Transparent Throughput Elasticity for Modern Cloud Storage

Author:

Nicolae Bogdan1,Riteau Pierre2,Zhen Zhuo3,Keahey Kate1

Affiliation:

1. Argonne National Laboratory, USA

2. StackHPC, UK

3. University of Chicago, USA

Abstract

Storage elasticity on the cloud is a crucial feature in the age of data-intensive computing, especially when considering fluctuations of I/O throughput. In this chapter, the authors explore how to transparently boost the I/O bandwidth during peak utilization to deliver high performance without over-provisioning storage resources. The proposal relies on the idea of leveraging short-lived virtual disks of better performance characteristics (and more expensive) to act during peaks as a caching layer for the persistent virtual disks where the application data is stored during runtime. They show how this idea can be achieved efficiently at the block-device level, using a caching mechanism that leverages iterative behavior and learns from past experience. Second, they introduce a corresponding performance and cost prediction methodology. They demonstrate the benefits of our proposal both for micro-benchmarks and for two real-life applications using large-scale experiments. They conclude with a discussion on how these techniques can be generalized for increasingly complex landscape of modern cloud storage.

Publisher

IGI Global

Reference55 articles.

1. Cloud Computing and Big Data: A Review of Current Service Models and Hardware Perspectives

2. The maximum intensity of tropical cyclones in axisymmetric numerical model simulations.;G. H.Bryan;Journals of the American Meteorological Society,2009

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