Analyzing Enterprise Storage Workloads With Graph Modeling and Clustering

Utilizing graph analysis models and algorithms to exploit complex interactions over a network of entities is emerging as an attractive network analytic technology. In this paper, we show that traditional column or row-based trace analysis may not be effective in deriving deep insights hidden in the...

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Veröffentlicht in:	IEEE journal on selected areas in communications 2016-03, Vol.34 (3), p.551-574
Hauptverfasser:	Yang Zhou, Ling Liu, Seshadri, Sangeetha, Chiu, Lawrence
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithm design and analysis Analytical models Clustering Clustering algorithms Correlation Full-rank Approximation Heterogeneous Trace Graph Optimization Performance evaluation Random Walk Servers Spatial Extent Clustering Temporal Cycle Clustering Unified Weighted Spatial/Temporal Similarity
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