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Data Dissemination and Query in Mobile Social Networks
With the increasing popularization of personal hand-held mobile devices, more people use them to establish network connectivity and to query and share data among themselves in the …
Deep Cognitive Networks
Although deep learning models have achieved great progress in vision, speech, language, planning, control, and many other areas, there still exists a large performance gap between …
Self-* and P2P for Network Management
The network management community has been pushed towards the design of alternative management approaches able to support heterogeneity, scalability, reliability, and minor human …
Modeling Trust Context in Networks
We make complex decisions every day, requiring trust in many different entities for different reasons. These decisions are not made by combining many isolated trust evaluations. …
Modeling and Analysis of Voice and Data in Cognitive Radio Networks
This Springer Brief investigates the voice and elastic/interactive data service support over cognitive radio networks (CRNs), in terms of their delay requirements. The increased …
Energy-Efficient Area Coverage for Intruder Detection in Sensor Networks
This Springer Brief presents recent research results on area coverage for intruder detection from an energy-efficient perspective. These results cover a variety of topics, …
A Primer on Generative Adversarial Networks
This book is meant for readers who want to understand GANs without the need for a strong mathematical background. Moreover, it covers the practical applications of GANs, making it …
Cohesive Subgraph Search Over Large Heterogeneous Information Networks
This SpringerBrief provides the first systematic review of the existing works of cohesive subgraph search (CSS) over large heterogeneous information networks (HINs). It also covers …
Securing Unmanned Aerial Vehicle Networks
This book focuses on the model and algorithm aspects of securing Unmanned Aerial Vehicle Networks (UAV). To equip readers with the essential knowledge required for conducting …
Bringing Machine Learning to Software-Defined Networks
Emerging machine learning techniques bring new opportunities to flexible network control and management. This book focuses on using state-of-the-art machine learning-based …