Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing

Abdulrahman Abdulkarim; Ishaq Muhammed; Lele Mohammed; Abbas Babayaro

doi:doi:10.11648/j.ajnc.20190802.11

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Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing

Abdulrahman Abdulkarim, Ishaq Muhammed, Lele Mohammed, Abbas Babayaro

Received: 20 May 2019 Accepted: 31 July 2019 Published: 16 August 2019

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Abstract

Cloud computing consists of a cluster of computing resources that are delivered over a network, which is accomplished by utilizing virtualization technologies to consolidate and allocate resources suitable for various different software applications. Therefore, an efficient task scheduling in the cloud would be required to improve the performance of the cloud. In this paper, implementation of a model that seeks to improve load balancing algorithm for virtual machine load balancing was performed using simulations. A method by which average burst time was used as the time quantum for the round robin load balancing algorithm to achieve more effective time sharing. Results obtained from the simulations along with performance evaluation carried out shows response time and data center processing time achieved using the improved model is slightly minimal compared to the other algorithms. This shows more effective load balancing by achieving a better overall throughput.

DOI	10.11648/j.ajnc.20190802.11
Published in	American Journal of Networks and Communications (Volume 8, Issue 2, December 2019)
Page(s)	47-58
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), 2024. Published by Science Publishing Group

Keywords

Cloud Computing, Round Robin, Virtual Machine (VM), Load Balancing, Burst Time, Time Quantum, Response Time

References

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[2]	Aggarwal, R., & Gupta, L. (2017). Load Balancing in Cloud Computing. International Journal of Computer Science and Mobile Computing, Volume 6, Issue 6, 180-186.
[3]	Bey, K. B., Benhammadi, F., & Benaissa, R. (2015). Balancing Heuristic for Independent Task Scheduling in Cloud Computing. 12th International Symposium on Programming and Systems, 7-12.
[4]	Ettikyala, K., & Latha, Y. N. (2016). Rank Based Efficient Task Scheduling for Cloud Computing. IEEE International Conference on Data Mining and Advanced Computing, 343-346.
[5]	Krishna, P. V. (2013). Honey Bee Behavior Inspired Load Balancing of Task in Cloud Computing Environments. Applied Software Computing, 2292-2303.
[6]	Mathew, T., Sekaran, K. C., & Jose, J. (2014). Study and Analysis of Various Task Scheduling Algorithm in Cloud Computing Environment. International Conference on Advances in Computing, 658-664.
[7]	Nusrat, P., Amit, A., & Ravi, R. (2014). Round Robin Approach for VM Load Balancing Algorithm in Cloud Computing Environment. Internation Journal of Advanced Research in Computer Science and Software Engineering, 34-39.
[8]	Phi, N. X., & Hung, T. C. (2017). Load Balancing Algorithm to Improve Response Time on Cloud Environment. International Journal on Cloud Computing: Services and Architecture, Volume 7, No. 6, 1-12.
[9]	Sachdeva, R., & Kakkar, S. (2017). A Novel Approach in Cloud Computing for Load Balancing Using Composite Algorithms. International Journal of Advanced Research in Computer Science and Software Engineering, Volume 7, Issue 2, 51-56.
[10]	Selvarani, S., & Sadhasivam, G. S. (2010). Improved cost-based algorithm for task scheduling in cloud computing. Computational Intelligence and computing research, 1-5.
[11]	Zannon, N., & Rawshdeh, D. (2015). STASR: A New Task Scheduling Algorithm for Cloud Environment. Network Protocols and Algorithms (pp. 81-95). Macrothink Institude.
[12]	Rani, P., & Nagpal, P. (2017). Optimized Task Scheduling Algorithm for Cloud Computing Environment. International Journal of Emerging Trends & Technology in Computer Science, Volume 6, Issue 5, 39-47.
[13]	George, M. S., Das, K. C. N., & Pushpa, B. R. (2017). Enhanced honeybee inspired load balancing algorithm for cloud environment. 2017 International Conference on Communication and Signal Processing (ICCSP). doi: 10.1109/iccsp.2017.8286670.
[14]	Kumar, A. S.; Venkatesan, M. Task scheduling in a cloud computing environment using HGPSO algorithm. Cluster Comput. 2018, 1–7.
[15]	Wang, S.; Qian, Z.; Yuan, J.; You, I. A DVFS based energy-e_cient tasks scheduling in a data center. IEEE Access 2017, 5, 13090–13102.

