ClusVNFI: A Hierarchical Clustering-Based Approach for Solving VNFI Dilemma in NFV Orchestration

被引:3
作者
Chen, Jing [1 ]
Chen, Jia [1 ]
Hu, Renkun [1 ]
Zhang, Hongke [1 ]
机构
[1] Beijing Jiaotong Univ, Dept Elect & Informat Engn, Beijing 100044, Peoples R China
关键词
Clustering; orchestration; multi-objective; VNFI; hierarchical; SERVICE; OPTIMIZATION; PLACEMENT;
D O I
10.1109/ACCESS.2019.2956502
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Network functions virtualization (NFV) is becoming a prevailing design for future Internet by migrating network functions from dedicated hardware appliances to software instances running in virtual computing platforms. NFV resource allocation approaches can dynamically instantiate network functions by using virtualized network functions (VNFs) to satisfy various quality-of-service (QoS) requirements with minimum network costs. The operator can launch a new VNF instance (VNFI) for each VNF required for flows, or assign it to the established VNFI. This makes NFV orchestration (NFVO) even more complicated. In addition, the challenges of developing NFVO scheme include how to manage the dependency between VNFs placement (network-level) and routing of flows (flow-level) through ordered VNFs, and how to efficiently utilize the available network resources. In this paper, ClusVNFI, a hierarchical resource allocation approach based on clustering, is proposed to address these challenges. To be specific, VNFs are proposed to be clustered based on their correlation. Then VNFs belonging to the same cluster are inclined to be deployed on one node to reduce the occupied link bandwidth. Moreover, network nodes are clustered based on the similarity on end-to-end flow latency information. Accordingly, flows in the same cluster intend to share the instantiated VNFIs, aiming at improving VNFI utilization while avoiding path stretch. By capturing the dependency between network-level and flow-level through clustering, ClusVNFI can achieve the tradeoff among multiple objectives including maximizing the number of admitted flows, minimizing path stretch, and improving VNFI utilization. Extensive simulation results show that the proposed ClusVNFI can balance multiple objectives comparing with other typical heuristic algorithms. Moreover, ClusVNFI can reduce network resource occupation effectively, while guaranteeing the average delay and network hops.
引用
收藏
页码:173257 / 173272
页数:16
相关论文
共 50 条
  • [11] Fuzzy Clustering-Based Approach for Outlier Detection
    Al-Zoubi, Moh'd Belal
    Ali, Al-Dahoud
    Yahya, Abdelfatah A.
    RECENT ADVANCES AND APPLICATIONS OF COMPUTER ENGINEERING: PROCEEDINGS OF THE 9TH WSEAS INTERNATIONAL CONFERENCE (ACE 10), 2010, : 192 - +
  • [12] A Clustering-Based Approach to Reduce Feature Redundancy
    de Amorim, Renato Cordeiro
    Mirkin, Boris
    KNOWLEDGE, INFORMATION AND CREATIVITY SUPPORT SYSTEMS: RECENT TRENDS, ADVANCES AND SOLUTIONS, KICSS 2013, 2016, 364 : 465 - 475
  • [13] A Multi-Objective Evolutionary Algorithm With Hierarchical Clustering-Based Selection
    Zhou, Shenghao
    Chen, Ze
    Li, Qi
    Gu, Mengjun
    Bao, Zhoucheng
    He, Wenda
    Sheng, Weiguo
    IEEE ACCESS, 2023, 11 : 2557 - 2569
  • [14] A Novel Clustering-Based Approach of Indoor Location Fingerprinting
    Lee, Chung-Wei
    Lin, Tsung-Nan
    Fang, Shih-Hau
    Chou, Yen-Chih
    2013 IEEE 24TH INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR, AND MOBILE RADIO COMMUNICATIONS (PIMRC), 2013, : 3191 - 3196
  • [15] A CLUSTERING-BASED APPROACH FOR EVALUATION OF EO IMAGE INDEXING
    Bahmanyar, Reza
    Rigoll, Gerhard
    Datcu, Mihai
    SMPR CONFERENCE 2013, 2013, 40-1-W3 : 79 - 84
  • [16] An efficient clustering-based segmentation approach for biometric image
    Shukla A.
    Kanungo S.
    Recent Advances in Computer Science and Communications, 2021, 14 (03) : 803 - 819
  • [17] A clustering-based approach to predict outcome in cancer patients
    Xing, Kai
    Chen, Dechang
    Henson, Donald
    Sheng, Li
    ICMLA 2007: SIXTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, PROCEEDINGS, 2007, : 541 - +
  • [18] A clustering-based obstacle segmentation approach for urban environments
    Ridel, Daniela A.
    Shinzato, Patrick Y.
    Wolf, Denis F.
    2015 12TH LATIN AMERICAN ROBOTICS SYMPOSIUM AND 2015 3RD BRAZILIAN SYMPOSIUM ON ROBOTICS (LARS-SBR), 2015, : 265 - 270
  • [19] A mixed clustering-based approach for a territorial hydrological regionalization
    Oumaima Rami
    Moulay Driss Hasnaoui
    Driss Ouazar
    Ahmed Bouziane
    Arabian Journal of Geosciences, 2022, 15 (1)
  • [20] LQG Control of Large Networks: A Clustering-Based Approach
    Xue, Nan
    Chakrabortty, Aranya
    2017 AMERICAN CONTROL CONFERENCE (ACC), 2017, : 2333 - 2338