By Topic

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

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

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