Sierpinski triangle based data center architecture in cloud computing

Qi Han, Muhammad Shiraz, Abdullah Gani, Md Whaiduzzaman, Suleman Khan

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)887-907
JournalJournal of Supercomputing
Issue number2
Early online date26 Apr 2014
Publication statusPublished - 1 Aug 2014
Externally publishedYes


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