
Genetic-Based Algorithms Applied to a Workflow Scheduling Algorithm with Security and Deadline Constraints in Clouds
Abstract
The literature described a number of metaheuristic cloud scheduling techniques as well as their applications. Genetic-based algorithms applied to a workflow scheduling algorithm with security and deadline constraints in clouds In a wide range of workflow scheduling algorithms for cloud environments, the efficiency of metaheuristic techniques has been established. However, it is still unknown whether the metaheuristic chosen is suitable for solving the optimization problem.
This Genetic-based algorithms applied to a workflow scheduling algorithm with security and deadline constraints in clouds paper examines the effect on attempts to optimize workflow scheduling of both Particle Swarm Optimization (PSO) and Genetic-based Algorithms (GA). The findings indicate that GA-based algorithms significantly outperformed PSO both in terms of cost-effectiveness and response time.
System Configuration
H/W System Configuration
Speed : 1.1 GHz
RAM : 256 MB(min)
Hard Disk : 20 GB
Floppy Drive : 1.44 MB
Key Board : Standard Windows Keyboard
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S/W System Configuration
Platform : cloud computing
Operating system : Windows Xp,7,
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Working on : Browser Like Firefox, IE







