Authors : Rajashri. S. Shekokare; Dr. Rais Abdul Hamid Kha; Dr. Pawan Baldhare; Mohammad. Muqeem

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/ymj7zv8c

Scribd : https://tinyurl.com/2yv66xsc

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY963

Abstract : In this paper, a dynamic resource allocation technique for cloud computing is proposed. Instead of using local servers or computer hard drives, cloud computing uses remote servers hosted on the internet to store and access data and programs. The three service models offered by cloud computing are IAAS (Infrastructure as a Service), PAAS (Platform as a Service), and SAAS (Software as a Service). Cloud computing is also known as International Computing. Hardware as a Service (HAAS) is another name for IAAS. It is an internet-managed computing infrastructure. Users can avoid the expense and complexity of buying and maintaining real servers by using IAAS models. Providing mechanisms for effective resource management is a key goal of cloud computing in the future. We present a novel approach in this paper called dynamic scheduling and consolidation mechanism, which distributes resources according to the demand of virtual machines (VMs) on infrastructure as a service (IAAS).With the use of this technique, users can add, remove, or modify instances dynamically based on user- specified conditions and load. Our goal is to create a virtual machine monitoring- based load balancing algorithm that maximizes or minimizes various performance parameters (such throughput) for clouds of varying sizes.

Keywords : Infrastructure-As-A-Service , Amazon Ec2, Optimizing VM Load, Load Balancing, Platform-As-A- Service, Software–As-A-Service, Cloud Computing, Amazon AWS.

References :

1. Thomas A. Hen zinger Anmol V. Singh Vasu Singh Thomas Wies Damien Zufferey, “FlexPRICE:Flexible Provisioning of Resources in a Cloud Environment”, IEEE 3rd International Conference on Cloud Computing 5-10, july 2010, pp. 8390.
2. Shu-Ching Wang, Kuo-Qin Yan, (Corresponding author), Wen-Pin Liao and Shun-Sheng Wang,“Towards a Load Balancing in a Three-level Cloud Computing Network”, IEEE 3rd International Conference on Computer Science & Information Technology 9-11, July 2010, pp. 108-113.
3. Yoshitomo MURATA, Ryusuke EGAWA, Manabu HIGASHIDA, Hiroaki KOBAYASHI,“A History-BaJob Scheduling Mechanism for the Vector Computing Cloud”, 2010, 10th Annual International Symposium on Applications and the Internet, 19-23, July 2010, pp. 125-128.
4. Andrew J. Younge, Gregor von Laszewski, Lizhe Wang, Sonia Lopez-Alarcon, Warren Carithers,“Eficient Resource Management for Cloud Computing Environments”, International Conference on Green Computing,15-18,Aug 2010, pp. 357-364.
5. LIU Jia, HUANG Ting-Lei,“Dynamic Route Scheduling for Optimization of Cloud Database”.
6. Barrie Sisisky,” Cloud Computing Bible”. John Wiley & Sons, January 11, 2011.
7. Introduction to Cloud Computing Architecture, White paper, SUN, Microsystems,1st edition, June 2009.
8. M.Rajendra Prasad, D. B. (2013). Cloud Computing : Research Issues and Implications. International Journalof Cloud Computing and Services Science , 2, 134-139.
9. Yi Zhao, Wenlong Huang,“Adaptive Distributed Load Balancing Algorithm based on Live Migration of Virtual Machines in Cloud”, IEEE 5th International Joint Conference on INC,IMS and IDC, 25-27 Aug 2009, pp.170-176
10. Martin Randles, David Lamb, A. Taleb-Bendiab,“A Comparative Study into Distributed Load Balancing Algorithms for Cloud Computing”, IEEE 24th International Conference on Advanced Information Networking and Applications Workshops, 20-23, April 2010, pp. 551-556.
11. Huai Zhang, Shufen Zhang, Xuebin Chen, Xiuzhen Huo,“Cloud Computing Research and Development Trend” Second International Conference on Future Networks, 22-24 Jan 2010, pp. 93-97.
12. Cary Landis, Dan Blacharski,“Cloud Computing Made Easy”, Version 0.3
13. Ioannis Psoroulas, Ioannis Anagnostopoulos, Vassili Loumos, Eleftherios Kayafas,“A Study of the Parameters Concerning Load Balancing Algorithms”, IJCSNS International Journal of Computer Science and Network Security, Vol. 7, No. 4, 2007, pp. 202-214.
14. Sandeep Sharma, Sarabjit Singh, Meenakshi Sharma “Performance Analysis of Load Balancing Algorithms”, World Academy of Science, Engineering and Technology, 38, 2008 pp. 269- 272.
15. Amazon Inc.,”Amazon Elastic Compute Cloud,” https://aws.amazon .com.
16. Dynamic allocation method for efficient load balancing in virtual machines for cloud computing environment, Vol.3, N September 2012, DOI : 10.5121/acij.2012.3506