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FAILSafeFAILSafe: Failure Analysis & Inference in Large-Scale Systems
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FAILSafe: Failure Analysis & Inference in Large-Scale Systems
http://failsafe.cs.umn.edu/
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FAILSafe: Failure Analysis & Inference in Large-Scale Systems
failsafe.cs.umn.edu
FAILSafe
http://failsafe.cs.umn.edu/index.php?page=research
In this work, we try to understand failure characteristics in a large-scale system. We have used PlanetLab system as our case-study and demonstrate how using additional information along-with classification provide us with insights into the nature of some of the failures. Figure 1: Schematic diagraph of two step methodology. Sample Results and Findings. The following figure illustrates the failures occuring in PlanetLab over a 1-month period (Feb'07). Time (each dot: 5 min). Last modified on June 3, 2008.
FAILSafe
http://failsafe.cs.umn.edu/index.php?page=news
We published a technical report. Extracting the Textual and Temporal Structure of Supercomputing Logs. Our paper titled Co-designing the Failure Analysis and Monitoring of Large-Scale Systems. Has been accepted for publication at HotMetrics. First Workshop on Hot Topics in Measurement and Modeling of Computer Systems Co-located with Sigmetrics’08. This project is funded in part through grants from NSF. Last modified on June 1, 2009.
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Sourabh Jain
http://www-users.cs.umn.edu/~sourj
Go to the U of M home page. Department of Computer Science. University of Minnesota-Twin Cities. I am Sourabh. I've completed my PhD at University of Minnesota. In the Department of Computer Science. I am/was a member of Networking Research Group. Led by Prof. Zhi-Li Zhang. I did my undergraduate studies in Computer Science and Engineering at Indian Institute of Technology Roorkee ( IIT-Roorkee. Characterizing Roles of Front-end Servers in End-to-End Performance of Dynamic Content Distribution'. May 15, ...
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FAILSafe
Large-scale distributed systems such as content distribution networks, peer-to-peer systems, computation grids, and network testbeds. The goal of this project is to develop techniques for a better understanding of such failures, in order to identify their possible locations, causes, and to predict their occurrences pre- emptively. This project is funded in part through grants from NSF. Last modified on May 17, 2010.
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