A Survey on Various Task Scheduling Algorithms Toward Load Balancing in Public Cloud

Pradeep Naik; Surbhi Agrawal; Srikanta Murthy

doi:doi:10.11648/j.ajam.s.2015030102.13

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A Survey on Various Task Scheduling Algorithms Toward Load Balancing in Public Cloud

Pradeep Naik, Surbhi Agrawal, Srikanta Murthy

Published in American Journal of Applied Mathematics (Volume 3, Issue 1-2)

Received: 14 November 2014 Accepted: 9 December 2014 Published: 30 December 2014

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Abstract

Cloud computing is one of the real innovation in giving a shared pool of resources globally. In cloud computing there exist diverse sorts of architectures in particular private, public, hybrid and so on. The cloud computing is also meant for providing service via platform (PaaS), Infrastructure (IaaS), Software (SaaS). The term capacity planning is used to dynamically upscale or downscale the computing resources accordingly. There will be many job requests which require to get executed among the available resources in a particular cloud in order to achieve the maximum throughput, minimum waiting time and best overall performance. In this paper a systematic review is made on various job scheduling algorithms along with their working procedure and a comparison among these algorithms is presented. The paper concludes with a proposed system with improvised QoS parameters to provide a load balanced task scheduling algorithm for public clouds.

Published in	American Journal of Applied Mathematics (Volume 3, Issue 1-2) This article belongs to the Special Issue Frontiers in Mathematics and Computing
DOI	10.11648/j.ajam.s.2015030102.13
Page(s)	14-17
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2014. Published by Science Publishing Group

Keywords

Cloud Computing, Bipartite Graph, Augmenting Path, Job Scheduling, Scheduling, Load Balancing

References

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[3]	Ghanbari, Shamsollah, and Mohamed Othman. "A Priority based Job Scheduling Algorithm in Cloud Computing." Procedia Engineering 50 (2012): 778-785.
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[5]	UpendraBhoi, “Enhanced Max-Min Task scheduling algorithm in cloud computing”. International journal of application or innovation in engineering and Management.
[6]	Poonam Devi, “Implementation of cloud computing by using short job scheduling”, International journal of advanced research in computer science and software engineering, july-2013, ISSN :2277-128X
[7]	Jing Liu, Xing-GuoLuo, Xing-Ming Zhang and Bai-Nan Li, “Job Scheduling model for cloud computing based on multi-objective Genetic Algorithm”, IJCSI International journal of computer science issues, January 2013, ISSN (Print): 1694-0784 \| ISSN(online)1694-0814.
[8]	AshishPatro, MinJae Hwang, Thanumalayan S., ThawanKooburat, “Garuda a cloud-based job scheduler”.
[9]	P. Patel, A. Ranabahu and A. Sheth, “Service level agreement incloudcomputing”,://knoesis.wright.edu/library/download/OOPSLA_cloudwsla_v3.pdf, (2009).
[10]	R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg and I. Brandic, "Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility", Future Generation Computer Systems, vol. 25, issue 6, (2009), pp. 599-616.
[11]	W. Sun, Y. Zhang and Y. Inoguchi, "Dynamic task flow scheduling for heterogeneous distributed computing: algorithm and strategy", IEICE Trans. on Inf. & Sys., vol. E90-D, no. 4, (2007), pp. 736-744.
[12]	Yun Chi, Hyun Jin Moon, HakanHakigumus, Junichi Tatemura, “SLA-Tree: A framework for efficiently supporting SLA-based Decisions in cloud computing”, EDBT/ICDT’2011 Proceedings of the 14th international conference on existing database technology, ACM 978-1-4503-0528-0/11/0003
[13]	http://www.openstack.org/software/

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APA Style

Pradeep Naik, Surbhi Agrawal, Srikanta Murthy. (2014). A Survey on Various Task Scheduling Algorithms Toward Load Balancing in Public Cloud. American Journal of Applied Mathematics, 3(1-2), 14-17. https://doi.org/10.11648/j.ajam.s.2015030102.13

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ACS Style

Pradeep Naik; Surbhi Agrawal; Srikanta Murthy. A Survey on Various Task Scheduling Algorithms Toward Load Balancing in Public Cloud. Am. J. Appl. Math. 2014, 3(1-2), 14-17. doi: 10.11648/j.ajam.s.2015030102.13

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AMA Style

Pradeep Naik, Surbhi Agrawal, Srikanta Murthy. A Survey on Various Task Scheduling Algorithms Toward Load Balancing in Public Cloud. Am J Appl Math. 2014;3(1-2):14-17. doi: 10.11648/j.ajam.s.2015030102.13

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@article{10.11648/j.ajam.s.2015030102.13,
  author = {Pradeep Naik and Surbhi Agrawal and Srikanta Murthy},
  title = {A Survey on Various Task Scheduling Algorithms Toward Load Balancing in Public Cloud},
  journal = {American Journal of Applied Mathematics},
  volume = {3},
  number = {1-2},
  pages = {14-17},
  doi = {10.11648/j.ajam.s.2015030102.13},
  url = {https://doi.org/10.11648/j.ajam.s.2015030102.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajam.s.2015030102.13},
  abstract = {Cloud computing is one of the real innovation in giving a shared pool of resources globally. In cloud computing there exist diverse sorts of architectures in particular private, public, hybrid and so on. The cloud computing is also meant for providing service via platform (PaaS), Infrastructure (IaaS), Software (SaaS). The term capacity planning is used to dynamically upscale or downscale the computing resources accordingly. There will be many job requests which require to get executed among the available resources in a particular cloud in order to achieve the maximum throughput, minimum waiting time and best overall performance. In this paper a systematic review is made on various job scheduling algorithms along with their working procedure and a comparison among these algorithms is presented. The paper concludes with a proposed system with improvised QoS parameters to provide a load balanced task scheduling algorithm for public clouds.},
 year = {2014}
}

