Decision-Tree Placement Algorithm for Containerized VoIP VNFs: A Network Management Approach

被引:0
|
作者
Gedia, Dewang [1 ]
Perigo, Levi [2 ]
机构
[1] Univ Colorado, Interdisciplinary Telecom Program, Boulder, CO 80309 USA
[2] Univ Colorado, Comp Sci Dept, Boulder, CO USA
关键词
Algorithm; cAdvisor; Container; Docker; Netperf; Node Exporter; OpenSIPS; Prometheus; !text type='Python']Python[!/text; VNF;
D O I
10.1109/ICIN53892.2022.9758119
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Prior work identified that the Decision-Tree (DT) algorithm allocates the best placement location for a containerized software-defined networking controller virtual network function (SDN-VNF). However, this identification and placement criteria was restricted to OpenFlow network architectures. To address this limitation, this study enhances the DT algorithm to identify the optimal containerized VNF placement location for a Voice over Internet Protocol (VoIP) VNF, thus expanding the applicability of the DT algorithm to incorporate UDP networks carrying Session Initiation Protocol (SIP) packets. To validate the enhancement, this study compares two approaches for implementing the DT algorithm: first, using Netperf, and second, using a northbound Python application. The results indicate the DT algorithm offers significantly smaller and near-constant lead time (time required to identify the best placement location) when it is coupled with a northbound Python application compared to the Netperf approach. Furthermore, the second approach using the northbound Python application removes any Linux Operating System (OS) dependency (required with Netperf), which further benefits its adoption in multi-faceted VoIP networks. The outcome of this research enhances the body of knowledge on implementing optimal containerized VNF placement algorithms.
引用
收藏
页码:116 / 120
页数:5
相关论文
共 50 条
  • [21] Application of Decision-Tree Based on Prediction Model for Project Management
    Tu, Xin-ying
    Fu, Tao
    ADVANCED DATA MINING AND APPLICATIONS (ADMA 2010), PT II, 2010, 6441 : 508 - 513
  • [22] Systems approach vs. decision-tree analysis: An offshore development decision
    Al-Harthy, M.
    Khurana, A.
    PETROLEUM SCIENCE AND TECHNOLOGY, 2007, 25 (08) : 1053 - 1064
  • [23] Exploring residential satisfaction in shrinking cities: a decision-tree approach
    Barreira, Ana Paula
    Agapito, Dora
    Panagopoulos, Thomas
    Guimaraes, Maria Helena
    URBAN RESEARCH & PRACTICE, 2017, 10 (02) : 156 - 177
  • [24] Feature-selection ability of the decision-tree algorithm and the impact of feature-selection/extraction on decision-tree results based on hyperspectral data
    Wang, Y. Y.
    Li, J.
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2008, 29 (10) : 2993 - 3010
  • [25] Another decision-tree approach for identification of critical control points
    Bryan, FL
    JOURNAL OF FOOD PROTECTION, 1996, 59 (11) : 1242 - 1247
  • [26] SmartCLIDE design pattern assistant: A decision-tree based approach
    Polyzoidou, Eleni
    Papagiannaki, Evangelia
    Nikolaidis, Nikolaos
    Ampatzoglou, Apostolos
    Mittas, Nikolaos
    Arvanitou, Elvira Maria
    Chatzigeorgiou, Alexander
    Manolis, George
    Manganopoulou, Evdoxia
    SOFTWARE-PRACTICE & EXPERIENCE, 2023, 53 (06): : 1304 - 1331
  • [27] A DECISION-TREE APPROACH TO THE LURIA-NEBRASKA NEUROPSYCHOLOGICAL BATTERY
    WEBSTER, JS
    DOSTROW, V
    SCOTT, RR
    CLINICAL NEUROPSYCHOLOGY, 1984, 6 (01): : 17 - 21
  • [28] Design of fuzzy classification system based on decision-tree and genetic algorithm
    School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China
    Dongnan Daxue Xuebao, 2006, SUPPL. (23-26):
  • [29] Classification of nicotine-dependent users in India: a decision-tree approach
    Akansha Singh
    Himanshu Katyan
    Journal of Public Health, 2019, 27 : 453 - 459
  • [30] An automated decision-tree approach to predicting protein interaction hot spots
    Darnell, Steven J.
    Page, David
    Mitchell, Julie C.
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2007, 68 (04) : 813 - 823