupt.edu.cn, yangxl@cqupt.edu.cn

Abstract

Optical burst switching (OBS) is a promising paradigm for the next generation Internet. Data channel scheduling algorithm is one of the key issues in OBS networks. In this paper, an efficient composite data channel scheduling algorithm is proposed, this algorithm select LAUC or LAUC-VF to schedule the arriving burst according to the current information of the void interval of the data channel. The algorithm reduces scheduling time of data burst while minimizing the void interval of the data channel. Simulation results show that the scheduling time of the proposed algorithm is close to LAUC, and the performance of data burst loss probability is better than LAUC-VF.