Slicing algorithm based on resource sharing evaluation and user security rating under cloud network integration

doi:10.12267/j.issn.2096-5931.2022.11.006

Abstract

Abstract:

With the development of cloud network integration architecture, cloud network slicing realizes the unified management and allocation of network resources, but the arrangement of cloud network slicing sharing resources exposes the risk of information leakage. This paper proposes a slicing algorithm based on resource sharing and user security rating, which maximizes the benefits of the slicing and makes the slicing meet the requirements of a certain mapping security level, and ensures that the deployed slicing meets the requirements of security performance. Experiments show that this algorithm can improve the satisfaction rate, resource utilization rate and cost profit rate of the orchestration.

Key words: cloud-network convergence, network slicing, security performance

CLC Number:

TP393.0文献标志码:A

LUO Yiming, QUAN Wei. Slicing algorithm based on resource sharing evaluation and user security rating under cloud network integration[J]. Information and Communications Technology and Policy, 2022, 48(11): 39-45.

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URL:

http://ictp.caict.ac.cn/EN/10.12267/j.issn.2096-5931.2022.11.006

http://ictp.caict.ac.cn/EN/Y2022/V48/I11/39

Figures/Tables 5

参数	取值/个
优先级队列 $Q$ 的长度 $w$	50
影响范围参数 $β$	10
处罚系数 $p i$	5
处罚程度 $a$	2
评级变化程度 $k$	5
单位带宽收益 $p$	7~10
非切片用途的单位带宽收益 $b$	2
单位CPU收益 $d$	3
惯性系数 $ω$	1.4
学习参数 $c 1$	2
学习参数 $c 2$	2
粒子数 $X$	40
迭代次数 $N$	50
安全门限 $γ$	0.3

参数	取值/个
优先级队列 $Q$ 的长度 $w$	50
影响范围参数 $β$	10
处罚系数 $p i$	5
处罚程度 $a$	2
评级变化程度 $k$	5
单位带宽收益 $p$	7~10
非切片用途的单位带宽收益 $b$	2
单位CPU收益 $d$	3
惯性系数 $ω$	1.4
学习参数 $c 1$	2
学习参数 $c 2$	2
粒子数 $X$	40
迭代次数 $N$	50
安全门限 $γ$	0.3

References 20

[1]	中国电信集团公司. 云网融合2030技术白皮书[R], 2020.
[2]	NGMN Alliance. 5G white paper[R], 2015.
[3]	Network Functions Virtualisation. Introductory white paper[J]. SDN and OpenFlow World Congress, 2012(10):22-24.
[4]	LI E L, MAO Z M, REXFORD J. Toward software-defined cellular networks[C]// European Workshop on Software Defined Networking. IEEE Computer Society, 2012.
[5]	HUANG H, GUO So, WU J, et al. Service chaining for hybrid network function[J]. IEEE Transactions on Cloud Computing, 2017: 1-1.
[6]	SALLENT O, PEREZ-ROMERO J, FERRUS R, et al. On radio access network slicing from a radio resource management perspective[J]. IEEE Wireless Communications, 2017, 24(5):166-174. doi: 10.1109/MWC.2017.1600220WC URL
[7]	RISTENPART T, TROMER E, SHACHAM H, et al. Hey, you, get off of my cloud: exploring information leakage in third-party compute clouds[C]// CSS, ACM Conference on Computer and Communications Security, University of California, 2009.
[8]	ALJUHANI A, ALHARBI T. Virtualized network functions security attacks and vulnerabilities[C]// Computing & Communication Workshop & Conference. IEEE, 2017:1-4.
[9]	PATOUNAS, GEORGIOS, MARINA, et al. Network slicing in 5G: survey and challenges[J]. IEEE Communications Magazine: Articles, News, and Events of Interest to Communications Engineers, 2017, 55(5):94-100.
[10]	蒋建峰, 张凤岩, 张趁香. 基于SecPSO优化的5G网络切片安全隔离算法[J]. 无线电工程, 2022, 52(3):442-449.
[11]	MOON S, SEKAR V, REITER M K. Nomad: mitigating arbitrary cloud side channels via provider-assisted migration[Z], 2015.
[12]	LIANG X, GUI X, et al. Mitigating cloud co-resident attacks via grouping-based virtual machine placement strategy[C]. IEEE International Performance Computing & Communications Conference, 2017:1-8.
[13]	CAO J, YAN Z, WEI A N, et al. VNF-FG design and VNF placement for 5G mobile networks[J]. 中国科学:信息科学(英文版), 2017, 60(4):15.
[14]	GHAZNAVI M, KHAN A, SHAHRIAR N, et al. Elastic virtual network function placement[C]. IEEE International Conference on Cloud Networking, 2015:255-260.
[15]	KHETTAB Y, BAGAA M, DUTRA D, et al. Virtual security as a service for 5G verticals[C]. IEEE WCNC, 2018.
[16]	QU L, ASSI C, SHABAN K. Delay-aware scheduling and resource optimization with network function virtualization[J]. IEEE Transactions on Communications, 2016, 64(9):1-1. doi: 10.1109/TCOMM.2015.2509298 URL
[17]	ZHU Q, XI Z. Game-theory based buffer-space and transmission-rate allocations for optimal energy-efficiency over wireless virtual networks[C]. IEEE Global Communications Conference, 2015.
[18]	BAUMGARTNER A, REDDY V S, BAUSCHERT T. Mobile core network virtualization: a model for combined virtual core network function placement and topology optimization[C]// Network Softwarization, IEEE, 2015.
[19]	张宏科, 冯博昊, 权伟. 智融标识网络基础研究[J]. 电子学报, 2019, 47(5):977-982.
[20]	杨维, 李歧强. 粒子群优化算法综述[J]. 中国工程科学, 2004, 6(5):8.