Abstract: In recent years, IT managers of large enterprises and stakeholders have turned to cloud computing due to the benefits of reduced maintenance costs and security concerns, as well as access to high-performance hardware and software resources. The two main challenges that need to be considered in terms of importance are ensuring that everyone has access to services and finding efficient allocation options. First, especially with software services, it is very difficult to predict every service that may be needed. The second challenge is to select the best independent service among different providers with features related to application reliability. This paper presents a framework that uses the particle swarm optimization technique to optimize reliability parameters in distributed systems applications. The proposed strategy seeks a program with the best service and a high degree of competence. Although this method does not provide an exact solution, the particle swarm optimization algorithm reaches a result close to the best solution and reduces the time required to adjust the parameters of distributed systems applications. The results of the work have been compared with the genetic algorithm and it has been shown that the PSO algorithm has a shorter response time than both the genetic algorithm and the PSO. Also, the PSO algorithm shows strong stability and ensures that the solution obtained from the proposed approach will be close to the optimal solution.

Wenli WANG and Yanlin BAI. “Reliability in Cloud Computing Applications with Chaotic Particle Swarm Optimization Algorithm”. International Journal of Advanced Computer Science and Applications (IJACSA) 15.7 (2024). http://dx.doi.org/10.14569/IJACSA.2024.01507115

@article{WANG2024,
title = {Reliability in Cloud Computing Applications with Chaotic Particle Swarm Optimization Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.01507115},
url = {http://dx.doi.org/10.14569/IJACSA.2024.01507115},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {7},
author = {Wenli WANG and Yanlin BAI}
}