Beyond The Signal Artificial Intelligence Cloud And Security In Next Gen Telecom Networks
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Beyond the Signal: Artificial Intelligence, Cloud, and Security in Next-Gen Telecom Networks
Author: Venkata Bharadwaj komaragiri
language: en
Publisher: Deep Science Publishing
Release Date: 2025-04-21
The telecommunications industry is rapidly evolving from a utility-driven service to a data-centric, intelligent ecosystem. Beyond the Signal: AI, Cloud, and Security in Next-Gen Telecom Networks explores this dynamic transformation, focusing on the critical technologies that are redefining how networks are built, operated, and protected in the era of 5G and beyond. As networks grow more complex and user expectations soar, the integration of Artificial Intelligence (AI), cloud computing, and robust cybersecurity has become not just advantageous—but essential. AI is enabling smarter, self-optimizing networks that can predict faults, manage traffic in real time, and deliver seamless user experiences. Cloud infrastructure is empowering telcos to scale efficiently, launch services faster, and support diverse applications—from edge computing to IoT ecosystems. Meanwhile, cybersecurity is no longer a siloed function but a foundational pillar, ensuring trust, privacy, and resilience in an increasingly connected world. This book offers a comprehensive look at how these technologies intersect and work in harmony to power next-generation telecom networks. From AI-driven network automation and predictive maintenance to cloud-native architectures and zero-trust security frameworks, each chapter uncovers key innovations shaping the telecom landscape. We also explore the challenges that accompany this shift—data sovereignty, vendor interoperability, regulatory compliance, and the need for a skilled workforce to support this digital leap. With insights from industry leaders, real-world implementations, and emerging trends, Beyond the Signal serves as both a technical guide and a strategic vision for telecom professionals, policymakers, and technology enthusiasts. The future of telecom is not just about faster speeds or lower latency—it’s about intelligent, secure, and adaptive networks that serve as the backbone of digital society. This book invites you to explore that future and discover how AI, cloud, and security are taking us far beyond the signal.
Implementing Data Analytics and Architectures for Next Generation Wireless Communications
Wireless communication is continuously evolving to improve and be a part of our daily communication. This leads to improved quality of services and applications supported by networking technologies. We are now able to use LTE, LTE-Advanced, and other emerging technologies due to the enormous efforts that are made to improve the quality of service in cellular networks. As the future of networking is uncertain, the use of deep learning and big data analytics is a point of focus as it can work in many capacities at a variety of levels for wireless communications. Implementing Data Analytics and Architectures for Next Generation Wireless Communications addresses the existing and emerging theoretical and practical challenges in the design, development, and implementation of big data algorithms, protocols, architectures, and applications for next generation wireless communications and their applications in smart cities. The chapters of this book bring together academics and industrial practitioners to exchange, discuss, and implement the latest innovations and applications of data analytics in advanced networks. Specific topics covered include key encryption techniques, smart home appliances, fog communication networks, and security in the internet of things. This book is valuable for technologists, data analysts, networking experts, practitioners, researchers, academicians, and students.
Explainable Edge AI: A Futuristic Computing Perspective
Author: Aboul Ella Hassanien
language: en
Publisher: Springer Nature
Release Date: 2022-11-10
This book presents explainability in edge AI, an amalgamation of edge computing and AI. The issues of transparency, fairness, accountability, explainability, interpretability, data-fusion, and comprehensibility that are significant for edge AI are being addressed in this book through explainable models and techniques. The concept of explainable edge AI is new in front of the academic and research community, and consequently, it will undoubtedly explore multiple research dimensions. The book presents the concept of explainability in edge AI which is the amalgamation of edge computing and AI. In the futuristic computing scenario, the goal of explainable edge AI will be to execute the AI tasks and produce explainable results at the edge. First, this book explains the fundamental concepts of explainable artificial intelligence (XAI), then it describes the concept of explainable edge AI, and finally, it elaborates on the technicalities of explainability in edge AI. Owing to the quick transition in the current computing scenario and integration with the latest AI-based technologies, it is significant to facilitate people-centric computing through explainable edge AI. Explainable edge AI will facilitate enhanced prediction accuracy with the comprehensible decision and traceability of actions performed at the edge and have a significant impact on futuristic computing scenarios. This book is highly relevant to graduate/postgraduate students, academicians, researchers, engineers, professionals, and other personnel working in artificial intelligence, machine learning, and intelligent systems.