Notification: Our email services are now fully restored after a brief, temporary outage caused by a denial-of-service (DoS) attack. If you sent an email on Dec 6 and haven't received a response, please resend your email.
CFP last date
20 December 2024
Reseach Article

Improving Task Scheduling in Large Scale Cloud Computing Environment using Artificial Bee Colony Algorithm

by R.sathish Kumar, S.gunasekaran
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 5
Year of Publication: 2014
Authors: R.sathish Kumar, S.gunasekaran
10.5120/18072-9017

R.sathish Kumar, S.gunasekaran . Improving Task Scheduling in Large Scale Cloud Computing Environment using Artificial Bee Colony Algorithm. International Journal of Computer Applications. 103, 5 ( October 2014), 29-32. DOI=10.5120/18072-9017

@article{ 10.5120/18072-9017,
author = { R.sathish Kumar, S.gunasekaran },
title = { Improving Task Scheduling in Large Scale Cloud Computing Environment using Artificial Bee Colony Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 5 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 29-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number5/18072-9017/ },
doi = { 10.5120/18072-9017 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:33:45.678263+05:30
%A R.sathish Kumar
%A S.gunasekaran
%T Improving Task Scheduling in Large Scale Cloud Computing Environment using Artificial Bee Colony Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 5
%P 29-32
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the face of Scheduling, the tasks are scheduled by using Different scheduling Algorithms. Each Scheduling Algorithm has own particularity and complexity during Scheduling. In order to get the minimum time for the execution of the task the Scheduling algorithm must be good, once the performance of the scheduling algorithm is good then automatically the result obtained by that particular algorithm will be considered , there are huge number of task that are scheduled under cloud computing in order to get the minimum time and the maximum through put the Scheduling algorithm plays an important factor Here the algorithm which used for Scheduling the task is artificial bee colony algorithm this scheduling process is done under the cloud computing environment. In this Paper we are considering the time as the main QoS factor, minimum total task finishing time, mean task finishing time and load balancing time is obtained by using this Cloud simulation environment

References
  1. AChin Soon Chong. S (2009) "A Bee Colony Optimization Algorithm to JobShop Scheduling", Proceedings of the 2006 Winter Simulation Conference.
  2. AHorst. Wedde, Muddassar Farooq, and Yue Zhang (2009)"Beehive: An Efficient Fault- Tolerant Routing Algorithm Inspired by Honey Bee Behavior", ANTS 2004, LNCS 3172, pp. 83–94, 2004. cSpringer-Verlag Berlin Heidelberg 2004
  3. Bitam Salim . G (2010) "Bees Life Algorithm for Job Scheduling in CloudComputing", BEES 2010, LNCS 5612, pp. 22–54, 212. ICCIT – 2012
  4. Jingpeng Li A Bayesian (2003) "Optimization Algorithm for the Nurse Scheduling Problem" Proceedings of 2003 Congress on Evolutionary Computation (CEC2003), pp. 2149-2156, IEEE Press, Canberra, Australia, 2003.
  5. Nadezda Stanarevic Milan Tuba, and Nebojsa Bacanin (2011) "Modified Artificial bee colony algorithm for constrained problems optimization"International Journal of Mathematical Models and Methods in Applied Sciences
  6. Nidhal Kamel Taha El-Omari (2010) "Developing Optimization Algorithm Using Artificial Bee Colony System" Ubiquitous Computing and Communication Journal.
  7. Pan. Q, Li. H, Xie. S, Wang. S (2010) "A Hybrid Artificial Bee Colony Algorithm for FlexibleJobShop Scheduling Problems", Int. J. of Computers, Communications & Control, ISSN 1841-9836, E-ISSN 1841-9844 Vol. VI(2011), No. 2 (June), pp. 286-296
  8. Qi Cao, Zhi-Bo Wei and Wen-Mao Gong (2009)"An Optimized Algorithm For Task Scheduling Based On Activity Based CostinginCloud Computing", 3rd International Conference on Bioinformatics and Biomedical Engineering, (ICBBE)
  9. Rodrigo. W Calheiros et. al (2010) Cloudsim: "A Novel Framework Modeling and Simulation of Cloud Computing Infrastructures and Services" 5th International Conference on Simulation and networking 2010.
  10. Wuqi Gao and Fengju Kang (2012) "Cloud Simulation Resource Scheduling Algorithm Based Multi-dimension Quality of Service Information Technology Journal Year 2012 Volume: 11.
Index Terms

Computer Science
Information Sciences

Keywords

Scheduling Complexity Performance Cloud Computing Total task finishing time Mean task finishing time Load balancing time Quality of Services