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Task Scheduling and Resource Optimization in Cloud Computing Using Deadline-Aware Particle Swarm Technique

Shruti 1 , Meenakshi Sharma2

  1. GRIMT, Kurukshetra University, Haryana, India.
  2. GRIMT, Kurukshetra University, Haryana, India.

Correspondence should be addressed to: shrutigoel63@gmail.com.

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-6 , Page no. 227-231, Jun-2017

Online published on Jun 30, 2017

Copyright © Shruti, Meenakshi Sharma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Shruti, Meenakshi Sharma, “Task Scheduling and Resource Optimization in Cloud Computing Using Deadline-Aware Particle Swarm Technique,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.227-231, 2017.

MLA Style Citation: Shruti, Meenakshi Sharma "Task Scheduling and Resource Optimization in Cloud Computing Using Deadline-Aware Particle Swarm Technique." International Journal of Computer Sciences and Engineering 5.6 (2017): 227-231.

APA Style Citation: Shruti, Meenakshi Sharma, (2017). Task Scheduling and Resource Optimization in Cloud Computing Using Deadline-Aware Particle Swarm Technique. International Journal of Computer Sciences and Engineering, 5(6), 227-231.

BibTex Style Citation:
@article{Sharma_2017,
author = {Shruti, Meenakshi Sharma},
title = {Task Scheduling and Resource Optimization in Cloud Computing Using Deadline-Aware Particle Swarm Technique},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2017},
volume = {5},
Issue = {6},
month = {6},
year = {2017},
issn = {2347-2693},
pages = {227-231},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1331},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1331
TI - Task Scheduling and Resource Optimization in Cloud Computing Using Deadline-Aware Particle Swarm Technique
T2 - International Journal of Computer Sciences and Engineering
AU - Shruti, Meenakshi Sharma
PY - 2017
DA - 2017/06/30
PB - IJCSE, Indore, INDIA
SP - 227-231
IS - 6
VL - 5
SN - 2347-2693
ER -

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Abstract

Cloud computing is defined as that type of computing which shows the development of potential, grid and parallel computing. It is the fastest new paradigm for delivery of services via internet. In this, the client can access software resources and valuable information over a network. It is the internet based computing in which resources are accessed via internet. In practice, the cloud computing faces the number of challenges like reliability, portability and shared access etc. Moreover, cloud computing faces the large quantity of cloud users, their tasks and data. Hence, to schedule the tasks efficiently, scheduling is done. In this paper, a Deadline Aware Particle Swarm Optimization (DAPSO) Algorithm is used which provides efficient and better results. Due to its fast convergence property, it is much better than Particle Swarm Optimization (PSO) algorithm. It is used to optimize the task scheduling algorithm which results in better performance and profit.

Key-Words / Index Term

Cloud computing, scheduling, Task Scheduling Algorithms, Particle Swarm Optimization (PSO), Task scheduling, Scheduling Types, Deadline Aware Particle Swarm Optimization (DAPSO).

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