GA-Based Job Scheduling Strategies for Fault Tolerant Grid Systems

2008 ◽  
Author(s):  
Chao-Chin Wu ◽  
Kuan-Chou Lai ◽  
Ren-Yi Sun
Keyword(s):  
Job Scheduling ◽  
Fault Tolerant ◽  
Grid Systems ◽  
Scheduling Strategies

Efficient Job Scheduling in Computational Grid Systems Using Wind Driven Optimization Technique

2018 ◽  
Vol 9 (1) ◽  
pp. 49-59
Author(s):  
Tarun Kumar Ghosh ◽  
Sanjoy Das
Keyword(s):  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Optimization Technique ◽  
Computational Grid ◽  
Grid System ◽  
Swarm Optimization ◽  
Grid Systems ◽  
Geographically Distributed ◽  
Job Scheduler ◽  
Computational Resources

Computational Grid has been employed for solving complex and large computation-intensive problems with the help of geographically distributed, heterogeneous and dynamic resources. Job scheduling is a vital and challenging function of a computational Grid system. Job scheduler has to deal with many heterogeneous computational resources and to take decisions concerning the dynamic, efficient and effective execution of jobs. Optimization of the Grid performance is directly related with the efficiency of scheduling algorithm. To evaluate the efficiency of a scheduling algorithm, different parameters can be used, the most important of which are makespan and flowtime. In this paper, a very recent evolutionary heuristic algorithm known as Wind Driven Optimization (WDO) is used for efficiently allocating jobs to resources in a computational Grid system so that makespan and flowtime are minimized. In order to measure the efficacy of WDO, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are considered for comparison. This study proves that WDO produces best results.

scholarly journals Two Level Job-Scheduling Strategies for a Computational Grid

2006 ◽  
pp. 774-781 ◽  
Author(s):  
Andrei Tchernykh ◽  
Juan Manuel Ramírez ◽  
Arutyun Avetisyan ◽  
Nikolai Kuzjurin ◽  
Dmitri Grushin ◽  
...  
Keyword(s):  
Job Scheduling ◽  
Computational Grid ◽  
Scheduling Strategies
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