基于自适应协同进化粒子群算法的虚拟网节能映射研究

胡颖; 庄雷; 兰巨龙; 马丁

doi:10.11999/JEIT151434

基于自适应协同进化粒子群算法的虚拟网节能映射研究

doi: 10.11999/JEIT151434

1.
(郑州大学信息工程学院郑州 450000) ②(解放军信息工程大学国家数字交换系统工程技术研究中心郑州 450002) ③(河南工业大学信息科学与工程学院郑州 450000)

基金项目:

国家973计划(2012CB315901)，国家自然科学基金(61379079)，河南省科技厅攻关项目(122102210042)

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- 文章访问数: 1312
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- 被引次数: 0
出版历程
- 收稿日期: 2015-12-17
- 修回日期: 2016-07-01
- 刊出日期: 2016-10-19

Energy Aware Virtual Network Embedding Using Particle Swarm Optimization Algorithm Based on Adaptive

1.
(School of Information Engineering, Zhengzhou University, Zhengzhou 450000, China)
2.
(National Digital Switching System Engineering &

Funds:

The National 973 Program of China (2012CB315901), The National Natural Science Foundation of China (61379079), The Science and Technology Key Project of Henan Province (122102210042)

摘要

摘要: 该文针对虚拟网节能映射问题提出自适应的协同进化粒子群算法。首先，为虚拟网节能映射问题设置了聚合度，该聚合度被用于自适应地选择粒子的搜索方式，即随机搜索、种内搜索或种外搜索。其次，根据粒子群的进化结果，自适应地确定是否终止对子群的搜索。最后，在常用的测试环境下进行了仿真实验，对映射的能耗效果对比了结果，实验结果表明了所提算法的高效性。
- 虚拟网节能映射 /
- 协同进化 /
- 自适应算法 /
- 粒子群算法
Abstract: A novel adaptive co-evolutionary particle swarm optimization algorithm is presented for energy aware virtual network embedding problem. The polymerization degree is designed, which is used to adaptively select searching method, namely variation search, internal search or external search. Second, the algorithm adaptively determine whether to terminate the searching process of particle swarm according to the evolution result. Moreover, extensive simulation under common test environment compares results in energy consumption performing goal, and the results indicate the efficiency of the proposed algorithm.
- Energy aware virtual network embedding /
- Co-evolution /
- Adaptive algorithm /
- Particle swarm optimization algorithm

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参考文献(26)

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