Handbook Of Research On Advances In Data Analytics And Complex Communication Networks

"This edited book discusses data analytics and complex communication networks and recommends new methodologies, system architectures, and other solutions to prevail over the current limitations faced by the field"--

"This edited book discusses data analytics and complex communication networks and recommends new methodologies, system architectures, and other solutions to prevail over the current limitations faced by the field"--

To overcome the constraints of 5G for supporting new challenges, 6G wireless systems must be developed with new and attractive features. These systems are expected to increase performance and maximize quality of service several folds more than 5G along with other exciting features. However, 6G is still in its infancy and must be explored. The Handbook of Research on Design, Deployment, Automation, and Testing Strategies for 6G Mobile Core Network discusses the technological feats used in the new 6G wireless systems. It discusses the design, automation, and uses for industry as well as testing strategies. Covering topics such as 6G architecture, smart healthcare, and wireless communication, this major reference work is an excellent resource for computer scientists, engineers, students and professors in higher education, researchers, and academicians.

This book gathers outstanding research papers presented at the 6th International Joint Conference on Advances in Computational Intelligence (IJCACI 2022), held in hybrid mode during October 15 – 16, 2022. IJCACI 2022 is jointly organized by Jahangirnagar University (JU), Bangladesh and South Asian University (SAU), India. The book presents the novel contributions in areas of computational intelligence and it serves as a reference material for advance research. The topics covered are collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

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.

Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.

Even though many data analytics tools have been developed in the past years, their usage in the field of cyber twin warrants new approaches that consider various aspects including unified data representation, zero-day attack detection, data sharing across threat detection systems, real-time analysis, sampling, dimensionality reduction, resource-constrained data processing, and time series analysis for anomaly detection. Further study is required to fully understand the opportunities, benefits, and difficulties of data analytics and the internet of things in today’s modern world. New Approaches to Data Analytics and Internet of Things Through Digital Twin considers how data analytics and the internet of things can be used successfully within the field of digital twin as well as the potential future directions of these technologies. Covering key topics such as edge networks, deep learning, intelligent data analytics, and knowledge discovery, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

Enormous developments have been made in the field of information and communication technologies (ICT) during the past four decades as ICT has spread rapidly in the world and become a significant part of daily life for economic units. ICT development and penetration are continuing to affect all aspects of societies and have led to significant changes in almost all disciplines such as education, environment, economics, management, energy, health, and medical care. Economic and Social Implications of Information and Communication Technologies explores the economic and social implications of ICT development and penetration from a multidisciplinary perspective. Covering key topics such as sustainability, public health, and economic growth, this reference work is ideal for managers, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.