IoT-Based Social Device Network with Cloud Computing Architecture: A Systematic Review

The Internet of Things (IoT) has redefined how devices interact, enabling a transition from isolated machine communication to dynamic, intelligent networks known as Social Device Networks (SDNs). These networks comprise interconnected devices that establish relationships based on context, proximity, functionality, or user preferences. With the growing need for efficient data handling, resource sharing, and real-time analytics, cloud computing has emerged as a key enabler of scalable, flexible, and cost-effective infrastructures for Internet of Things (IoT)- based Software-Defined Networks (SDNs). This systematic review examines the integration of Internet of Things (IoT)- based Software-Defined Networks (SDNs) with cloud computing architecture, focusing on their structural designs, data communication protocols, service models, and security mechanisms. By analysing scholarly articles published between 2013 and 2024—primarily from IEEE and other reputable databases—this paper synthesizes key findings, technological trends, and challenges faced in deploying such systems. We examine the evolution from traditional cloud-based systems to hybrid models that incorporate fog and edge computing to reduce latency and improve responsiveness in time-critical applications. The review also emphasizes the importance of secure communication protocols such as MQTT, CoAP, and AMQP for seamless device collaboration within social networks. In addition to identifying current gaps in security, privacy, and interoperability, this review highlights promising applications in healthcare, smart cities, industrial automation, and transportation. The convergence of AI with SDNs, along with the deployment of next-generation networks such as 5G, is expected to further enhance the performance and scalability of these systems. This paper offers a comprehensive foundation for future research and Development in IoT-enabled social device ecosystems powered by cloud computing.