Adaptive Load Balancing Using RR and ALB: Resource Provisioning in Cloud

Main Article Content

Santosh T. Waghmode
Bankat M. Patil

Abstract

Cloud Computing context, load balancing is an issue. With a rise in the number of cloud-based technology users and their need for a broad range of services utilizing resources successfully or effectively in a cloud environment is referred to as load balancing, has become a significant obstacle. Load balancing is crucial in storage systems to increase network capacity and speed up response times. The main goal is to present a new load-balancing mechanism that can balance incoming requests from users all over globally who are in different regions requesting data from remote data sources. This method will combine effective scheduling and cloud-based techniques. A dynamic load balancing method was developed to ensure that cloud environments have the ability to respond rapidly, in addition to running cloud resources efficiently and speeding up job processing times. Applications' incoming traffic is automatically split up across a number of targets, including Amazon EC2 instances, network addresses, and other entities by elastic load balancing. Elastic load balancing offers three distinct classifications of load balancer, and each one provides high availability, intelligent scalability, and robust security to guarantee the error-free functioning of your applications. Application load balancing and round robin are the two load balancing mechanisms in database cloud that are focus of this research study.

Article Details

How to Cite
Waghmode, S. T. ., & Patil, B. M. . (2023). Adaptive Load Balancing Using RR and ALB: Resource Provisioning in Cloud. International Journal on Recent and Innovation Trends in Computing and Communication, 11(7), 302–314. https://doi.org/10.17762/ijritcc.v11i7.7940
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References

Hemalatha, M. "An approach on semi-distributed load balancing algorithm for cloud computing system." International Journal of Computer Applications 975 (2018): 8887.

Al-Rayis, Ektemal, and Heba Kurdi. "Performance analysis of load balancing architectures in cloud computing." 2013 European Modelling Symposium. IEEE, 2013.

Waghmode, Santosh T., and Bankat M. Patil. "Adaptive Load Balancing in Cloud Computing Environment." International Journal of Intelligent Systems and Applications in Engineering 11.1s (2023): 209-217.

Kaur, Rajwinder, and Pawan Luthra. "Load balancing in cloud system using max min and min min algorithm." International Journal of Computer Applications 975 (2014): 8887.

Ristenpart, Thomas, et al. "Hey, you, get off of my cloud: exploring information leakage in third-party compute clouds." Proceedings of the 16th ACM conference on Computer and communications security. 2009.

Bleikertz, Sören, et al. "Security audits of multi-tier virtual infrastructures in public infrastructure clouds." Proceedings of the 2010 ACM workshop on Cloud computing security workshop. 2010.

Balduzzi, Marco, et al. "A Security Analysis of Amazon’s Elastic Compute Cloud Service–Long Version–." Publication: ACM (2011): 10.

Ms. Ritika Dhabalia, Ms. Kritika Dhabalia. (2012). An Intelligent Auto-Tracking Vehicle. International Journal of New Practices in Management and Engineering, 1(02), 08 - 13. Retrieved from http://ijnpme.org/index.php/IJNPME/article/view/5

Al Awadhi, Eman, Khaled Salah, and Thomas Martin. "Assessing the security of the cloud environment." 2013 7th IEEE GCC Conference and Exhibition (GCC). IEEE, 2013.

Randles, Martin, David Lamb, and Azzelarabe Taleb-Bendiab. "A comparative study into distributed load balancing algorithms for cloud computing." 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops. IEEE, 2010.

Serrano, Nicolas, Gorka Gallardo, and Josune Hernantes. "Infrastructure as a service and cloud technologies." IEEE Software 32.2 (2015): 30-36.

Kashani, Mostafa Haghi, and Ebrahim Mahdipour. "Load Balancing Algorithms in Fog Computing." IEEE Transactions on Services Computing 16.2 (2022): 1505-1521.

Sharma, Pradeep Kumar, et al. "Issues and challenges of data security in a cloud computing environment." 2017 IEEE.

8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON). IEEE, 2017.

Panda, Sanjaya K., and Prasanta K. Jana. "Load balanced task scheduling for cloud computing: A probabilistic approach." Knowledge and Information Systems 61.3 (2019): 1607-1631.

