A Strategy of Energy Optimization in Enterprise Networks with Location-Constraint

CONG Xin; ZI Ling-ling; YANG Dong-xu

doi:10.3969/j.issn.0372-2112.2019.08.007

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A Strategy of Energy Optimization in Enterprise Networks with Location-Constraint

更新时间：2025-07-16

- A Strategy of Energy Optimization in Enterprise Networks with Location-Constraint
- Acta Electronica Sinica Vol. 47, Issue 8, Pages: 1654-1660(2019)
- 作者机构：
  
  辽宁工程技术大学电子与信息工程学院,辽宁,葫芦岛,125105
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61602227, No.61702241);General Program of Education Department of Liaoning Province (No.LJYL019);Doctoral Research Foundation of Liaoning Province (No.201601365)
- DOI：10.3969/j.issn.0372-2112.2019.08.007
  CLC： TP393
- Published Online：25 August 2019，
  
  Published：2019
- 稿件说明：
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CONG Xin, ZI Ling-ling, YANG Dong-xu. A Strategy of Energy Optimization in Enterprise Networks with Location-Constraint[J]. Acta Electronica Sinica, 2019, 47(8): 1654-1660.
DOI：

CONG Xin, ZI Ling-ling, YANG Dong-xu. A Strategy of Energy Optimization in Enterprise Networks with Location-Constraint[J]. Acta Electronica Sinica, 2019, 47(8): 1654-1660. DOI： 10.3969/j.issn.0372-2112.2019.08.007.

摘要

建立在物理设备集中且以云平台收益为目标的虚拟网络映射技术在企业级网络中存在不适应性，本文提出了有位置限制的企业级虚拟网络映射能源优化策略（EL-VNE）.首先，采用复数理论将计算能力和带宽能力归一到单个节点处，减少了映射次数.其次，提出了EL-VNE模型，包括能源消耗，资源消耗，位置限制等数学描述，并证明其属于NP完全问题.最后，提出了启发式算法求解EL-VNE的最佳解空间，确定虚拟映射方案，达到优化能耗的目的.相比于EAD和GLC等算法，EL-VNE在映射和运行过程中能进一步降低能源消耗且有更好的性能表现.

Abstract

The studied technologies which were based on centralized physical devices and targeted on benefit optimization could not be applied in the enterprise network. To solve this problem

a cost optimization strategy based on location constrain (EL-VNE) was proposed for virtual network embedding in the enterprise network. Firstly

the computing and bandwidth capabilities were unified to a single node by using the complex theory

which decreased embedding times. Secondly

the EL-VNE model was presented and composed by mathematical descriptions about energy consumption

resource consumption and location constrain

which was proved to be NP-completed. Finally

heuristic algorithms were designed to find the solution of EL-VNE and then the embedding scheme with energy optimization was obtained. Compared with algorithms such as EAD and GLC

EL-VNE saves energy consumption in the process of embedding and running

and has better performance.

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