This paper is published in Volume-7, Issue-3, 2021
Area
Information Technology
Author
Parminder Kaur, Sarabjeet Kaur
Org/Univ
Adesh Institute of Engineering and Technology, Faridkot, Punjab, India
Pub. Date
07 May, 2021
Paper ID
V7I3-1208
Publisher
Keywords
Cloud Computing, Chaotic Map, Cuckoo Search Algorithm, Task Scheduling

Citationsacebook

IEEE
Parminder Kaur, Sarabjeet Kaur. Task scheduling in the cloud computing using an improved cuckoo search algorithm, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Parminder Kaur, Sarabjeet Kaur (2021). Task scheduling in the cloud computing using an improved cuckoo search algorithm. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.

MLA
Parminder Kaur, Sarabjeet Kaur. "Task scheduling in the cloud computing using an improved cuckoo search algorithm." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.

Abstract

Cloud computing is an advanced internet resources network that is used by many users remotely. The resources include software, hardware, and various applications. The main challenge in cloud computing is task scheduling due to numerous requests are generated simultaneously from remote locations. To overcome this challenge, task scheduling algorithms are designed that appropriately arrange the tasks. In the literature, metaheuristic algorithms have been deployed for optimal task scheduling. The most popular algorithms are genetic algorithm, particle swarm, and cuckoo search algorithm. However, if the initial population of these algorithms is properly not defined then it is easily trapped into the local optimal solution and causes low precision. In this paper, we have overcome this issue and designed an improved cuckoo search algorithm. In the proposed method, the initial population is defined using the chaotic map algorithm and after cuckoo search algorithm is applied to determine optimal task scheduling. The experimental results show that the proposed method is superior in terms of convergence rate, makespan, average waiting time, and average turnaround time as compared to the existing algorithm.
Paper PDF