基于多目标遗传算法优化弹性光网络的多路径保护机制

刘焕淋; 李瑞艳; 孔德谦; 陈勇

doi:10.11999/JEIT151384

基于多目标遗传算法优化弹性光网络的多路径保护机制

doi: 10.11999/JEIT151384

1.
(重庆邮电大学光纤通信技术与网络重点实验室重庆 400065) ②(重庆邮电大学自动化学院重庆 400065)

基金项目:

国家自然科学基金(61275077, 61571072)，重庆市教委自然科学基金(KJ1140421)，重庆市科委自然基金(2015jcyjA40024)

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出版历程
- 收稿日期: 2015-12-08
- 修回日期: 2016-05-13
- 刊出日期: 2016-09-19

Optimization Survivable Multipath Provisioning Based on Multi-objectives Genetic Algorithm for Elastic Optical Networks

1.
(Key Laboratory of Optical Communications and Networks, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)
2.
(School of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)

Funds:

The National Natural Science Foundation of China (61275077, 61571072), The Scientific Research Fund of Chongqing Municipal Commission (KJ1140421), The Basic and Frontier Research Program of Chongqing (2015jcyjA40024)

摘要

摘要: 弹性光网络中多路径的保护方案相比单路径有效地降低网络带宽阻塞率，但会导致接收端多径时延差的问题，且业务的多路径分割传输策略使用了光网络较多的频谱资源。该文基于多目标遗传算法提出了遗传多路径保护算法(Genetic Multipath Protection Algorithm, GMPA)，解决多路径时延差和节约频谱资源问题。在GMPA算法中，根据业务请求在光网络中建立K条边分离最短路径和带宽分配方案作为GMPA算法的初始种群，设计了一种联合考虑传输时延差和带宽资源分配的向量函数优化种群分类和拥挤距离排序。为提高算法的搜索能力和收敛速度，算法在交叉操作中设计个体自交叉方式，在变异过程中设置了带宽基因位变异范围及约束条件。仿真结果表明，相比多路径保护(Multiple Path Protection, MPP)算法和工作路径首次分配保护路径最后分配(Primary First-fit Modified Backup Last-fit, PF-MBL) 算法，GMPA算法获得最低的带宽阻塞率，其频谱资源利用率接近最优的MPP算法，路径间距离差异性能优于MPP算法。
- 弹性光网络 /
- 遗传多路径保护算法 /
- 路径间距离差异
Abstract: Multipath provisioning algorithm outperforms single-path provisioning algorithm in terms of bandwidth blocking probability. However, multipath transmission causes the differential delay among different paths and affects the usage of spectrum resources. To address the problem, a Genetic Multipath Protection Algorithm (GMPA) is proposed based on multi-objectives genetic algorithm. according to traffic requests, the K link-disjoined paths and bandwidth assignments are designed as the population initialization scheme. A vector function is proposed to balance the path-distance difference and network spectrum resources by optimizing population classification and crowding distance sorting. An individual self-cross pattern is introduced and the variation range and constraint conditions of bandwidth gene are designed to improve the algorithm search ability and convergence. Compared with the Multiple Path Protection (MPP) and Primary First-fit Modified Backup Last-fit (PF-MBL), simulation results show that the proposed GMPA algorithm can get lowest bandwidth blocking probability, its spectrum resource utilization is close to the optimal MPP, and the path-distance difference of GMPA is better than that of MPP.
- Elastic Optical Networks (EONs) /
- Genetic Multipath Protection Algorithm (GMPA) /
- Path-distance difference

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参考文献(20)

ZHOU H, MAO S, and AGRAWAL P. Optical power allocation for adaptive transmissions in wavelength-division multiplexing free space optical networks[J]. Digital Communications and Networks, 2015, 1(3): 171-180. doi: 10.1016/j.dcan.2015.09.004.

刘焕淋, 方强, 雷芳. WDM光网络中多播业务量疏导方法分析[J]. 重庆邮电大学学报(自然学报), 2012, 24(3): 269-277. doi: 10.3979/j.issn.1673-825X.2012.03.001.

