A Comprehensive Sensitivity Analysis of a Data Center Network with Server Virtualization for Business Continuity. (25th October 2015)

• Record Type: Journal Article
• Authors: Nguyen, Tuan Anh; Min, Dugki; Park, Jong Sou
• Other Names: Leng Supeng Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2015(2015)
• Publication Date: 2015-10-25
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2015/521289
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Sensitivity assessment of availability for data center networks (DCNs) is of paramount importance in design and management of cloud computing based businesses. Previous work has presented a performance modeling and analysis of a fat-tree based DCN using queuing theory. In this paper, we present a comprehensive availability modeling and sensitivity analysis of a DCell-based DCN with server virtualization for business continuity using stochastic reward nets (SRN). We use SRN in modeling to capture complex behaviors and dependencies of the system in detail. The models take into account (i) two DCell configurations, respectively, composed of two and three physical hosts in a DCell0 unit, (ii) failure modes and corresponding recovery behaviors of hosts, switches, and VMs, and VM live migration mechanism within and between DCell0 s, and (iii) dependencies between subsystems (e.g., between a host and VMs and between switches and VMs in the same DCell0 ). The constructed SRN models are analyzed in detail with regard to various metrics of interest to investigate system's characteristics. A comprehensive sensitivity analysis of system availability is carried out in consideration of the major impacting parameters in order to observe the system's complicated behaviors and find the bottlenecks of system availability. The analysis results show the availability improvement, capability of fault tolerance, and business continuity of the DCNs complying with DCell network topology. This study provides a basis of designing and management of DCNs for business continuity.