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Issue No.05 - May (2012 vol.23)

pp: 902-912

Yulei Wu , University of Bradford, Bradford

Geyong Min , University of Bradford, Bradford

Keqiu Li , Dalian University of Technology, Dalian

Bahman Javadi , The University of Melbourne, Melbourne

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.198

ABSTRACT

Multicluster systems have emerged as a promising infrastructure for provisioning of cost-effective high-performance computing and communications. Analytical models of communication networks in cluster systems have been widely reported. However, for tractability and simplicity, the existing models are based on the assumptions that the network traffic follows the nonbursty Poisson arrival process and the message destinations are uniformly distributed. Recent measurement studies have shown that the traffic generated by real-world applications reveals the bursty nature in both the spatial domain (i.e., nonuniform distribution of message destinations) and temporal domain (i.e., bursty message arrival process). In order to obtain a comprehensive understanding of the system performance, a novel analytical model is developed for communication networks in multicluster systems in the presence of the spatio-temporal bursty traffic. The spatial traffic burstiness is captured by the communication locality and the temporal traffic burstiness is modeled by the Markov-modulated Poisson process. After validating its accuracy through extensive simulation experiments, the model is used to investigate the impact of bursty message arrivals and communication locality on network performance. The analytical results demonstrate that the communication locality can relieve the degrading effects of bursty message arrivals on the network performance.

INDEX TERMS

Cluster computing, bursty traffic, communication locality, fat tree, performance modeling.

CITATION

Yulei Wu, Geyong Min, Keqiu Li, Bahman Javadi, "Modeling and Analysis of Communication Networks in Multicluster Systems under Spatio-Temporal Bursty Traffic",

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