基于自適應(yīng)協(xié)同進(jìn)化粒子群算法的虛擬網(wǎng)節(jié)能映射研究

胡穎; 莊雷; 蘭巨龍; 馬丁

doi:10.11999/JEIT151434

基于自適應(yīng)協(xié)同進(jìn)化粒子群算法的虛擬網(wǎng)節(jié)能映射研究

doi: 10.11999/JEIT151434

1.
(鄭州大學(xué)信息工程學(xué)院鄭州 450000) ②(解放軍信息工程大學(xué)國(guó)家數(shù)字交換系統(tǒng)工程技術(shù)研究中心鄭州 450002) ③(河南工業(yè)大學(xué)信息科學(xué)與工程學(xué)院鄭州 450000)

基金項(xiàng)目:

國(guó)家973計(jì)劃(2012CB315901)，國(guó)家自然科學(xué)基金(61379079)，河南省科技廳攻關(guān)項(xiàng)目(122102210042)

計(jì)量
- 文章訪問(wèn)數(shù): 1335
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出版歷程
- 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: 該文針對(duì)虛擬網(wǎng)節(jié)能映射問(wèn)題提出自適應(yīng)的協(xié)同進(jìn)化粒子群算法。首先，為虛擬網(wǎng)節(jié)能映射問(wèn)題設(shè)置了聚合度，該聚合度被用于自適應(yīng)地選擇粒子的搜索方式，即隨機(jī)搜索、種內(nèi)搜索或種外搜索。其次，根據(jù)粒子群的進(jìn)化結(jié)果，自適應(yīng)地確定是否終止對(duì)子群的搜索。最后，在常用的測(cè)試環(huán)境下進(jìn)行了仿真實(shí)驗(yàn)，對(duì)映射的能耗效果對(duì)比了結(jié)果，實(shí)驗(yàn)結(jié)果表明了所提算法的高效性。
- 虛擬網(wǎng)節(jié)能映射 /
- 協(xié)同進(jìn)化 /
- 自適應(yīng)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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