Load Balancing Strategies for Cloud Computing: A Simulation-Based Study

Authors Navneet Kumar Rajpoot, Prabhdeep Singh, Bhaskar Pant

Department of Computer Science & Engineering, Graphic Era Deemed to be University, Dehradun, India

Е-mail navneetrajpootgeu@gmail.com
Issue Volume 15, Year 2023, Number 3
Dates Received 25 April 2023; revised manuscript received 17 June 2023; published online 30 June 2023
Citation Navneet Kumar Rajpoot, Prabhdeep Singh, Bhaskar Pant, J. Nano- Electron. Phys. 15 No 3, 03023 (2023)
DOI https://doi.org/10.21272/jnep.15(3).03023
PACS Number(s) 07.05.Tp
Keywords Ant Colony Optimization, Cloud computing, CloudAnalyst, Load balancing, Nature-inspired algorithm.

The CloudAnalyst simulation tool offers various load balancing techniques that can be utilized for efficiently distributing tasks. This research paper explores various load balancing techniques by utilizing the CloudAnalyst simulation tool. The research paper intends to evaluate and contrast the effectiveness of conventional load balancing techniques. While gathering information, the technique entails the simulation of diverse cases with varying parameters, including server capacity, workload, and network latency. The results are compared and contrasted to demonstrate that each technique for load balancing has strengths and weaknesses, and that the most suitable technique should be chosen based on the specific scenario. The Round Robin algorithm is easy to implement but may not be suitable for all scenarios. The Least Connection algorithm is suitable for scenarios where server capacity is not uniform. The IP Hash algorithm is useful for stateful applications, while the Weighted Round Robin algorithm is suitable for scenarios where servers have different capacities. The Least time algorithm is useful for scenarios where processing time is critical. The proposed framework for this research paper is based on nature-inspired load balancing using the CloudAnalyst simulation tool. The framework aims to develop a load balancing algorithm that can adapt to changing workload patterns in real-time.

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