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Automated and dynamic application accuracy management and resource provisioning in a cloud environment

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3 Author(s)
Vijayakumar, S. ; Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH, USA ; Qian Zhu ; Agrawal, G.

The recent emergence of cloud computing is making the vision of utility computing realizable, i.e., computing resources and services from a cloud can be delivered, utilized, and paid for in the same fashion as utilities like water or electricity. This, however, creates new resource provisioning problems. Because of the pay-as-you-go model, resource provisioning should be performed carefully. Resource provisioning can be particularly challenging for adaptive applications, where there can be a tradeoff between the application Quality of Service (QoS), or accuracy, and the resource costs incurred. In this paper, we consider adaptive streaming applications where a user wants to achieve the minimum resource costs while maintaining a specified accuracy goal. We present a dynamic and automated framework which can adapt the adaptive parameters to meet the specific accuracy goal, and then dynamically converge to near-optimal resource allocation. Our solution can handle unexpected changes in the data distribution characteristics and/or rates. We evaluate our approach using two streaming applications and demonstrate the effectiveness of our framework.

Published in:

Grid Computing (GRID), 2010 11th IEEE/ACM International Conference on

Date of Conference:

25-28 Oct. 2010