Performance optimization of intelligent optical networks by multiple alternate routes based on the K-shortest path algorithm

被引：0
|
作者：
Cu, Xinyou [1 ]
Zheng, Xiaoping [1 ]
Zhang, Hanyi [1 ]
Li, Yanhe [1 ]
Guo, Yili [1 ]
机构：
[1] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China
来源：
NETWORK ARCHITECTURES, MANAGEMENT, AND APPLICATIONS IV | 2006年 / 6354卷
基金：
中国国家自然科学基金;
关键词：
Routing and Wavelength Assignment; K-Shortest Path Algorithm; Dynamic K-Shortest Path Algorithm; Linear Link Weight Function; Piecewise Linear Link Weight Function; Blocking Probability;
D O I：
10.1117/12.691159
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Blocking probability is one of the key factors to evaluate the routing and wavelength algorithms for intelligent optical network. Two kinds of Dynamic K-Shortest Path (DKSP) Algorithms were designed. One is based on Linear Link Weight Function (LW) and the other is based on Piecewise Linear Link Weight Function (PLW). It was found that the two kinds of DKSP can significantly decrease the blocking probability of optical network comparing to the static KSP for the same number of alternate routes. Compared to routing with LW, the coefficient of PLW has larger effect on the blocking probability of optical network when the number of alternate route is small, but the effect is weakened with the increase of the number of alternate route. As far as the two kinds of DKSP algorithms are concerned, DKSP with PLW has some advantage over DKSP with LW on decreasing the blocking probability. It was also found that the optimized performance can almost be got by DKSP with only 2-4 alternate routes for NSFNET.
引用
收藏
页数：8
相关论文
共 50 条
  • [41] Shortest path routing algorithm based on chaotic neural networks
    Zhang, Huidang
    He, Yuyao
    Zhang, Qizhi
    [J]. Jisuanji Gongcheng/Computer Engineering, 2006, 32 (17): : 12 - 14
  • [42] Clustering Algorithm in wireless sensor networks based on shortest path
    El Khediri, Salim
    Thaljaoui, Adel
    Dallali, Adel
    Kachouri, Abdennaceur
    [J]. 2018 30TH INTERNATIONAL CONFERENCE ON MICROELECTRONICS (ICM), 2018, : 335 - 338
  • [43] Application of the support vector machine and heuristic k-shortest path algorithm to determine the most eco-friendly path with a travel time constraint
    Zeng, Weiliang
    Miwa, Tomio
    Morikawa, Takayuki
    [J]. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2017, 57 : 458 - 473
  • [44] Multiple Path Based Regenerator Placement Algorithm in Translucent Optical Networks
    Sambo, N.
    Andriolli, N.
    Giorgetti, A.
    Castoldi, P.
    Bottari, Giulio
    [J]. ICTON: 2009 11TH INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS, VOLS 1 AND 2, 2009, : 1105 - +
  • [45] Study on the K-shortest Paths Searching Algorithm of Urban Mass Transit Network Based on the Network Characteristics
    Zhou, Weiteng
    Han, Baoming
    Yin, Haodong
    [J]. ADVANCES IN TRANSPORTATION, PTS 1 AND 2, 2014, 505-506 : 689 - 697
  • [46] Dynamic priority-based alternate routing for multiple classes of traffic in intelligent optical networks
    Cui, Xinyou
    Li, Yanhe
    Cao, Yining
    Zhang, Hanyi
    Guo, Yili
    Zheng, Xiaoping
    [J]. OPTICAL ENGINEERING, 2007, 46 (02)
  • [47] Finding Community Structure in Networks Using a Shortest-Path-Based k-Means Algorithm
    Jinglu GAO
    [J]. Journal of Mathematical Research with Applications, 2013, (03) : 288 - 296
  • [48] Finding Community Structure in Networks Using a Shortest-Path-Based k-Means Algorithm
    Jinglu GAO
    [J]. 数学研究及应用, 2013, 33 (03) : 288 - 296
  • [49] Optimization of subway crew scheduling based on shortest path faster algorithm
    Xue, Feng
    Liang, Peng
    Li, Hai
    Chen, Chongshuang
    Zhou, Tianxing
    [J]. Journal of Railway Science and Engineering, 2022, 19 (09) : 2532 - 2540
  • [50] Drilling path optimization based on swarm intelligent algorithm
    Zhu, Guang Yu
    [J]. 2006 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS, VOLS 1-3, 2006, : 193 - 196
12345