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Researcher's paper named best at IEEE conference


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July, 2007 — A publication on a self-tuning hierarchical aggregation system by HP Labs researcher Praveen Yalagandula has received the best paper award at the first IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007).

The paper, co-authored by Mike Dahlin of the University of Texas (Austin), proposes a novel self-tuning approach for deciding aggregation aggressiveness in large-scale systems based on observed read and write patterns. Scalable aggregation is a building block for many large-scale distributed applications, including monitoring and resource-scheduling.

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In their work, Shruti: A Self-tuning Hierarchical Aggregation System, the researchers explain that current aggregation systems either have a single in-built aggregation mechanism or require applications to specify an aggregation policy a priori. Because it is hard to predict the read and write access patterns in large systems, applications that are built on such systems suffer from inefficient network usage.

The paper demonstrates a general approach for self-tuning the aggregation aggressiveness to the measured workload in the system that is aimed at optimizing the overall communication costs (e.g., the number of messages exchanged on read and write operations). Such self-organizing and self-healing approaches are key to building distributed systems that are more efficient and robust, the authors say.

Yalagandula joined HP Labs' Mobile and Media Systems Lab in 2005 after completing his PhD from the university of Texas at Austin. His research interests are in large-scale distributed systems and networking.

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