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@article{170656,
        author = {Dr. Gopal Sharma},
        title = {An Extensive Analysis of Resource Distribution in Cloud Computing Settings},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {7},
        pages = {495-500},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=170656},
        abstract = {is study providing a comprehensive analysis of resource allocation mechanisms and their impact on system efficiency, focusing on key challenges such as load balancing, latency reduction, energy efficiency, and resource overprovisioning. It explores state-of-the-art algorithms and strategies, including heuristic, metaheuristic, and AI-based approaches, while addressing trade-offs between computational efficiency and system complexity. Furthermore, this paper evaluates resource allocation performance in multi-cloud and hybrid-cloud environments, highlighting real-world case studies and experimental results. The findings aim to guide the development of robust, adaptive resource distribution frameworks that enhance service delivery while minimizing operational costs. The study underscores the importance of integrating advanced predictive analytics and machine learning to foster intelligent, self-optimizing cloud ecosystems.},
        keywords = {loud computing, resource distribution, load balancing, energy efficiency, machine learning, multi-cloud environments, adaptive systems, sustainability, predictive analytics, hybrid cloud.},
        month = {December},
        }