SDN based network resource selection multi-objective optimization algorithm

Nan BAO; Jiakuo ZUO; Han HU; Xu BAO

doi:10.11959/j.issn.1000-436x.2019031

您当前的位置：

首页 >

文章列表页 >

SDN based network resource selection multi-objective optimization algorithm

Papers | 更新时间：2024-06-05

- SDN based network resource selection multi-objective optimization algorithm
- Journal on Communications Vol. 40, Issue 2, Pages: 51-59(2019)
- 作者机构：
  
  1. 南京邮电大学物联网学院，江苏南京 210023
  2. 江苏大学计算机科学与通信工程学院，江苏镇江 212013
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61701255);The Natural Science Foundation of Jiangsu Province(BK20150866);The Natural Science Foundation of the Jiangsu Higher Education Institutions(15KJB510026);Postdoctoral Fund of Jiangsu Province(SBH17024);NUPTSF(NY214185);NUPTSF(NY215046);NUPTSF(NY217056)
- DOI：10.11959/j.issn.1000-436x.2019031
  CLC： TP393
- Online First：2019-02，
  
  Published：25 February 2019
- 稿件说明：
移动端阅览
Nan BAO, Jiakuo ZUO, Han HU, et al. SDN based network resource selection multi-objective optimization algorithm[J]. Journal on Communications, 2019, 40(2): 51-59.
DOI：

Nan BAO, Jiakuo ZUO, Han HU, et al. SDN based network resource selection multi-objective optimization algorithm[J]. Journal on Communications, 2019, 40(2): 51-59. DOI： 10.11959/j.issn.1000-436x.2019031.

摘要

针对基于软件定义网络（SDN）的复杂结构中不同资源效用目标共存、资源选择策略相互影响的问题，提出了一种基于 SDN 的网络资源选择多目标优化算法。该算法综合考虑资源供给方和客户方对资源效用的不同优化目标，构建资源选择多目标优化模型，并采用基于参考矢量的多目标优化算法对模型求解。仿真结果表明，与其他资源优化算法相比，所提算法能够快速收敛得到均匀分布的非劣解集，均衡基于 SDN 资源接入管理时多方的优化目标。

Abstract

For the problem of coexistence of different resource utility objectives and mutual influence of resource selection strategies in the complex structure of software-defined network (SDN)

an SDN based network resource selection multi-objective optimization algorithm was proposed.The optimization goals of resource providers and clients were taken into account in the algorithm

and a resource selection multi-objective optimization model was constructed.The model was further solved by the reference vector based multi-objective optimization algorithm.Simulation results show that compared with other algorithms

the proposed algorithm could quickly converge to the uniformly distributed non-inferior solution set

and balance the optimization objects of multi-party in SDN based resource access management.

关键词

Keywords

references

BHAT P , NAGATA S , CAMPOY L , et al . LTE-advanced:an operator perspective [J ] . IEEE Communications Magazine , 2012 , 50 ( 2 ): 104 - 114 .

ALI-AHMAD H , CICCONETTI C , OLIVA A D L , et al . An SDNbased network architecture for extremely dense wireless networks [C ] // IEEE Future Networks and Services . 2013 : 1 - 7 .

WANG K , WANG Y , ZENG D , et al . An SDN-based architecture for next-generation wireless networks [J ] . IEEE Wireless Communications , 2017 , 24 ( 1 ): 25 - 31 .

ZEHRA U , SHAH M A . A survey on resource allocation in software defined networks (SDN) [C ] // International Conference on Automation and Computing . 2017 : 1 - 6 .

刘宇 . SDN的网络虚拟化资源分配技术 [D ] . 南京:南京邮电大学 , 2015 .

LIU Y . Resource allocation technology of network virtualization in software-defined networks [D ] . Nanjing:Nanjing University of Posts and Telecommunications , 2015 .

AWAIS M , AHMED A , NAEEM M , et al . Efficient joint user association and resource allocation for cloud radio access networks [J ] . IEEE Access , 2017 , 5 ( 99 ): 1439 - 1448 .

ZHANG Y , WANG Y , FAN B . SDN based optimal user cooperation and energy efficient resource allocation in cloud assisted heterogeneous networks [J ] . IEEE Access , 2017 , 5 ( 99 ): 1469 - 1481 .

张潇璐 , 刘曦 , 李伟东 , 等 . 基于共享资源量的动态多资源公平分配策略 [J ] . 通信学报 , 2016 , 37 ( 7 ): 151 - 160 .

ZHANG X L , LIU X , LI W D , et al . Dynamic fair allocation of multi-resources based on shared resource quantity [J ] . Journal on Communications , 2016 , 37 ( 7 ): 151 - 160 .

FARSHIN A , SHARIFIAN S . MAP-SDN:a metaheuristic assignment and provisioning SDN framework for cloud datacenters [J ] . Journal of Supercomputing , 2017 , 73 ( 1 ): 1 - 25 .