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TY  - JOUR
T1  - A Survey on Various Task Scheduling Algorithms Toward Load Balancing in Public Cloud
AU  - Pradeep Naik
AU  - Surbhi Agrawal
AU  - Srikanta Murthy
Y1  - 2014/12/30
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DO  - 10.11648/j.ajam.s.2015030102.13
T2  - American Journal of Applied Mathematics
JF  - American Journal of Applied Mathematics
JO  - American Journal of Applied Mathematics
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EP  - 17
PB  - Science Publishing Group
SN  - 2330-006X
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AB  - Cloud computing is one of the real innovation in giving a shared pool of resources globally. In cloud computing there exist diverse sorts of architectures in particular private, public, hybrid and so on. The cloud computing is also meant for providing service via platform (PaaS), Infrastructure (IaaS), Software (SaaS). The term capacity planning is used to dynamically upscale or downscale the computing resources accordingly. There will be many job requests which require to get executed among the available resources in a particular cloud in order to achieve the maximum throughput, minimum waiting time and best overall performance. In this paper a systematic review is made on various job scheduling algorithms along with their working procedure and a comparison among these algorithms is presented. The paper concludes with a proposed system with improvised QoS parameters to provide a load balanced task scheduling algorithm for public clouds.
VL  - 3
IS  - 1-2
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Author Information

Pradeep Naik

CSE Department, PESIT-BSC, Bangalore, India
Surbhi Agrawal

CSE Department, PESIT-BSC, Bangalore, India
Srikanta Murthy

CSE Department, PESIT-BSC, Bangalore, India

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APA Style

Pradeep Naik, Surbhi Agrawal, Srikanta Murthy. (2014). A Survey on Various Task Scheduling Algorithms Toward Load Balancing in Public Cloud. American Journal of Applied Mathematics, 3(1-2), 14-17. https://doi.org/10.11648/j.ajam.s.2015030102.13

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ACS Style

Pradeep Naik; Surbhi Agrawal; Srikanta Murthy. A Survey on Various Task Scheduling Algorithms Toward Load Balancing in Public Cloud. Am. J. Appl. Math. 2014, 3(1-2), 14-17. doi: 10.11648/j.ajam.s.2015030102.13

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AMA Style

Pradeep Naik, Surbhi Agrawal, Srikanta Murthy. A Survey on Various Task Scheduling Algorithms Toward Load Balancing in Public Cloud. Am J Appl Math. 2014;3(1-2):14-17. doi: 10.11648/j.ajam.s.2015030102.13

Copy | Download

@article{10.11648/j.ajam.s.2015030102.13,
  author = {Pradeep Naik and Surbhi Agrawal and Srikanta Murthy},
  title = {A Survey on Various Task Scheduling Algorithms Toward Load Balancing in Public Cloud},
  journal = {American Journal of Applied Mathematics},
  volume = {3},
  number = {1-2},
  pages = {14-17},
  doi = {10.11648/j.ajam.s.2015030102.13},
  url = {https://doi.org/10.11648/j.ajam.s.2015030102.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajam.s.2015030102.13},
  abstract = {Cloud computing is one of the real innovation in giving a shared pool of resources globally. In cloud computing there exist diverse sorts of architectures in particular private, public, hybrid and so on. The cloud computing is also meant for providing service via platform (PaaS), Infrastructure (IaaS), Software (SaaS). The term capacity planning is used to dynamically upscale or downscale the computing resources accordingly. There will be many job requests which require to get executed among the available resources in a particular cloud in order to achieve the maximum throughput, minimum waiting time and best overall performance. In this paper a systematic review is made on various job scheduling algorithms along with their working procedure and a comparison among these algorithms is presented. The paper concludes with a proposed system with improvised QoS parameters to provide a load balanced task scheduling algorithm for public clouds.},
 year = {2014}
}

Copy | Download

TY  - JOUR
T1  - A Survey on Various Task Scheduling Algorithms Toward Load Balancing in Public Cloud
AU  - Pradeep Naik
AU  - Surbhi Agrawal
AU  - Srikanta Murthy
Y1  - 2014/12/30
PY  - 2014
N1  - https://doi.org/10.11648/j.ajam.s.2015030102.13
DO  - 10.11648/j.ajam.s.2015030102.13
T2  - American Journal of Applied Mathematics
JF  - American Journal of Applied Mathematics
JO  - American Journal of Applied Mathematics
SP  - 14
EP  - 17
PB  - Science Publishing Group
SN  - 2330-006X
UR  - https://doi.org/10.11648/j.ajam.s.2015030102.13
AB  - Cloud computing is one of the real innovation in giving a shared pool of resources globally. In cloud computing there exist diverse sorts of architectures in particular private, public, hybrid and so on. The cloud computing is also meant for providing service via platform (PaaS), Infrastructure (IaaS), Software (SaaS). The term capacity planning is used to dynamically upscale or downscale the computing resources accordingly. There will be many job requests which require to get executed among the available resources in a particular cloud in order to achieve the maximum throughput, minimum waiting time and best overall performance. In this paper a systematic review is made on various job scheduling algorithms along with their working procedure and a comparison among these algorithms is presented. The paper concludes with a proposed system with improvised QoS parameters to provide a load balanced task scheduling algorithm for public clouds.
VL  - 3
IS  - 1-2
ER  -

Copy | Download