There are many challenges in Data Grids, and especially the data replication and the job scheduling are significant problems. There have been many works on the data replication and the job scheduling in Data Grids separately. However, there are still only a few works on solving those two significant problems together in Data Grids. In this work, we propose the optimization model for the co-scheduling problem of the data replication and the job execution in Data Grids, which is more realistic and widely adaptable to real systems. We use 0-1 integer programming model to formulate the co-scheduling problem of the data replication and the job scheduling. Our final goal in this work is to find the optimal solution, that is, the data replication ...
Grid computing is emerging as a new paradigm for solving large-scale problems and is becoming an est...
In data-intensive applications data transfer is a primary cause of job execution delay. Data access ...
Many current international scientific projects are based on large scale applications that are both c...
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and...
Grid is a distributed system that enables dynamic aggregation of geographically dislocated computing...
Abstract. Traditional job schedulers for grid or cluster systems are responsible for assigning incom...
This paper presents a novel Bee Colony based optimization algorithm, named Job Data Scheduling using...
ABSTRACT Data Grid environment is a geographically distributed that deal with date-intensive applic...
Abstract — Managing large datasets has become one major application of grids. Life science applicati...
Data Grids deal with geographically-distributed large-scale data-intensive applications. Schemes sch...
One of the first motivations of using grids comes from applications managing large data sets in fiel...
(eng) One of the first motivations of using grids comes from applications managing large data sets l...
One of the first motivations of using grids comes from applications managing large data sets like fo...
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...
Grid computing is emerging as a new paradigm for solving large-scale problems and is becoming an est...
In data-intensive applications data transfer is a primary cause of job execution delay. Data access ...
Many current international scientific projects are based on large scale applications that are both c...
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and...
Grid is a distributed system that enables dynamic aggregation of geographically dislocated computing...
Abstract. Traditional job schedulers for grid or cluster systems are responsible for assigning incom...
This paper presents a novel Bee Colony based optimization algorithm, named Job Data Scheduling using...
ABSTRACT Data Grid environment is a geographically distributed that deal with date-intensive applic...
Abstract — Managing large datasets has become one major application of grids. Life science applicati...
Data Grids deal with geographically-distributed large-scale data-intensive applications. Schemes sch...
One of the first motivations of using grids comes from applications managing large data sets in fiel...
(eng) One of the first motivations of using grids comes from applications managing large data sets l...
One of the first motivations of using grids comes from applications managing large data sets like fo...
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...
Grid computing is emerging as a new paradigm for solving large-scale problems and is becoming an est...
In data-intensive applications data transfer is a primary cause of job execution delay. Data access ...
Many current international scientific projects are based on large scale applications that are both c...