王力 , 赵季红 , 曲桦 , 等 . 软件定义承载网中基于负载均衡的虚拟网络资源分配算法 [J ] . 电信科学 , 2015 , 31 ( 11 ): 32 - 38 .

WANG L , ZHAO J H , QU H , et al . Virtual network resource allocation algorithm based on load balance in carrier-SDN [J ] . Telecommunications Science , 2015 , 31 ( 11 ): 32 - 38 .

SEYEDEBRAHIMI M , BOUHAFS F , RASCHELLÀ A , et al . SDN-based channel assignment algorithm for interference management in dense Wi-Fi networks [C ] // IEEE European Conference on Networks and Communications . 2016 : 128 - 132 .

NARMANIIOGLU O , ZEYDAN E . Interference coordination in SDN-based heterogeneous mobile networks [C ] // IEEE International Black Sea Conference on Communications and Networking . 2017 : 1 - 6 .

ZHANG H , WANG B , JIANG C , et al . Energy efficient dynamic resource allocation in NOMA networks [C ] // IEEE Global Communications Conference . 2017 : 1 - 5 .

赵思逸 , 陈靖 , 龚水清 . 基于粒子群优化的虚拟 SDN 网络映射算法 [J ] . 计算机工程 , 2016 , 42 ( 12 ): 84 - 90 .

ZHAO S Y , CHEN J , GONG S Q . Virtual SDN network mapping algorithm based on particle swarm optimization [J ] . Computer Engineering , 2016 , 42 ( 12 ): 84 - 90 .

ZHAO Y , CHEN Y , JIAN R , et al . A resource allocation scheme for SDN-based 5G ultra-dense heterogeneous networks [C ] // IEEE GLOBECOM Workshops . 2017 : 1 - 6 .

KANG Q , SONG X , ZHOU M C , et al . A collaborative resource allocation strategy for decomposition-based multiobjective evolutionary algorithms [J ] . IEEE Transactions on Systems Man ＆ Cybernetics Systems ( Early Access ) , 2018 ,PP( 99 ): 1 - 8 .

JIN Y , OLHOFER M , SENDHO B . Dynamic weighted aggregation for evolutionary multi-objective optimization:why does it work and how? [C ] // Genetic and Evolutionary Computation Conference . 2001 : 1042 - 1049 .

ZHANG Q , LI H . MOEA/D:a multiobjective evolutionary algorithm based on decomposition [J ] . IEEE Transactions on Evolutionary Computation , 2007 , 11 ( 6 ): 712 - 731 .

LIU H L , GU F , ZHANG Q . Decomposition of a multiobjective optimization problem into a number of simple multiobjective subproblems [J ] . IEEE Transactions on Evolutionary Computation , 2014 , 18 ( 3 ): 450 - 455 .

CHENG R , JIN Y , OLHOFER M , et al . A reference vector guided evolutionary algorithm for many-objective optimization [J ] . IEEE Transactions on Evolutionary Computation , 2016 , 20 ( 5 ): 773 - 791 .

CHENG R , JIN Y , NARUKAWA K , et al . A multiobjective evolutionary algorithm using gaussian process-based inverse modeling [J ] . IEEE Transactions on Evolutionary Computation , 2015 , 19 ( 6 ): 838 - 856 .

PREECE D A . Experiments with mixtures:designs,models,and the analysis of mixture data [M ] . Hoboken : WileyPress , 2011 .

DEB K , AGRAWAL R B . Simulated binary crossover for continuous search space [J ] . Complex Systems , 1994 , 9 ( 3 ): 115 - 148 .

DEB K , GOYAL M . A Combined genetic adaptive search (GeneAS) for engineering design [J ] . Computer Science and Informatics , 1996 , 26 ( 4 ): 30 - 45 .

COELLO C A C , PULIDO G T , LECHUGA M S . Handling multiple objectives with particle swarm optimization [J ] . IEEE Transactions on Evolutionary Computation , 2007 , 8 ( 3 ): 256 - 279 .

Views

3111

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Optimization of air-ground cooperative communication performance for UAV-mounted STAR-RIS

ResilM-IBN: multi-agent framework for self-healing network management

Optimization approach for link establishment based on zero-hop transmission and parallel flow rules deployment in SDN

Time-triggered stream scheduling method combining no-wait and time-slot mapping reuse

Resource allocation algorithm for multi-beam LEO satellite based on decision performance evaluation

Related Author

Han Zhengjiang

Zhou Tao

Wang Erfu

Dong Ligang

Gou Jingwen

Jiang Xian

Zhang Zitian

Zhuge Bin

Related Institution

Electronic Engineering College, Heilongjiang University

School of Information and Electronic Engineering, Zhejiang Gongshang University

School of Computer Science, National University of Defense Technology

College of Computer,National University of Defense Technology

Guangxi Key Laboratory of Trust Software, Guilin University of Electronic Technology

AI问答

⁰