[1]顾艳林.优化人工蜂群算法的跨域虚拟网络映射算法[J].华侨大学学报(自然科学版),2016,37(4):507-510.[doi:10.11830/ISSN.1000-5013.201604023]
　GU Yanlin.Multi-Domain Virtual Network Mapping Algorithm Based on Optimized Artificial Bee Colony[J].Journal of Huaqiao University(Natural Science),2016,37(4):507-510.[doi:10.11830/ISSN.1000-5013.201604023]
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优化人工蜂群算法的跨域虚拟网络映射算法()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第37卷
期数:
2016年第4期
页码:
507-510
栏目:
出版日期:
2016-07-04

文章信息/Info

Title:
Multi-Domain Virtual Network Mapping Algorithm Based on Optimized Artificial Bee Colony
文章编号:
1000-5013(2016)04-0507-04
作者:
顾艳林
内蒙古财经大学 计算机信息管理学院, 内蒙古 呼和浩特 010020
Author(s):
GU Yanlin
College of Computer Science and Technology, Inner Mongolia University of Finance and Economics, Huhehaote 361021, China
关键词:
人工蜂群;  虚拟网络;  自治域;  服务代理
Keywords:
artificial bee colony;  virtual network;  autonomous domain;  service agent
分类号:
TP393
DOI:
10.11830/ISSN.1000-5013.201604023
文献标志码:
A
摘要:
针对跨域虚拟网络映射问题,提出一种基于优化人工蜂群算法的跨域虚拟网络映射算法.该算法采用集中管理、分布控制的方式实现物理网络资源的有效利用,并就人工蜂群算法收敛速度慢、局部最优缺点,提出寻优能力更强的优化人工蜂群算法进行域间映射请求的划分.实验结果表明:与LID-MVNE算法、Policy-MVNE算法、GA-MVNE算法相比,所提算法能够以更小的额外开销、更少的划分时间实现更高的接受率.
Abstract:
Aiming at the problem of multi-domain virtual network embedding, a multi-domain virtual network mapping algorithm based on optimized artificial bee colony is proposed. The proposed algorithm can maximize the utilization of limited physical network resources through centralized management and distributed control. And to overcome the defaults of the local optimization and low convergence of the traditional artificial bee colony algorithm, an optimized artificial bee colony algorithm is proposed, which is used to deal with the division of cross-domain mapping request. The experimental result shows that compared with LID-MVNE, Policy-MVNE, GA-MVNE, the proposed algorithm can realize higher acceptance ratio with less extra cost and time division.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2016-05-01
通信作者: 顾艳林(1971-),女,副教授,主要从事计算机应用及网络、程序设计的研究.E-mail:guyanlin5830908@126.com.
基金项目: 内蒙古自治区教育科学规划课题(GJ2011-51-02)
更新日期/Last Update: 2016-07-20