Impact of Parallel Download on Job Scheduling in Data Grid Environment

2008 ◽  
Author(s):  
Junwei Zhang ◽  
Bu-Sung Lee ◽  
Xueyan Tang ◽  
Chai-Kiat Yeo
Keyword(s):  
Job Scheduling ◽  
Data Grid ◽  
Grid Environment

Improving job scheduling performance with parallel access to replicas in Data Grid environment

2009 ◽  
Vol 56 (3) ◽  
pp. 245-269 ◽  
Author(s):  
Junwei Zhang ◽  
Bu-Sung Lee ◽  
Xueyan Tang ◽  
Chai-Kiat Yeo
Keyword(s):  
Job Scheduling ◽  
Data Grid ◽  
Grid Environment ◽  
Parallel Access

scholarly journals Cooling-Efficient Job Scheduling in a Heterogeneous Grid Environment

2015 ◽  
Vol 69 ◽  
pp. 104-115
Author(s):  
Ahmad Abba Haruna ◽  
Low T. Jung ◽  
Nordin Zakaria ◽  
Jun Okitsu
Keyword(s):  
Job Scheduling ◽  
Grid Environment

Balanced Job Scheduling Based on Ant Algorithm for Grid Network

2010 ◽  
Vol 2 (1) ◽  
pp. 34-50 ◽  
Author(s):  
Nikolaos Preve
Keyword(s):  
Grid Computing ◽  
Ant Colony Optimization ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Experimental Results ◽  
Ant Algorithm ◽  
Entire System ◽  
Grid Environment ◽  
Grid Network

Job scheduling in grid computing is a very important problem. To utilize grids efficiently, we need a good job scheduling algorithm to assign jobs to resources in grids. The main scope of this article is to propose a new Ant Colony Optimization (ACO) algorithm for balanced job scheduling in the Grid environment. To achieve the above goal, we will indicate a way to balance the entire system load while minimizing the makespan of a given set of jobs. Based on the experimental results, the proposed algorithm confidently demonstrates its practicability and competitiveness compared with other job scheduling algorithms.

Using Grid Technology for Maximizing Collaborative Emergency Response Decision Making

2009 ◽  
pp. 256-275 ◽  
Author(s):  
Eleana Asimakopoulou ◽  
Chimay J. Anumba ◽  
Bouchlaghem ◽  
Bouchlaghem
Keyword(s):  
Decision Making ◽  
Emergency Response ◽  
Data Grid ◽  
Informed Decision ◽  
Data Sources ◽  
Grid Technology ◽  
Distributed Data ◽  
Grid Environment ◽  
Design And Implementation ◽  
Response Decision

Much work is under way within the Grid technology community on issues associated with the development of services to foster collaboration via the integration and exploitation of multiple autonomous, distributed data sources through a seamless and flexible virtualized interface. However, several obstacles arise in the design and implementation of such services. A notable obstacle, namely how clients within a data Grid environment can be kept automatically informed of the latest and relevant changes about data entered/committed in single or multiple autonomous distributed datasets is identified. The view is that keeping interested users informed of relevant changes occurring across their domain of interest will enlarge their decision-making space which in turn will increase the opportunities for a more informed decision to be encountered. With this in mind, the chapter goes on to describe in detail the model architecture and its implementation to keep interested users informed automatically about relevant up-to-date data.

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