Quantum-Edge Synergy: A Novel Framework for Real-Time IoT Analytics Beyond Cloud and Edge Computing

Abstract

The Adaptation of the Internet of Things (IoT) is increasing to gain more insight from data from IOT devices [1]. Using cloud technologies to connect IOT devices and streaming real-time data to perform real-time analytics helps organizations find meaningful information that can drive growth and innovation [14]. Major cloud service providers support IoT device connectivity, data storage capabilities in different formats, and scalable computer and analytical tools [15]; however, the exponential growth of IoT devices and data has exposed limitations in traditional cloud architecture, such as latency, scalability, and security [37]. This paper discusses edge computing, quantum computing technologies, and their impact on the IoT ecosystem. Using simulations and conducting case studies, this paper explains that QES can optimize latency by up to sixty percent and enhance energy efficiency by forty-five percent in comparison to the cloud and edge computing that is currently in use. This provides a scalable solution for Internet of Things applications of the next generation, such as smart cities, autonomous systems, and healthcare monitoring technology. This paper focuses on Internet of Things devices, and their integration covers enhanced security, faster connectivity, and real-time data analytics, among other issues. This work addresses both present and future expansion of Internet of Things acceptance. Some topics covered include serverless computing, green computing solutions, cost, and reliability, fueling the next generation of Internet of Things-cloud ecosystems. This paper aims to provide a comprehensive and forward-looking perspective on the role that cloud computing plays on the Internet of Things (IoT), addressing the challenges currently being faced and opening up new opportunities.