CFP last date
20 January 2025
Reseach Article

Proposing Priority based Dynamic Resource Allocation [PDRA] Model in Cloud Computing

by Amit Chaturvedi, Praveen Sengar, Kalpana Sharma
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 4
Year of Publication: 2018
Authors: Amit Chaturvedi, Praveen Sengar, Kalpana Sharma
10.5120/ijca2018917508

Amit Chaturvedi, Praveen Sengar, Kalpana Sharma . Proposing Priority based Dynamic Resource Allocation [PDRA] Model in Cloud Computing. International Journal of Computer Applications. 182, 4 ( Jul 2018), 17-22. DOI=10.5120/ijca2018917508

@article{ 10.5120/ijca2018917508,
author = { Amit Chaturvedi, Praveen Sengar, Kalpana Sharma },
title = { Proposing Priority based Dynamic Resource Allocation [PDRA] Model in Cloud Computing },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2018 },
volume = { 182 },
number = { 4 },
month = { Jul },
year = { 2018 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number4/29750-2018917508/ },
doi = { 10.5120/ijca2018917508 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:10:22.120467+05:30
%A Amit Chaturvedi
%A Praveen Sengar
%A Kalpana Sharma
%T Proposing Priority based Dynamic Resource Allocation [PDRA] Model in Cloud Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 4
%P 17-22
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Scaling of resources in cloud computing is essential for the better utilization of resources. Dynamic allocation of the resources / VMs in the multi-tenant environment is the need of the cloud computing. Virtualization technologies evolved to help IT organizations and to improve the efficiency of their hardware resources by partitioning hardware to provide simultaneous support to multiple applications and their corresponding software stacks. If the resource utilization is not properly allocated to applications, it will lead to the faulty services to the customers. The Cloud is the hub of resources, and can be used by any client on rental bases and on no demand resources can left with no usage. Clients/ Brokers may request for the multiple VMs/ other resources like, applications, database, operating system etc, but the resources are limited. So, there is the need of such a system to handle this allocation and deallocation of resources or VMs. By this PDRA model, authors have presented an idea to handle the resources/ VMs allocation and deallocation system.

References
  1. A. Rashid, Dr. Amit Chaturvedi, “A Study on Resource Pooling, Allocation and Virtualization Tools used for Cloud Computing”, International Journal of Computer Applications (0975 – 8887), Volume 168, No. 2 , June 2017
  2. Dr. M. Durairaj, P. Kannan, “Elastic Resource Allocation Challenges in Cloud computing System”, nternational Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS), Vol. 12, issue 2, March -May 2015, pp. 180-184
  3. Nisha Sharma, Mamta Dhanda, “Improving Resource Allocation in Virtualized Cloud Environment”, International Journal of Computer Science Trends and Technology (IJCST) –Volume 2, Issue 4, Jul-Aug 2014
  4. Saraswathi AT, Kalaashri Y R A, Dr. S. Padmavathi, “Dynamic Resource Allocation Scheme in Cloud Computing”, Elsevier, Procedia Computer Science 47 (2015), pp. 30-36.
  5. N. Kumar, S. Saxena, “A Preference-based Resource Allocation In Cloud Computing Systems”, 3rd International Conference on Recent Trends in Computing 2015 (ICRTC-2015), Elsevier, Procedia Computer Science 57 ( 2015 ), pp. 104 – 111
  6. J. Chen, Y. Wang, “A Resource Demand Prediction Method Based on EEMD in Cloud Computing”, 8th International Congress of Information and Communication Technology (ICICT -2018), Elsevier, Procedia Computer Science 131 (2018), pp. 116–123
  7. D. Kumar, G. Baranwal, Z. Raza, D.P. Vidyarthi, “A truthful combinatorial double auction-based marketplace mechanism for cloud computing”, The Journal of Systems and Software 140 (2018), pp. 91–108
  8. M.G. Arani, S. Jabbehdari, M. A. Pourmina, “An autonomic resource provisioning approach for service-based cloud applications: A hybrid approach”, Future Generation Computer Systems, ISSN : 0167-739X, 2017, pp. 1-20
  9. P. Samimi, Y. Teimouri, M. Mukhtar, “A combinatorial double auction resource allocation model in cloud computing”, Information Sciences 357 (2016), pp. 201–216
  10. S. Vakilinia, M. M. Ali, D. Qiu, “Modeling of the resource allocation in cloud computing centers”, Elsevier, Computer Networks (2015), ISSN : 1389-1286, pp. 1-18
  11. P. Pradhan, P. K. Behera, B N B Ray, “Modified Round Robin Algorithm for Resource Allocation in Cloud Computing”, International Conference on Computational Modeling and Security (CMS 2016), Procedia Computer Science 85 ( 2016 ), pp. 878 – 890
  12. B. Shrimali, H. Patel, “Multi-objective optimization oriented policy for performance and energy efficient resource allocation in Cloud environment”, Journal of King Saud University, Computer and Information Sciences (2017), ISSN : 1319-1578, pp 1-10
  13. W.Lin, J.Z.Wang, C. Liang, D. Qi, “A Threshold-based Dynamic Resource Allocation Scheme for Cloud Computing”, PEEA 2011, Procedia Engineering 23 (2011),ISSN: 1877-7058, pp. 695-703.
  14. F. A. Omara, S.M. Khattab, R.Sahal, “Optimum Resource Allocation of Database in Cloud Computing”, Egyptian Informatics Journal (2014) 15, pp. 1–12
  15. S. Z. Goher, P. Bloodsworth, R.Ur Rasool, R. McClatchey, “Cloud provider capacity augmentation through automated resource bartering”, Future Generation Computer Systems (2017)
Index Terms

Computer Science
Information Sciences

Keywords

Virtual Machine dynamic allocation elasticity cloud scaling..