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IPMI-based Efficient Notification Framework for Large Scale Cluster Computing
Singapore May 16-May 19
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CCGRID.2006.150Sixth IEEE International Symposium on ...
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Chokchia Leangsuksun, Louisiana Tech University, USA
Tirumala Rao, Louisiana Tech University, USA
Anand Tikotekar, Louisiana Tech University, USA
Stephen L. Scott, Oak Ridge National Laboratory, USA
Richard Libby, Intel Corporation, USA
Jeffrey S. Vetter, Intel Corporation, USA
Yung-Chin Fang, Dell, Inc., USA
Hong Ong, Oak Ridge National Laboratory, USA
The demand for an efficient Jhult tolerance system has led to the development of complex monitoring infrastructure, which in turn has created an overwhelming task of data and event management. The increasing level of details at the hardware and software layer clearly afects the scalability and peijbrmance of monitoring and management tools. In this paper, we propose a problem notiJication framework that directly addresses the issue of monitor scalability. We first present the design and inzpIementation of our step-by-step approach to analyzing, filtering, and clas,slfiing the plethora of node statistics. Then, we present experimental results to show that our approach only needs minimal system resource and thus has low overhead. Finally, we introduce our web-based cluster management system that provides hardware controls at both cluster and nodal levels.
Index Terms:
Scalability, High-Availability, IPM.
Citation:
Chokchia Leangsuksun, Tirumala Rao, Anand Tikotekar, Stephen L. Scott, Richard Libby, Jeffrey S. Vetter, Yung-Chin Fang, Hong Ong, "IPMI-based Efficient Notification Framework for Large Scale Cluster Computing," ccgrid, vol. 2, pp.23, Sixth IEEE International Symposium on Cluster Computing and the Grid Workshops (CCGRIDW'06), 2006
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