Add to ORKGAbstract:-In this paper, we propose a new solution for data mining task scheduling in Grid environment. First, we propose a sample-based application run time evaluation. Then, we propose a cost model for predicting the data transfer time on Grid. Finally, according the priori estimation of the application response time and the data transfer time, we propose the method for tasks scheduling in grid environment
Grid computing has emerged from category of distributed and parallel computing where the heterogeneo...
Abstract In large Grids, like the National Grid Service (NGS), or large distributed architecture dif...
An efficient functioning of a complicated and dynamic grid environment requires a resource manager t...
Abstract:- Grid is a solution to computationally and data intensive computing problems. Since the di...
Abstract. Increasingly the datasets used for data mining are becoming huge and physically distribute...
Increasingly the datasets used for data mining are huge and physically distributed
Abstract:- Distributed data mining plays a crucial role in knowledge discovery in very large databas...
GRID environments are privileged targets for computation-intensive problem solving in areas from wea...
Grid computing is the form of distributed computing where the resources of various computers are sha...
Navigation or dynamic scheduling of applications on computational grids can be improved through the ...
Grid computing is a type of distributed computing that distributes the tasks to a group of network c...
Abstract. Task Scheduling is a critical design issue of distributed computing. The emerging Grid com...
The integration of remote and diverse resources and the increasing computational needs of Grand chal...
Abstract: In order to improve the performance of Data Mining applications, an effective method is ta...
Since the mid 1990s, grid computing systems have emerged as an analogy for making computing power as...
Grid computing has emerged from category of distributed and parallel computing where the heterogeneo...
Abstract In large Grids, like the National Grid Service (NGS), or large distributed architecture dif...
An efficient functioning of a complicated and dynamic grid environment requires a resource manager t...
Abstract:- Grid is a solution to computationally and data intensive computing problems. Since the di...
Abstract. Increasingly the datasets used for data mining are becoming huge and physically distribute...
Increasingly the datasets used for data mining are huge and physically distributed
Abstract:- Distributed data mining plays a crucial role in knowledge discovery in very large databas...
GRID environments are privileged targets for computation-intensive problem solving in areas from wea...
Grid computing is the form of distributed computing where the resources of various computers are sha...
Navigation or dynamic scheduling of applications on computational grids can be improved through the ...
Grid computing is a type of distributed computing that distributes the tasks to a group of network c...
Abstract. Task Scheduling is a critical design issue of distributed computing. The emerging Grid com...
The integration of remote and diverse resources and the increasing computational needs of Grand chal...
Abstract: In order to improve the performance of Data Mining applications, an effective method is ta...
Since the mid 1990s, grid computing systems have emerged as an analogy for making computing power as...
Grid computing has emerged from category of distributed and parallel computing where the heterogeneo...
Abstract In large Grids, like the National Grid Service (NGS), or large distributed architecture dif...
An efficient functioning of a complicated and dynamic grid environment requires a resource manager t...