Mining Frequent Subgraphs to Extract Communication Patterns in Data-Centres

In this paper, we propose to use graph-mining techniques to understand the communication pattern within a data-centre. We model the communication observed within a data-centre as a temporal sequence of communication graphs. We present techniques to identify frequently occurring sub-graphs within this temporal sequence of communication graphs. We argue that identification of such frequently occurring subgraphs can provide many useful insights about the functioning of the system. We demonstrate how the existing frequent sub-graph discovery algorithms can be modified for the domain of communication graphs in order to provide computationally light-weight and accurate solutions. We present two algorithms for extracting frequent communication subgraphs and present a detailed experimental evaluation to prove the correctness and efficiency of the proposed algorithms.

• Type: Journal
• Year: 2011
• Where: ICDCN
• Authors: Maitreya Natu, Vaishali P. Sadaphal, Sangameshwar Patil, Ankit Mehrotra
• Keywords: Accurate Solutions, Communication Pattern, Discovery Algorithms, Distributed And Parallel Computing, ICDCN 2011