An Adaptive Scheduling Algorithm for Scheduling Tasks in Computational Grid

2008 ◽  
Author(s):  
Kun-Ming Yu ◽  
Cheng-Kwan Chen
Keyword(s):  
Scheduling Algorithm ◽  
Computational Grid ◽  
Adaptive Scheduling

A Security Prioritized Computational Grid Scheduling Model

2011 ◽  
pp. 90-100
Author(s):  
Rekha Kashyap ◽  
Deo P. Vidyarthi
Keyword(s):  
Scheduling Algorithm ◽  
Computational Grid ◽  
Security Requirement ◽  
Computational Power ◽  
Grid Scheduling ◽  
System Utilization ◽  
Scheduling Model ◽  
Grid Resources

Grid supports heterogeneities of resources in terms of security and computational power. Applications with stringent security requirement introduce challenging concerns when executed on the grid resources. Though grid scheduler considers the computational heterogeneity while making scheduling decisions, little is done to address their security heterogeneity. This work proposes a security aware computational grid scheduling model, which schedules the tasks taking into account both kinds of heterogeneities. The approach is known as Security Prioritized MinMin (SPMinMin). Comparing it with one of the widely used grid scheduling algorithm MinMin (secured) shows that SPMinMin performs better and sometimes behaves similar to MinMin under all possible situations in terms of makespan and system utilization.

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.

An Adaptive Scheduling System for Computational Grid using Autonomic Computing

2012 ◽  
Vol 47 (13) ◽  
pp. 12-19
Author(s):  
Ebrahim Aghaei ◽  
Mohammad Saniee Abadeh ◽  
Mohammad Hossein Yektaie
Keyword(s):  
Autonomic Computing ◽  
Computational Grid ◽  
Adaptive Scheduling ◽  
Scheduling System
Sign in / Sign up

Export Citation Format

Share Document