Network Slicing Cost Allocation Model

被引:0
|
作者
Asma Chiha
Marlies Van der Wee
Didier Colle
Sofie Verbrugge
机构
[1] Ghent University-imec,IDLab
关键词
NFV; SDN; Resource allocation; Cost model; 5G; Satellite; Network function resource modelling;
D O I
暂无
中图分类号
学科分类号
摘要
Within the upcoming fifth generation (5G) mobile networks, a lot of emerging technologies, such as Software Defined Network (SDN), Network Function Virtualization (NFV) and network slicing are proposed in order to leverage more flexibility, agility and cost-efficient deployment. These new networking paradigms are shaping not only the network architectures but will also affect the market structure and business case of the stakeholders involved. Due to its capability of splitting the physical network infrastructure into several isolated logical sub-networks, network slicing opens the network resources to vertical segments aiming at providing customized and more efficient end-to-end (E2E) services. While many standardization efforts within the 3GPP body have been made regarding the system architectural and functional features for the implementation of network slicing in 5G networks, techno-economic analysis of this concept is still at a very incipient stage. This paper initiates this techno-economic work by proposing a model that allocates the network cost to the different deployed slices, which can then later be used to price the different E2E services. This allocation is made from a network infrastructure provider perspective. To feed the proposed model with the required inputs, a resource allocation algorithm together with a 5G network function (NF) dimensioning model are also proposed. Results of the different models as well as the cost saving on the core network part resulting from the use of NFV are discussed as well.
引用
收藏
页码:627 / 659
页数:32
相关论文
共 50 条
  • [1] Network Slicing Cost Allocation Model
    Chiha, Asma
    Van der Wee, Marlies
    Colle, Didier
    Verbrugge, Sofie
    [J]. JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT, 2020, 28 (03) : 627 - 659
  • [2] Slicing the Edge: Resource Allocation for RAN Network Slicing
    Phuong Luu Vo
    Minh N H Nguyen
    Nan Anh Le
    Nguyen H Tran
    [J]. IEEE WIRELESS COMMUNICATIONS LETTERS, 2018, 7 (06) : 970 - 973
  • [3] A Resource Allocation Framework for Network Slicing
    Leconte, Mathieu
    Paschos, Georgios S.
    Mertikopoulos, Panayotis
    Kozat, Ulas C.
    [J]. IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (IEEE INFOCOM 2018), 2018, : 2177 - 2185
  • [4] Multi-Resource Allocation for Network Slicing
    Fossati, Francesca
    Moretti, Stefano
    Perny, Patrice
    Secci, Stefano
    [J]. IEEE-ACM TRANSACTIONS ON NETWORKING, 2020, 28 (03) : 1311 - 1324
  • [5] Efficient Network Slicing with Dynamic Resource Allocation
    JI Hong
    ZHANG Tianxiang
    ZHANG Kai
    WANG Wanyuan
    WU Weiwei
    [J]. ZTE Communications, 2021, 19 (01) : 11 - 19
  • [6] Resource Allocation for Network Slicing in Mobile Networks
    Banchs, Albert
    de Veciana, Gustavo
    Sciancalepore, Vincenzo
    Costa-Perez, Xavier
    [J]. IEEE ACCESS, 2020, 8 : 214696 - 214706
  • [7] Constrained Reinforcement Learning for Resource Allocation in Network Slicing
    Xu, Yizhen
    Zhao, Zhengyang
    Cheng, Peng
    Chen, Zhuo
    Ding, Ming
    Vucetic, Branka
    Li, Yonghui
    [J]. IEEE COMMUNICATIONS LETTERS, 2021, 25 (05) : 1554 - 1558
  • [8] Resource Allocation Strategy of IoT based on Network Slicing
    Pang, Xue
    Zhang, Peiying
    [J]. 2020 IEEE COMPUTING, COMMUNICATIONS AND IOT APPLICATIONS (COMCOMAP), 2021,
  • [9] Resource Allocation for Network Slicing in WiFi Access Points
    Richart, Matias
    Baliosian, Javier
    Serrat, Joan
    Gorricho, Juan-Luis
    Aguero, Ramon
    Agoulmine, Nazim
    [J]. 2017 13TH INTERNATIONAL CONFERENCE ON NETWORK AND SERVICE MANAGEMENT (CNSM), 2017,
  • [10] Supervised Learning Based Resource Allocation with Network Slicing
    Zhang, Tianxiang
    Bian, Yuxin
    Lu, Qianchun
    Qi, Jin
    Zhang, Kai
    Ji, Hong
    Wang, Wanyuan
    Wu, Weiwei
    [J]. 2020 EIGHTH INTERNATIONAL CONFERENCE ON ADVANCED CLOUD AND BIG DATA (CBD 2020), 2020, : 25 - 30