Paper Info
Title
Design of an Adaptive Framework for Utility-Based Optimization of Scientific Applications in the Cloud
Abstract
Cloud computing plays an increasingly important role in realizing scientific applications by offering virtualized compute and storage infrastructures that can scale on demand. In this paper we report on the design of a self-configuring adaptive framework for developing and optimizing scientific applications on top of Cloud technologies. Our framework relies on a MAPE-K loop, known from autonomic computing, for optimizing the configuration of scientific applications taking into account the three abstraction layers of the Cloud stack: the application layer, the execution environment layer, and the resource layer. By evaluating monitored resources, the framework configures the layers and allocates resources on a per job basis. The evaluation of configurations relies on historic data and a utility function that ranks different configurations regarding to the arising costs. The adaptive framework has been integrated into the Vienna Cloud Environment (VCE) and has been evaluated with a MapReduce application.
Year
DOI
Venue
2012
10.1109/UCC.2012.48
Utility and Cloud Computing
Keywords
DocType
ISSN
mapreduce application,abstraction layer,resource layer,scientific application,utility-based optimization,execution environment layer,self-configuring adaptive framework,cloud technology,application layer,scientific applications,adaptive framework,vienna cloud environment,utility,cloud,autonomic computing,cloud computing,adaptive
Conference
2373-6860
ISBN
Citations 
PageRank 
978-1-4673-4432-6
8
0.53
References 
Authors
12
2
Name
Order
Citations
PageRank
Martin Koehler1568.05
Siegfried Benkner261467.47