Authors: Dr. Jyoti, Associate Professor, Ms. Jyoti
Abstract: The rapid expansion of the Internet of Things (IoT) has led to a massive increase in the number of connected devices, generating large volumes of heterogeneous data. Managing this data and ensuring efficient device performance requires advanced computing infrastructures. Cloud computing offers a scalable and cost-effective platform to support IoT ecosystems by providing storage, processing, and analytics capabilities on demand. This study explores the integration of IoT ecosystems with cloud computing to optimize IoT performance. It examines IoT architecture, communication protocols, and data management strategies while highlighting the role of cloud-based services in reducing latency, improving scalability, and enhancing security. The research also emphasizes performance optimization through edge computing, load balancing, and intelligent resource allocation. The findings suggest that a well-structured IoT-cloud integration can significantly improve system efficiency, reduce operational costs, and enable real-time decision-making, paving the way for smarter and more sustainable IoT deployments.This paper lays the foundation for this research by introducing the concepts of cloud computing, IoT ecosystems, and deep learning, while highlighting their interdependencies and potential for performance optimization. The paper also outlines the motivation behind this study, identifies key challenges, and presents the significance and contributions of the research.
