性能感知的核心网控制面资源分配算法

doi:10.3785/j.issn.1008-973X.2021.09.020

浙江大学学报(工学版)

2021, Vol. 55

Issue (9): 1782-1787 DOI: 10.3785/j.issn.1008-973X.2021.09.020

计算机与信息工程

性能感知的核心网控制面资源分配算法

陈俊杰1,2(

),李洪均1,曹张华1

1. 南通大学信息科学技术学院，江苏南通 226019
2. 南通先进通信技术研究院有限公司，江苏南通 226019

Performance-aware resource allocation algorithm for core network control plane

Jun-jie CHEN1,2(

),Hong-jun LI1,Zhang-hua CAO1

1. School of Information Science and Technology, Nantong University, Nantong 226019, China
2. Nantong Research Institute for Advanced Communication Technologies, Nantong 226019, China

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摘要：

针对网络功能虚拟化（NFV）环境下核心网控制面资源分配问题，提出性能感知的资源分配算法. 基于排队网络理论建立核心网控制面性能评估模型，推导出信令流程平均响应时间的近似表达式. 为了确定核心网控制面虚拟网络功能（VNF）实例的最优配置数量，综合考虑处理性能和VNF实例部署成本，建立核心网控制面资源分配多目标优化模型，并提出改进的多目标遗传算法. 仿真结果表明，该性能评估模型误差在10%以内，优于Jackson排队网络模型；与NSGA-II和HaD-MOEA相比，所提算法获得的近似Pareto前沿收敛性和多样性更好，更逼近真实Pareto前沿.

关键词： 核心网; 资源分配; 排队网络; 多目标优化; 拥挤距离

Abstract:

A performance-aware resource allocation algorithm was proposed aiming at the resource allocation problem of the core network control plane in network function virtualization (NFV) environment. Based on the queuing network theory, a performance evaluation model for the control plane was established, and an approximate expression for the average response time of the signaling procedures was derived. Further, considering both the processing performance and the deployment cost of virtual network function (VNF) instances, a multi-objective optimization model was developed for resource allocation of the control plane, and an improved multi-objective genetic algorithm was proposed. Simulation results showed that the error of the performance evaluation model was within 10% and the model was better than the Jackson network model. Compared with NSGA-II and HaD-MOEA, the approximate Pareto front obtained by the proposed algorithm was better in terms of convergence and diversity, and was closer to the real Pareto front.

Key words: core network resource allocation queueing network multi-objective optimization crowding distance

收稿日期: 2020-09-09 出版日期: 2021-10-20

CLC:

TP 915

基金资助: 南通市科技计划资助项目(JC2018025)

作者简介: 陈俊杰(1985—)，男，讲师，博士，从事云计算、5G研究. orcid.org/0000-0003-4219-6171. E-mail： cjjcy@ntu.edu.cn

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引用本文:

陈俊杰,李洪均,曹张华. 性能感知的核心网控制面资源分配算法[J]. 浙江大学学报(工学版), 2021, 55(9): 1782-1787.

Jun-jie CHEN,Hong-jun LI,Zhang-hua CAO. Performance-aware resource allocation algorithm for core network control plane. Journal of ZheJiang University (Engineering Science), 2021, 55(9): 1782-1787.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2021.09.020 或 https://www.zjujournals.com/eng/CN/Y2021/V55/I9/1782

图 1 调和距离的计算

图 2 3种性能分析方法的平均响应时间

图 3 解集的IGD指标值随进化代数的变化情况

表 1 3种算法的IGD和HVR指标值(t=30)

图 4 采用改进多目标遗传算法得到的Pareto前沿

图 5 不同资源分配算法下核心网控制面的处理性能和部署成本

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