Ghomi, Einollah Jafarnejad, Amir Masoud Rahmani, and Nooruldeen Nasih Qader. "Load-balancing algorithms in cloud computing: A survey." Journal of Network and Computer Applications 88 (2017): 50-71.

Waghmode, Santosh T., and Bankat M. Patil. "Load Balanc?ng Technique in Distributed Systems: A Review." 2021 2nd Global Conference for Advancement in Technology (GCAT). IEEE, 2021.

Kumar, Mohit, and Subhash Chander Sharma. "Dynamic load balancing algorithm to minimize the makespan time and utilize the resources effectively in cloud environment." International Journal of Computers and Applications 42.1 (2020): 108-117.

Waghmode, Santosh T., and Bankat M. Patil. "Optimized and adaptive dynamic load balancing in distributed database server." (2022): 145-149.

Naaz, S. ., ShivaKumar, K. B., & B. D., P. . (2023). Aggregation Signature of Multi Scale Features from Super Resolution Images for Bharatanatyam Mudra Classification for Augmented Reality Based Learning. International Journal of Intelligent Systems and Applications in Engineering, 11(3s), 224–234. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2565

Mishra, Sambit Kumar, Bibhudatta Sahoo, and Priti Paramita Parida. "Load balancing in cloud computing: a big picture." Journal of King Saud University-Computer and Information Sciences 32.2 (2020): 149-158.

Shukur, Hanan, et al. "Cloud computing virtualization of resources allocation for distributed systems." Journal of Applied Science and Technology Trends 1.3 (2020): 98-105.

Narhe, Aditya, et al. "SQL Query Formation for Database System using NLP." International Journal of Engineering Research and 8 (2019).

Andrew Hernandez, Stephen Wright, Yosef Ben-David, Rodrigo Costa, David Botha. Risk Assessment and Management with Machine Learning in Decision Science. Kuwait Journal of Machine Learning, 2(3). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/196

Sharma T, Banga VK. Efficient and enhanced algorithm in cloud computing. International Journal of Soft Computing and Engineering (IJSCE) ISSN. 2013 Mar:-2231-307.

Domanal SG, Reddy GR. Optimal load balancing in cloud computing by efficient utilization of virtual machines. In2014 sixth international conference on communication systems and networks (COMSNETS) 2014 Jan 6 (pp. 1-4). IEEE.

Morzelona, R. (2021). Human Visual System Quality Assessment in The Images Using the IQA Model Integrated with Automated Machine Learning Model . Machine Learning Applications in Engineering Education and Management, 1(1), 13–18. Retrieved from http://yashikajournals.com/index.php/mlaeem/article/view/5

Tilak S, Patil D. A survey of various scheduling algorithms in cloud environment. International Journal of Engineering Inventions. 2012 Sep-1(2):36-9.

Kumar M, Dubey K, Sharma SC. Job scheduling algorithm in cloud environment considering the priority and cost of job. InProceedings of Sixth International Conference on Soft Computing for Problem Solving: SocProS 2016, Volume 2 2017 (pp. 313-320). Springer Singapore.

https://aws.amazon.com/

Ana Silva, Deep Learning Approaches for Computer Vision in Autonomous Vehicles , Machine Learning Applications Conference Proceedings, Vol 1 2021.

Khetani, V. ., Gandhi, Y. ., Bhattacharya, S. ., Ajani, S. N. ., & Limkar, S. (2023). Cross-Domain Analysis of ML and DL: Evaluating their Impact in Diverse Domains. International Journal of Intelligent Systems and Applications in Engineering, 11(7s), 253–262.

Vyas, A. ., & Sharma, D. A. . (2020). Deep Learning-Based Mango Leaf Detection by Pre-Processing and Segmentation Techniques. Research Journal of Computer Systems and Engineering, 1(1), 11–16. Retrieved from https://technicaljournals.org/RJCSE/index.php/journal/article/view/18

R. Patil Rashmi, Y. Gandhi, V. Sarmalkar, P. Pund and V. Khetani, "RDPC: Secure Cloud Storage with Deduplication Technique," 2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, India, 2020, pp. 1280-1283, doi: 10.1109/I-SMAC49090.2020.9243442.