LIU Huanlin, FANG Qiang, and LEI Fang. Analysis of multicast traffic grooming algorithms in WDM mesh networks [J]. Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition), 2012, 24(3): 269-277. doi: 10.3979/j.issn.1673-825X.2012.03.001.

刘焕淋, 岁蒙, 徐一帆, 等. 基于距离自适应和有效共享路径感知的光疏导方法[J]. 电子与信息学报, 2015, 37(8): 1955-1970. doi: 10.11999/JEIT141442.

LIU Huanlin, SUI Meng, XU Yifan, et al. A method of optical grooming for distance-adaptive and effective sharing path-aware[J]. Journal of Electronics Information Technology, 2015, 37(8): 1955-1970. doi: 10.11999/ JEIT141442.

SHEN G, WEI Y, and BOSE S K. Optimal design for shared backup path protected elastic optical networks under single-link failure[J]. Journal of Optical Communications and Networking, 2014, 6(7): 649-659. doi: 10.1109/JOCN.2014. 6850206.

WAN X, HUA N, and ZHENG X. Dynamic routing and spectrum assignment in spectrum-flexible transparent optical networks[J]. Journal of Optical Communications and Networking, 2012, 4(8): 603-613. doi: 10.1364/JOCN.4. 000603.

TARHAN A and CAVDAR C. Shared path protection for distance adaptive elastic optical networks under dynamic traffic [C]. Reliable Networks Design and Modeling (RNDM), Almaty, 2013: 62-67. doi: 10.1109/ICUMT.2013.6798405.

WANG X, KUANG K X, WANG S, et al. Dynamic routing and spectrum allocation in EONs with mixed line rates[J]. Journal of Optical Communications and Networking, 2014, 6(12): 1115-1127. doi: 10.1109/JOCN.2014.6985903.

ZHU Z, LU W, ZHANG L, et al. Dynamic service provisioning in elastic optical networks with hybrid single-multi-path routing[J]. Journal of Lightwave Technology, 2013, 31(1): 15-22. doi: 10.1109/JLT.2012.2227683.

XIAO N and RUAN L. Survivable multipath provisioning in OFDM-based flexible optical networks[C]. Globecom Workshops, Anaheim, 2012: 346-351. doi: 10.1109/ GLOCOMW.2012.6477595.

RUAN L and ZHENG Y. Dynamic survivable multipath routing and spectrum allocation in OFDM-based flexible optical networks[J]. Journal of Optical Communications and Networking, 2014, 6(1): 77-85. doi: 10.1364/JOCN.6.000077.

LU W, ZHOU X, GONG L, et al. Dynamic multi-path service provisioning under differential delay constraint in elastic optical networks[J]. IEEE Communications Letters, 2013, 17(1): 158-161. doi: 10.1109/LCOMM.2012.120612.121343.

HUANG S, MARTEL C U, and Mukherjee B. Survivable multipath provisioning with differential delay constraint in telecom mesh networks[J]. IEEE/ACM Transactions on networking, 2011, 19(3): 657-669. doi: 10.1109/TNET.2010. 2082560.

尹珊. 灵活光网络中的资源优化[D]. [博士论文], 北京邮电大学, 2014.

YIN Shan. Resource optimization in flexible optical WDM networks[D]. [Ph.D. dissertation], Beijing University of Posts and Telecommunications, 2014.

申晓宁, 李涛, 张敏. 一种基于模糊逻辑引入偏好信息的多目标遗传算法[J]. 南京理工大学学报, 2011, 32(2): 245-250. doi: 10.14177/j.cnki.32-1397n.2011.02.015.

SHEN Xiaoning, LI Tao, and ZHANG Min. Multi-objective optimization genetic algorithm incorporating preference information based on fuzzy logic[J]. Journal of Nanjing University of Science and Technology, 2011, 32(2): 245-250. doi: 10.14177/j.cnki.32-1397n.2011.02.015.

张宇, 李国建, 史彬. 非支配排序进化策略求解煤气化多目标优化问题[J]. 化工学报, 2013, 64(12): 4628-4633.

ZHANG Yu, LI Guojian, and SHI Bin. Multi-objective optimization of coal gasifier using NSES[J]. CIESC Journal, 2013, 64(12): 4628-4633.

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