Kepler: An Extensible System for Design and Execution of Scientific Workflows
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
VisTrails: visualization meets data management
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Workflows for e-Science: Scientific Workflows for Grids
Workflows for e-Science: Scientific Workflows for Grids
Proceedings of the 5th IEEE workshop on Challenges of large applications in distributed environments
Provenance for Computational Tasks: A Survey
Computing in Science and Engineering
Nimrod/K: towards massively parallel dynamic grid workflows
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Scientific Workflow Systems for 21st Century, New Bottle or New Wine?
SERVICES '08 Proceedings of the 2008 IEEE Congress on Services - Part I
On the Use of Cloud Computing for Scientific Workflows
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
A break in the clouds: towards a cloud definition
ACM SIGCOMM Computer Communication Review
A Task Abstraction and Mapping Approach to the Shimming Problem in Scientific Workflows
SCC '09 Proceedings of the 2009 IEEE International Conference on Services Computing
Exploring many task computing in scientific workflows
Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers
Nephele: efficient parallel data processing in the cloud
Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers
An evolutionary game theoretic approach to adaptive and stable application deployment in clouds
Proceedings of the 2nd workshop on Bio-inspired algorithms for distributed systems
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
Case study for running HPC applications in public clouds
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Exploring the Performance Fluctuations of HPC Workloads on Clouds
CLOUDCOM '10 Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science
Performance Analysis of High Performance Computing Applications on the Amazon Web Services Cloud
CLOUDCOM '10 Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science
A Performance Evaluation of X-Ray Crystallography Scientific Workflow Using SciCumulus
CLOUD '11 Proceedings of the 2011 IEEE 4th International Conference on Cloud Computing
Parallelism in bioinformatics workflows
VECPAR'04 Proceedings of the 6th international conference on High Performance Computing for Computational Science
A Provenance-based Adaptive Scheduling Heuristic for Parallel Scientific Workflows in Clouds
Journal of Grid Computing
Using domain-specific data to enhance scientific workflow steering queries
IPAW'12 Proceedings of the 4th international conference on Provenance and Annotation of Data and Processes
Enabling re-executions of parallel scientific workflows using runtime provenance data
IPAW'12 Proceedings of the 4th international conference on Provenance and Annotation of Data and Processes
Capturing and querying workflow runtime provenance with PROV: a practical approach
Proceedings of the Joint EDBT/ICDT 2013 Workshops
Dimensioning the virtual cluster for parallel scientific workflows in clouds
Proceedings of the 4th ACM workshop on Scientific cloud computing
Performance evaluation of parallel strategies in public clouds: A study with phylogenomic workflows
Future Generation Computer Systems
Designing a parallel cloud based comparative genomics workflow to improve phylogenetic analyses
Future Generation Computer Systems
Hi-index | 0.00 |
Many of the existing large-scale scientific experiments modeled as scientific workflows are compute-intensive. Some scientific workflow management systems already explore parallel techniques, such as parameter sweep and data fragmentation, to improve performance. In those systems, computing resources are used to accomplish many computational tasks in high performance environments, such as multiprocessor machines or clusters. Meanwhile, cloud computing provides scalable and elastic resources that can be instantiated on demand during the course of a scientific experiment, without requiring its users to acquire expensive infrastructure or to configure many pieces of software. In fact, because of these advantages some scientists have already adopted the cloud model in their scientific experiments. However, this model also raises many challenges. When scientists are executing scientific workflows that require parallelism, it is hard to decide a priori the amount of resources to use and how long they will be needed because the allocation of these resources is elastic and based on demand. In addition, scientists have to manage new aspects such as initialization of virtual machines and impact of data staging. SciCumulus is a middleware that manages the parallel execution of scientific workflows in cloud environments. In this paper, we introduce an adaptive approach for executing parallel scientific workflows in the cloud. This approach adapts itself according to the availability of resources during workflow execution. It checks the available computational power and dynamically tunes the workflow activity size to achieve better performance. Experimental evaluation showed the benefits of parallelizing scientific workflows using the adaptive approach of SciCumulus, which presented an increase of performance up to 47.1%. Copyright © 2011 John Wiley & Sons, Ltd.