Abstract—As for the problem of how to carry out task scheduling and data replication effectively in the grid and to reduce task’s execution time, this thesis proposes the task scheduling algorithm and the optimum dynamic data replication algorithm and builds a scheme to effectively combine these two algorithms. First of all, the scheme adopts the ISS algorithm considering the number of tasks waiting queue, the location of task demand data and calculation capacity of site by adopting the method of network structure’s hierarchical scheduling to calculate the cost of comprehensive task with the proper weight efficiency and search out the best compute node area. And then the algorithm of ODHRA is adopted to analyze the data transmission time, m...
Abstract. Task Scheduling is a critical design issue of distributed computing. The emerging Grid com...
Data Grid is composed of a large number of distributed computation and storage resources to facilita...
One typical use case of large-scale distributed computing in data centers is to decompose a computat...
Grid computing is an effective distributed and adaptable processing network that manages a huge numb...
Grid technology, which together a number of personal computer clusters with high speed networks, can...
In data grids huge amount of data are generated and processed by users around the world. Objective o...
Data Grids deal with geographically-distributed large-scale data-intensive applications. Schemes sch...
In data-intensive applications data transfer is a primary cause of job execution delay. Data access ...
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and...
In data-intensive applications data transfer is a primary cause of job execution delay. Data access ...
ABSTRACT Data Grid environment is a geographically distributed that deal with date-intensive applic...
Grid computing is a powerful distributed and scalable computing infrastructure that deals with massi...
Abstract: A Data Grid connects a collection of geographically distributed computational and storage ...
Abstract--Grid computing provides virtual organizations of geographically distributed users with sof...
In data grids scientific and business applications produce huge volume of data which needs to be tra...
Abstract. Task Scheduling is a critical design issue of distributed computing. The emerging Grid com...
Data Grid is composed of a large number of distributed computation and storage resources to facilita...
One typical use case of large-scale distributed computing in data centers is to decompose a computat...
Grid computing is an effective distributed and adaptable processing network that manages a huge numb...
Grid technology, which together a number of personal computer clusters with high speed networks, can...
In data grids huge amount of data are generated and processed by users around the world. Objective o...
Data Grids deal with geographically-distributed large-scale data-intensive applications. Schemes sch...
In data-intensive applications data transfer is a primary cause of job execution delay. Data access ...
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and...
In data-intensive applications data transfer is a primary cause of job execution delay. Data access ...
ABSTRACT Data Grid environment is a geographically distributed that deal with date-intensive applic...
Grid computing is a powerful distributed and scalable computing infrastructure that deals with massi...
Abstract: A Data Grid connects a collection of geographically distributed computational and storage ...
Abstract--Grid computing provides virtual organizations of geographically distributed users with sof...
In data grids scientific and business applications produce huge volume of data which needs to be tra...
Abstract. Task Scheduling is a critical design issue of distributed computing. The emerging Grid com...
Data Grid is composed of a large number of distributed computation and storage resources to facilita...
One typical use case of large-scale distributed computing in data centers is to decompose a computat...