Resource bundles: Using aggregation for statistical wide-area resource discovery and allocation

Michael Cardosa, Abhishek Chandra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

Resource discovery is an important process for finding suitable nodes that satisfy application requirements in large loosely-coupled distributed systems. Besides inter-node heterogeneity, many of these systems also show a high degree of intra-node dynamism, so that selecting nodes based only on their recently observed resource capacities for scalability reasons can lead to poor deployment decisions resulting in application failures or migration overheads. In this paper, we propose the notion of a resource bundle-a representative resource usage distribution for a group of nodes with similar resource usage patterns-that employs two complementary techniques to overcome the limitations of existing techniques: resource usage histograms to provide statistical guarantees for resource capacities, and clustering-based resource aggregation to achieve scalability. Using trace-driven simulations and data analysis of a month-long PlanetLab trace, we show that resource bundles are able to provide high accuracy for statistical resource discovery (up to 56% better precision than using only recent values), while achieving high scalability (up to 55% fewer messages than a non-aggregation algorithm). We also show that resource bundles are ideally suited for identifying group-level characteristics such as finding load hot spots and estimating total group capacity (within 8% of actual values).

Original languageEnglish (US)
Title of host publicationProceedings - The 28th International Conference on Distributed Computing Systems, ICDCS 2008
Pages760-768
Number of pages9
DOIs
StatePublished - 2008
Event28th International Conference on Distributed Computing Systems, ICDCS 2008 - Beijing, China
Duration: Jul 17 2008Jul 20 2008

Publication series

NameProceedings - The 28th International Conference on Distributed Computing Systems, ICDCS 2008

Other

Other28th International Conference on Distributed Computing Systems, ICDCS 2008
CountryChina
CityBeijing
Period7/17/087/20/08

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