面向節(jié)點異構(gòu)的能耗感知虛擬網(wǎng)絡映射算法

龔水清; 陳靖; 王崴

doi:10.11999/JEIT141527

面向節(jié)點異構(gòu)的能耗感知虛擬網(wǎng)絡映射算法

doi: 10.11999/JEIT141527

1.
(空軍工程大學信息與導航學院西安 710077) ②(空軍工程大學防空反導學院西安 710051)

基金項目:

國家自然科學基金(51075395)和國家863計劃項目(2013AA040604)

計量
- 文章訪問數(shù): 1302
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2014-12-02
- 修回日期: 2015-03-06
- 刊出日期: 2015-08-19

Energy-aware Virtual Network Embedding Algorithm for Heterogeneous Nodes

1.
(College of Information and Navigation, Air Force Engineering University, Xi'an 710077, China)
2.
(College of Air and Missile Defense, Air Force Engineering University, Xi'an 710051, China)

摘要

摘要: 在底層網(wǎng)絡節(jié)點異構(gòu)的環(huán)境中，能耗優(yōu)化的虛擬網(wǎng)絡映射問題并不是最小化工作節(jié)點和鏈路數(shù)。該文針對此問題，構(gòu)建底層網(wǎng)絡節(jié)點和鏈路的負載能耗模型，并以能耗最優(yōu)為目標，建立虛擬網(wǎng)絡映射問題的數(shù)學模型，提出一種能耗感知虛擬網(wǎng)絡映射算法。該算法在節(jié)點映射階段以最小化能耗和協(xié)調(diào)鏈路映射為原則，將虛擬節(jié)點映射至綜合資源能力最大的底層節(jié)點上，并采用改進的能耗感知k最短路徑法進行鏈路映射。仿真結(jié)果表明，該算法顯著減少虛擬網(wǎng)絡映射的能耗，且底層網(wǎng)絡節(jié)點異構(gòu)性越大，能耗優(yōu)勢更為明顯。
- 網(wǎng)絡虛擬化 /
- 虛擬網(wǎng)絡映射 /
- 能耗模型 /
- 資源能力
Abstract: The energy optimized virtual network embedding problem in the substrate network with heterogeneous nodes is not to minimize the number of working nodes and links. The load-based energy consumption models of the node and link in the substrate network are built, a mathematical model of the virtual network embedding problem is modeled in order to reduce energy consumption, and an energy-aware virtual network embedding heuristic algorithm is proposed. Based on the principles of energy optimization and coordination with link mapping, the virtual node is mapped onto the substrate node with the highest comprehensive resource capacity in the node mapping phase, and the link mapping phase is based on the energy-aware k shortest path algorithm. Simulation results show that the proposed algorithm reduces the energy consumption significantly, and the heterogeneity of substrate network nodes is greater, reducing the energy consumption is more obvious.
- Network virtualization /
- Virtual network embedding /
- Energy consumption model /
- Resource capacity

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