Resource Overbooking: Using Aggregation Profiling in large scale Resource Discovery
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2011 by IJETT Journal|
|Year of Publication : 2011|
|Authors :Dr.M.Helda Mercy, C.Anand, T.S. Suganya|
Dr.M.Helda Mercy, C.Anand, T.S. Suganya "Resource Overbooking: Using Aggregation Profiling in large scale Resource Discovery". International Journal of Engineering Trends and Technology (IJETT),V1(1):52-54 May to June 2011. ISSN:2231-5381. www.ijettjournal.org. Published by Seventh Sense Research Group.
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 can lead to poor deployment decisions resulting in application failures or migration overheads. However, most existing resource discovery mechanisms rely mainly on recent observations to achieve scalability in large systems. 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 scalabil ity. Using trace - driven simulations and data analysis of a month - long Planet Lab trace, we show that resource bundles are able to provide high accuracy for statistical resource discovery, while achieving high scalability. We also show that resource bundles are ideally suited for identifying group - level characteristics (e.g., hot spots, total group capacity).
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