Sierpinski triangle based data center architecture in cloud computing

Qi, Han, Shiraz, Muhammad, Gani, Abdullah, Whaiduzzaman, Md and Khan, Suleman (2014) Sierpinski triangle based data center architecture in cloud computing. The Journal of Supercomputing, 69 (2). pp. 887-907. ISSN 0920-8542

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Official URL: https://doi.org/10.1007/s11227-014-1187-9

Abstract

Computational clouds are increasingly becoming popular for the provisioning of computing resources and service on demand basis. As a backbone in computational clouds, a set of applications are configured over virtual machines running on a large number of server machines in data center networks (DCNs). Currently, DCNs use tree-based architecture which inherits the problems of limited bandwidth capacity and lower server utilization. This requires a new design of scalable and inexpensive DCN infrastructure which enables high-speed interconnection for exponentially increasing number of client devices and provides fault-tolerant and high network capacity. In this paper, we propose a novel architecture for DCN which uses Sierpinski triangle fractal to mitigate throughput bottleneck in aggregate layers as accumulated in tree-based structure. Sierpinski Triangle Based (STB) is a fault-tolerant architecture which provides at least two parallel paths for each pair of servers. The proposed architecture is evaluated in NS2 simulation. The performance of STB-based architecture is then validated by comparing the results with DCell and BCube DCN architecture. Theoretical analysis and simulation results verify that the proportion of switches to servers is 0.167 in STB, lower than BCube (3.67); the average shortest path length is limited between 5.0 and 6.7, whenever node failure proportion remains between 0.02 and 0.2, shorter than DCell and BCube in a four-level architecture. Network throughput is also increased in STB, which spends 87 s to transfer data than DCell and BCube in a given condition. The simulation results validate the significance of STB based DCN architecture for datacenter in computational clouds.

Item Type: Article
Uncontrolled Keywords: Data center network, Cloud computing, Architecture, Network topology
Subjects: G400 Computer Science
G500 Information Systems
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Elena Carlaw
Date Deposited: 18 Nov 2019 10:43
Last Modified: 18 Nov 2019 10:43
URI: http://nrl.northumbria.ac.uk/id/eprint/41466

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