On Using Physical Programming for Multi-Domain SFC Placement With Limited Visibility

被引:5
作者
Toumi, Nassima [1 ]
Bernier, Olivier [2 ]
Meddour, Djamal-Eddine [2 ]
Ksentini, Adlen [3 ]
机构
[1] Orange, F-22300 Lannion, France
[2] EURECOM, Commun Syst Dept, F-06410 Sophia Antipolis, France
[3] EURE COM, Commun Syst Dept, F-06410 Sophia Antipolis, France
关键词
Service function chaining; multi-domain; multi objective optimization; physical programming; network function virtualization; software defined networks; LOW LATENCY; OPTIMIZATION; SECURITY; NETWORK;
D O I
10.1109/TCC.2020.3046997
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Service Function Chaining (SFC) is a networking concept by which traffic is steered through a set of ordered functions composing an end-to-end service. It represents one of the facilitating technologies for 5G, and is enabled by the Network Function Virtualization (NFV) and Software Defined Networks (SDN) paradigms. In the multi-domain context, SFC placement faces new challenges related to the lack of visibility on the local domain's networks. Indeed, the domain operators are often reluctant to unveil details on their topology to external parties. Furthermore, the new 5G use cases introduce new requirements for services such as end-to-end latency, and a minimal guaranteed bandwidth that the placement process needs to optimize simultaneously. In this article, we propose a centralized framework that allows SFC partitioning and embedding over multiple domains with a limited visibility over the global infrastructure. We model the multi-objective SFC placement problem using the Physical Programming method, which allows the expression of the Decision Maker's preferences through meaningful parameters, and propose an exact algorithm as well as a scalable heuristic solution. We then perform an extensive evaluation of the framework as well as the proposed algorithms. The results demonstrate our solution's effectiveness with a limited visibility on the network.
引用
收藏
页码:2787 / 2803
页数:17
相关论文
共 37 条
  • [1] 3GPP, Technical specification group radio access network
  • [2] study on nonorthogonal multiple access (NOMA) for NR
  • [3] Abujoda A, 2016, INT CONF COMMUN SYST
  • [4] An improved physical programming method for multi-objective inverse problems
    An, Siguang
    Yang, Shiyou
    Bai, Yanan
    Wu, Xiushan
    [J]. INTERNATIONAL JOURNAL OF APPLIED ELECTROMAGNETICS AND MECHANICS, 2016, 52 (3-4) : 1151 - 1159
  • [5] [Anonymous], 2020, LINEARIZATION PRODUC
  • [6] [Anonymous], 2020, NETWORKX
  • [7] [Anonymous], 2020, AZURE IOT EDGE
  • [8] [Anonymous], 2020, AWS IOT GREENGRASS
  • [9] An Interactive Fuzzy Physical Programming for Solving Multiobjective Skip Entry Problem
    Chai, Runqi
    Savvaris, Al
    Tsourdos, Antonios
    Xia, Yuanqing
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2017, 53 (05) : 2385 - 2398
  • [10] A Comprehensive Survey on Internet of Things (IoT) Toward 5G Wireless Systems
    Chettri, Lalit
    Bera, Rabindranath
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2020, 7 (01) : 16 - 32