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APA Style

Abdulrahman Abdulkarim, Ishaq Muhammed, Lele Mohammed, Abbas Babayaro. (2019). Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing. American Journal of Networks and Communications, 8(2), 47-58. https://doi.org/10.11648/j.ajnc.20190802.11

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ACS Style

Abdulrahman Abdulkarim; Ishaq Muhammed; Lele Mohammed; Abbas Babayaro. Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing. Am. J. Netw. Commun. 2019, 8(2), 47-58. doi: 10.11648/j.ajnc.20190802.11

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AMA Style

Abdulrahman Abdulkarim, Ishaq Muhammed, Lele Mohammed, Abbas Babayaro. Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing. Am J Netw Commun. 2019;8(2):47-58. doi: 10.11648/j.ajnc.20190802.11

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@article{10.11648/j.ajnc.20190802.11,
  author = {Abdulrahman Abdulkarim and Ishaq Muhammed and Lele Mohammed and Abbas Babayaro},
  title = {Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing},
  journal = {American Journal of Networks and Communications},
  volume = {8},
  number = {2},
  pages = {47-58},
  doi = {10.11648/j.ajnc.20190802.11},
  url = {https://doi.org/10.11648/j.ajnc.20190802.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnc.20190802.11},
  abstract = {Cloud computing consists of a cluster of computing resources that are delivered over a network, which is accomplished by utilizing virtualization technologies to consolidate and allocate resources suitable for various different software applications. Therefore, an efficient task scheduling in the cloud would be required to improve the performance of the cloud. In this paper, implementation of a model that seeks to improve load balancing algorithm for virtual machine load balancing was performed using simulations. A method by which average burst time was used as the time quantum for the round robin load balancing algorithm to achieve more effective time sharing. Results obtained from the simulations along with performance evaluation carried out shows response time and data center processing time achieved using the improved model is slightly minimal compared to the other algorithms. This shows more effective load balancing by achieving a better overall throughput.},
 year = {2019}
}

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TY  - JOUR
T1  - Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing
AU  - Abdulrahman Abdulkarim
AU  - Ishaq Muhammed
AU  - Lele Mohammed
AU  - Abbas Babayaro
Y1  - 2019/08/16
PY  - 2019
N1  - https://doi.org/10.11648/j.ajnc.20190802.11
DO  - 10.11648/j.ajnc.20190802.11
T2  - American Journal of Networks and Communications
JF  - American Journal of Networks and Communications
JO  - American Journal of Networks and Communications
SP  - 47
EP  - 58
PB  - Science Publishing Group
SN  - 2326-8964
UR  - https://doi.org/10.11648/j.ajnc.20190802.11
AB  - Cloud computing consists of a cluster of computing resources that are delivered over a network, which is accomplished by utilizing virtualization technologies to consolidate and allocate resources suitable for various different software applications. Therefore, an efficient task scheduling in the cloud would be required to improve the performance of the cloud. In this paper, implementation of a model that seeks to improve load balancing algorithm for virtual machine load balancing was performed using simulations. A method by which average burst time was used as the time quantum for the round robin load balancing algorithm to achieve more effective time sharing. Results obtained from the simulations along with performance evaluation carried out shows response time and data center processing time achieved using the improved model is slightly minimal compared to the other algorithms. This shows more effective load balancing by achieving a better overall throughput.
VL  - 8
IS  - 2
ER  -

