Enhanced Genetic Algorithm based Task Scheduling in Cloud Computing

Abstract

Cloud computing is basically internet based computing while software, information and shared resources are provided to devices and computers on demand, like electricity grid. With the fusion of network technology and traditional computing technology such as distributed computing parallel computing, grid computing a cloud computing product is formed. Task scheduling is the major concern in the field of cloud computing. As the use of cloud computing increases, the burden on the cloud network also increases. So, it's the duty of the scheduler to make cloud efficient to solve client's tasks. This work focuses on the same to achieve the objective of optimized task scheduling where improved genetic algorithm is proposed. Genetic algorithm is artificial intelligent based soft computing technique to optimize the process. Here in this work, genetic algorithm is enhanced using new fitness function based on mean and grand mean values. This optimization can be implemented on both ends, for job scheduling and resource scheduling. This will schedule the whole process and optimize as much as possible. The results analysis also proves the cloud system's increased efficiency for task scheduling.

Modified Genetic Algorithm Based Solution for Task Scheduling in Cloud Computing Environment

“…Kousik Dasgupta et al (2013) [2] have presented an approach that handles the load on processors as well as reduces the makespan, but takes equal priority tasks. In 2014, Rajveer Kaur et al [11] have developed a scheduling algorithm that assigns a priority to the tasks according to Role Based Access Control method. Roles are defined according to Job competency, Authorization, and Responsibility.…”

Genetic-Based Task Scheduling Algorithm in Cloud Computing Environment

“…Therefore, the Cloud provider needs a good algorithm to schedule the users' tasks on the Cloud to satisfy QoS, minimize makespan, and guarantee good utilization of the Cloud resources [5]. Therefore, task scheduling is classified as an optimization problem.…”

“…Kaur and S. Kinger [5] have proposed task scheduling algorithm-based enhancement GA. They use a new fitness function based on mean and grand mean values.…”

“…As the allocation of Cloud resource is based on SLA, the task execution cost is considered one of the main performance parameters of the task scheduling algorithm [5]. On the other hand, the task scheduling algorithm is considered a complex process because it must schedule a large number of tasks into the available resources.…”

A New Technique to Manage Big Bioinformatics Data Using Genetic Algorithms

“…Fig. 3 presents the simple Genetic Algorithm flowchart which it briefly describes the four basic operators to resolve a problem as follows: fitness function, selection operator, crossover operator, and mutation operator [9,10,11,12,13,14].…”