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CloudOptimus: AI driven Dynamic Resource Allocation in Cloud Environment using Hybrid Algorithm

Year: 2025

Type: article

Abstract: —This paper introduces a new method with a Hybrid Particle Swarm Optimization (HPSO) algorithm to improve resource allocation in cloud computing. The proposed system incorporates adaptive mechanisms and hybridization approaches to enhance convergence rate and solution quality. Extensive simulations prove that the HPSO algorithm performs better than conventional PSO and other heuristic approaches regarding execution time, resource utilization, and Quality of Service (QoS) measures. The results indicate that HPSO provides a strong and scalable solution for dynamic resource allocation in heterogeneous cloud environments. Index Terms—Hybrid, Particle Swarm Optimization, Cloud, Quality of Service, Genetic Algorithm, Reinforcement Learning

Source: INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT

DOI: 10.55041/ijsrem47090

Author: Suma Gowda

Language: English

Topic: Cloud Computing and Resource Management

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W4410171793

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