International Journal of Science, Engineering and TechnologyAuthors: Shaurya Nivaran
Abstract: The proliferation of Internet of Things (IoT) devices and cloud computing services has transformed wireless environments, creating unprecedented opportunities and challenges in data management, system integration, and real-time communication. Efficient interaction between heterogeneous IoT devices and cloud infrastructures requires intelligent abstractions that can simplify complexity while optimizing performance. This paper proposes a novel framework for intelligent system abstractions that enables seamless cloud-IoT interaction in wireless spaces. The framework leverages context-aware data processing, adaptive network management, and predictive analytics to provide real-time insights, improve resource utilization, and enhance system responsiveness. By abstracting the underlying heterogeneity of devices and communication protocols, the system allows developers to focus on high-level functionality without compromising efficiency or scalability. Experimental evaluations, including simulations and deployment in real-world wireless environments, demonstrate significant improvements in latency reduction, throughput, and robustness under variable network conditions. Additionally, the framework supports dynamic adaptation to changing workloads and environmental conditions, making it suitable for large-scale, distributed IoT-cloud ecosystems. The proposed approach contributes to the advancement of intelligent wireless systems by providing a scalable and flexible architecture that bridges the gap between IoT devices and cloud services. These findings highlight the potential of system abstractions to accelerate innovation, simplify development, and enable efficient deployment of complex IoT-cloud solutions across diverse wireless networks.
DOI: https://doi.org/10.5281/zenodo.18161357
