This paper studies five real-world data intensive workflow applications in the fields of natural language processing, astronomy image analysis, and web data analysis. Data intensiv...
Load balancing is a key concern when developing parallel and distributed computing applications. The emergence of computational grids extends this problem, where issues of cross-d...
Junwei Cao, Daniel P. Spooner, Stephen A. Jarvis, ...
One of the first motivations of using grids comes from applications managing large data sets in field such as high energy physics or life sciences. To improve the global throughput...
Divisible load applications consist of a load, that is input data and associated computation, that can be divided arbitrarily into independent pieces. Such applications arise in m...
Selection of resources for execution of scientific workflows in data grids becomes challenging with the exponential growth of files as a result of the distribution of scientific e...