Reliability and Availability Evaluation for Cloud Data Center Networks Using Hierarchical Models

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Abstract
Modeling a cloud computing center is crucial to evaluate and predict its inner connectivity reliability and availability. Many previous studies on system availability/reliability assessment of virtualized systems consisting of singular servers in cloud data centers have been reported. In this paper, we propose a hierarchical modeling framework for the reliability and availability evaluation of tree-based data center networks. The hierarchical model consists of three layers, including 1) reliability graphs in the top layer to model the system network topology; 2) a fault-tree to model the architecture of the subsystems; and 3) stochastic reward nets to capture the behaviors and dependency of the components in the subsystems in detail. Two representative data center networks based on three-tier and fat-tree topologies are modeled and analyzed in a comprehensive manner. We specifically consider a number of case-studies to investigate the impact of networking and management on cloud computing centers. Furthermore, we perform various detailed analyses with regard to reliability and availability measures for the system models. The analysis results show that appropriate networking to optimize the distribution of nodes within the data center networks can enhance the reliability/availability. The conclusion of this paper can be used toward the practical management and the construction of cloud computing centers.
Funding Information
  • Konkuk University
  • Ministry of Science and ICT (MSIT), South Korea, through the Information Technology Research Center Support Program (IITP-2018-2016-0-00465)
  • Institute for Information and Communications Technology Promotion
  • IITP through the Korea Government Development of a Traffic Predictive Simulation SW for Improving the Urban Traffic Congestion (MSIT 2017-0-00121)
  • Project CS19.10 managed by the Institute of Information Technology
  • Ministry of Trade, Industry and Energy
  • Korean Institute for Advancement of Technology (N0002431)

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