Cognitive Visual Analytics of Multi-Dimensional Cloud System Monitoring Data

Author:

Baciu George1,Wang Yungzhe2,Li Chenhui2

Affiliation:

1. GAMA Lab, Department of Computing, Hong Kong Polytechnic University, Hung Hom, Hong Kong

2. Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong

Abstract

Hardware virtualization has enabled large scale computational service delivery models with high cost leverage and improved resource utilization on cloud computing platforms. This has completely changed the landscape of computing in the last decade. It has also enabled large–scale data analytics through distributed high performance computing. Due to the infrastructure complexity, end–users and administrators of cloud platforms can rarely obtain a full picture of the state of cloud computing systems and data centers. Recent monitoring tools enable users to obtain large amounts of data with respect to many utilization parameters of cloud platforms. However, they fail to get the maximal overall insight into the resource utilization dynamics of cloud platforms. Furthermore, existing tools make it difficult to observe large-scale patterns, making it difficult to learn from the past behavior of cloud system dynamics. In this work, the authors describe a perceptual-based interactive visualization platform that gives users and administrators a cognitive view of cloud computing system dynamics.

Publisher

IGI Global

Reference34 articles.

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2. Cloudet

3. Belkin, M., & Niyogi, P. (2001). Laplacian eigenmaps and spectral techniques for embedding and clustering. Proceedings of NIPS (Vol. 14, pp. 585–591).

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