As enterprise access networks expand to accommodate more mobile users, a diverse array of devices, and new cloud-based applications, ensuring consistent end-to-end user performance has become increasingly complex. To address these challenges, recent advancements in big data network analytics, AI, and cloud computing are being utilized. AI is now more deeply integrated into software that manages networks, storage, and computing resources.
This edited volume explores how modern network analytics, IoT, and cloud computing platforms are being used to collect, analyze, and correlate vast amounts of big data across the entire network stack. The goal is to enhance quality of service (QoS) and quality of experience (QoE), as well as to boost overall network performance. The book covers topics such as big data and AI techniques for processing the massive data generated by IoT devices, cloud storage optimization, the development of next-generation access protocols and internet architectures, fault tolerance, and reliability in intelligent networks, along with a variety of emerging applications.
This book is a valuable resource for researchers, scientists, engineers, professionals, advanced students, and faculty in ICT, data science, networking, AI, machine learning, and sensing. It will also interest professionals in data science, AI, cloud, and IoT startups, as well as developers and system designers.
