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基于多目標(biāo)遺傳算法優(yōu)化彈性光網(wǎng)絡(luò)的多路徑保護(hù)機(jī)制

劉煥淋,  李瑞艷,  孔德謙,  陳勇

劉煥淋, 李瑞艷, 孔德謙, 陳勇. 基于多目標(biāo)遺傳算法優(yōu)化彈性光網(wǎng)絡(luò)的多路徑保護(hù)機(jī)制[J]. 電子與信息學(xué)報(bào), 2016, 38(9): 2261-2267. doi: 10.11999/JEIT151384
引用本文: 劉煥淋, 李瑞艷, 孔德謙, 陳勇. 基于多目標(biāo)遺傳算法優(yōu)化彈性光網(wǎng)絡(luò)的多路徑保護(hù)機(jī)制[J]. 電子與信息學(xué)報(bào), 2016, 38(9): 2261-2267. doi: 10.11999/JEIT151384
LIU Huanlin, LI Ruiyan, KONG Deqian, CHEN Yong. Optimization Survivable Multipath Provisioning Based on Multi-objectives Genetic Algorithm for Elastic Optical Networks[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2261-2267. doi: 10.11999/JEIT151384
Citation: LIU Huanlin, LI Ruiyan, KONG Deqian, CHEN Yong. Optimization Survivable Multipath Provisioning Based on Multi-objectives Genetic Algorithm for Elastic Optical Networks[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2261-2267. doi: 10.11999/JEIT151384

基于多目標(biāo)遺傳算法優(yōu)化彈性光網(wǎng)絡(luò)的多路徑保護(hù)機(jī)制

doi: 10.11999/JEIT151384 cstr: 32379.14.JEIT151384
  • 1.

    (重慶郵電大學(xué)光纖通信技術(shù)與網(wǎng)絡(luò)重點(diǎn)實(shí)驗(yàn)室 重慶 400065) ②(重慶郵電大學(xué)自動(dòng)化學(xué)院 重慶 400065)

基金項(xiàng)目: 

國家自然科學(xué)基金(61275077, 61571072)，重慶市教委自然科學(xué)基金(KJ1140421)，重慶市科委自然基金(2015jcyjA40024)

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: 彈性光網(wǎng)絡(luò)中多路徑的保護(hù)方案相比單路徑有效地降低網(wǎng)絡(luò)帶寬阻塞率，但會(huì)導(dǎo)致接收端多徑時(shí)延差的問題，且業(yè)務(wù)的多路徑分割傳輸策略使用了光網(wǎng)絡(luò)較多的頻譜資源。該文基于多目標(biāo)遺傳算法提出了遺傳多路徑保護(hù)算法(Genetic Multipath Protection Algorithm, GMPA)，解決多路徑時(shí)延差和節(jié)約頻譜資源問題。在GMPA算法中，根據(jù)業(yè)務(wù)請(qǐng)求在光網(wǎng)絡(luò)中建立K條邊分離最短路徑和帶寬分配方案作為GMPA算法的初始種群，設(shè)計(jì)了一種聯(lián)合考慮傳輸時(shí)延差和帶寬資源分配的向量函數(shù)優(yōu)化種群分類和擁擠距離排序。為提高算法的搜索能力和收斂速度，算法在交叉操作中設(shè)計(jì)個(gè)體自交叉方式，在變異過程中設(shè)置了帶寬基因位變異范圍及約束條件。仿真結(jié)果表明，相比多路徑保護(hù)(Multiple Path Protection, MPP)算法和工作路徑首次分配保護(hù)路徑最后分配(Primary First-fit Modified Backup Last-fit, PF-MBL) 算法，GMPA算法獲得最低的帶寬阻塞率，其頻譜資源利用率接近最優(yōu)的MPP算法，路徑間距離差異性能優(yōu)于MPP算法。
    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.
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出版歷程
  • 收稿日期:  2015-12-08
  • 修回日期:  2016-05-13
  • 刊出日期:  2016-09-19

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