학술논문

Dynamic Scheduling Algorithms for Workflow Applications in Grid Environment
Document Type
Conference
Source
2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2009 11th International Symposium on. :254-261 Sep, 2009
Subject
Computing and Processing
General Topics for Engineers
Dynamic scheduling
Heuristic algorithms
Scheduling algorithm
Algorithm design and analysis
Failure analysis
Performance analysis
Delay
Satellites
Image processing
Monitoring
Dynamic Scheduling
Workflow Applications
Grid Environment
Language
Abstract
Implementing efficient dynamic scheduling algorithms is a real challenge but a well designed algorithm can bring a significant performance improvement, regardless of unexpected events that may occur during execution. What is more, analyzing an application's needs and ensuring the most appropriate course of action in case of a delay or failure is bound to offer the best performance for the application in question. This paper presents three dynamic scheduling algorithms for workflows, implemented at application level. The application does satellite image processing, by describing a complex operation as a workflow of elementary operators. The scheduling process described by these algorithms doesn't control the resources directly so it is more natural to consider it closer to Grid applications. The algorithms are responsible for the management of tasks in workflow, such as managing the tasks for parallel execution, managing of data and correlation of events. To fulfill their functions, the scheduling algorithms need information coming from monitoring services available in the execution platform. The platform provides a series of libraries and services as well as a management and execution mechanism which will be used to test each algorithm's efficiency. The comparison between proposed dynamic algorithms and the platform's initial scheduling mechanism highlights the obtained improvements referring to the workflow execution time.