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Author Information

Abdulrahman Abdulkarim

Department of Computer Science, Faculty of Science, Federal Polytechnic, Bauchi, Nigeria
Ishaq Muhammed

Department of Computer Science, Faculty of Science, Federal Polytechnic, Bauchi, Nigeria
Lele Mohammed

Department of Computer Science, Faculty of Science, Federal Polytechnic, Bauchi, Nigeria
Abbas Babayaro

Department of Information and Communication Technology, Bauchi State University Gadau, Bauchi, Nigeria

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Plain Text BibTeX RIS

APA Style

Abdulrahman Abdulkarim, Ishaq Muhammed, Lele Mohammed, Abbas Babayaro. (2019). Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing. American Journal of Networks and Communications, 8(2), 47-58. https://doi.org/10.11648/j.ajnc.20190802.11

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ACS Style

Abdulrahman Abdulkarim; Ishaq Muhammed; Lele Mohammed; Abbas Babayaro. Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing. Am. J. Netw. Commun. 2019, 8(2), 47-58. doi: 10.11648/j.ajnc.20190802.11

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AMA Style

Abdulrahman Abdulkarim, Ishaq Muhammed, Lele Mohammed, Abbas Babayaro. Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing. Am J Netw Commun. 2019;8(2):47-58. doi: 10.11648/j.ajnc.20190802.11

Copy | Download

@article{10.11648/j.ajnc.20190802.11,
  author = {Abdulrahman Abdulkarim and Ishaq Muhammed and Lele Mohammed and Abbas Babayaro},
  title = {Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing},
  journal = {American Journal of Networks and Communications},
  volume = {8},
  number = {2},
  pages = {47-58},
  doi = {10.11648/j.ajnc.20190802.11},
  url = {https://doi.org/10.11648/j.ajnc.20190802.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnc.20190802.11},
  abstract = {Cloud computing consists of a cluster of computing resources that are delivered over a network, which is accomplished by utilizing virtualization technologies to consolidate and allocate resources suitable for various different software applications. Therefore, an efficient task scheduling in the cloud would be required to improve the performance of the cloud. In this paper, implementation of a model that seeks to improve load balancing algorithm for virtual machine load balancing was performed using simulations. A method by which average burst time was used as the time quantum for the round robin load balancing algorithm to achieve more effective time sharing. Results obtained from the simulations along with performance evaluation carried out shows response time and data center processing time achieved using the improved model is slightly minimal compared to the other algorithms. This shows more effective load balancing by achieving a better overall throughput.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing
AU  - Abdulrahman Abdulkarim
AU  - Ishaq Muhammed
AU  - Lele Mohammed
AU  - Abbas Babayaro
Y1  - 2019/08/16
PY  - 2019
N1  - https://doi.org/10.11648/j.ajnc.20190802.11
DO  - 10.11648/j.ajnc.20190802.11
T2  - American Journal of Networks and Communications
JF  - American Journal of Networks and Communications
JO  - American Journal of Networks and Communications
SP  - 47
EP  - 58
PB  - Science Publishing Group
SN  - 2326-8964
UR  - https://doi.org/10.11648/j.ajnc.20190802.11
AB  - Cloud computing consists of a cluster of computing resources that are delivered over a network, which is accomplished by utilizing virtualization technologies to consolidate and allocate resources suitable for various different software applications. Therefore, an efficient task scheduling in the cloud would be required to improve the performance of the cloud. In this paper, implementation of a model that seeks to improve load balancing algorithm for virtual machine load balancing was performed using simulations. A method by which average burst time was used as the time quantum for the round robin load balancing algorithm to achieve more effective time sharing. Results obtained from the simulations along with performance evaluation carried out shows response time and data center processing time achieved using the improved model is slightly minimal compared to the other algorithms. This shows more effective load balancing by achieving a better overall throughput.
VL  - 8
IS  - 2
ER  -

Copy | Download