Application of Reinforcement Learning on Medium Access Control for Wireless Sensor Networks

Application of Reinforcement Learning on Medium Access Control for Wireless Sensor Networks PDF Author: Yi Chu
Publisher:
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Category :
Languages : en
Pages :

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Application of Reinforcement Learning on Medium Access Control for Wireless Sensor Networks

Application of Reinforcement Learning on Medium Access Control for Wireless Sensor Networks PDF Author: Yi Chu
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description


Deep Reinforcement Learning for Wireless Communications and Networking

Deep Reinforcement Learning for Wireless Communications and Networking PDF Author: Dinh Thai Hoang
Publisher: John Wiley & Sons
ISBN: 1119873738
Category : Technology & Engineering
Languages : en
Pages : 293

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Book Description
Deep Reinforcement Learning for Wireless Communications and Networking Comprehensive guide to Deep Reinforcement Learning (DRL) as applied to wireless communication systems Deep Reinforcement Learning for Wireless Communications and Networking presents an overview of the development of DRL while providing fundamental knowledge about theories, formulation, design, learning models, algorithms and implementation of DRL together with a particular case study to practice. The book also covers diverse applications of DRL to address various problems in wireless networks, such as caching, offloading, resource sharing, and security. The authors discuss open issues by introducing some advanced DRL approaches to address emerging issues in wireless communications and networking. Covering new advanced models of DRL, e.g., deep dueling architecture and generative adversarial networks, as well as emerging problems considered in wireless networks, e.g., ambient backscatter communication, intelligent reflecting surfaces and edge intelligence, this is the first comprehensive book studying applications of DRL for wireless networks that presents the state-of-the-art research in architecture, protocol, and application design. Deep Reinforcement Learning for Wireless Communications and Networking covers specific topics such as: Deep reinforcement learning models, covering deep learning, deep reinforcement learning, and models of deep reinforcement learning Physical layer applications covering signal detection, decoding, and beamforming, power and rate control, and physical-layer security Medium access control (MAC) layer applications, covering resource allocation, channel access, and user/cell association Network layer applications, covering traffic routing, network classification, and network slicing With comprehensive coverage of an exciting and noteworthy new technology, Deep Reinforcement Learning for Wireless Communications and Networking is an essential learning resource for researchers and communications engineers, along with developers and entrepreneurs in autonomous systems, who wish to harness this technology in practical applications.

Computational Intelligence for Wireless Sensor Networks

Computational Intelligence for Wireless Sensor Networks PDF Author: Sandip Kumar Chaurasiya
Publisher: CRC Press
ISBN: 1000594211
Category : Computers
Languages : en
Pages : 282

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Book Description
Computational Intelligence for Wireless Sensor Networks: Principles and Applications provides an integrative overview of the computational intelligence (CI) in wireless sensor networks and enabled technologies. It aims to demonstrate how the paradigm of computational intelligence can benefit Wireless Sensor Networks (WSNs) and sensor-enabled technologies to overcome their existing issues. This book provides extensive coverage of the multiple design challenges of WSNs and associated technologies such as clustering, routing, media access, security, mobility, and design of energy-efficient network operations. It also describes various CI strategies such as fuzzy computing, evolutionary computing, reinforcement learning, artificial intelligence, swarm intelligence, teaching learning-based optimization, etc. It also discusses applying the techniques mentioned above in wireless sensor networks and sensor-enabled technologies to improve their design. The book offers comprehensive coverage of related topics, including: Emergence of intelligence in wireless sensor networks Taxonomy of computational intelligence Detailed discussion of various metaheuristic techniques Development of intelligent MAC protocols Development of intelligent routing protocols Security management in WSNs This book mainly addresses the challenges pertaining to the development of intelligent network systems via computational intelligence. It provides insights into how intelligence has been pursued and can be further integrated in the development of sensor-enabled applications.

Wireless Sensor Networks - Design, Applications and Challenges

Wireless Sensor Networks - Design, Applications and Challenges PDF Author: Jaydip Sen
Publisher: BoD – Books on Demand
ISBN: 1803554533
Category : Technology & Engineering
Languages : en
Pages : 164

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Book Description
In the current era of pervasive computing and the Internet of Things (IoT), where technology seamlessly integrates into our environment and everyday objects, Wireless Sensor Networks (WSNs) will play increasingly critical roles in several applications and use cases. WSNs find diverse applications in the real world, including monitoring pollution levels in the environment and soil moisture for agriculture, as well as monitoring healthcare patients, traffic, and more. However, the design, optimization, and deployment of such networks face several challenges, including robust architectural design for complex applications, efficient routing, security and privacy of computing and communication, delay minimization, fault tolerance, and maintaining the quality of service in real-time applications. This book presents cutting-edge research and innovative applications in WSNs in various areas such as key management and security, efficiency in routing, machine learning models for dynamic adaptation, and temperature sensing. It is a valuable resource for researchers, engineers, practitioners, and graduate and doctoral students.

Machine Learning: Theoretical Foundations and Practical Applications

Machine Learning: Theoretical Foundations and Practical Applications PDF Author: Manjusha Pandey
Publisher: Springer Nature
ISBN: 9813365188
Category : Technology & Engineering
Languages : en
Pages : 172

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Book Description
This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9–12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.

Handbook of Research on Novel Soft Computing Intelligent Algorithms

Handbook of Research on Novel Soft Computing Intelligent Algorithms PDF Author: Pandian Vasant
Publisher: IGI Global
ISBN: 1466644516
Category : Technology & Engineering
Languages : en
Pages : 1173

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Book Description
"This book explores emerging technologies and best practices designed to effectively address concerns inherent in properly optimizing advanced systems, demonstrating applications in areas such as bio-engineering, space exploration, industrial informatics, information security, and nuclear and renewable energies"--Provided by publisher.

Research Anthology on Artificial Intelligence Applications in Security

Research Anthology on Artificial Intelligence Applications in Security PDF Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1799877485
Category : Computers
Languages : en
Pages : 2253

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Book Description
As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it’s important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research.

Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks

Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks PDF Author: Sagayam, K. Martin
Publisher: IGI Global
ISBN: 1799850692
Category : Computers
Languages : en
Pages : 405

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Book Description
Wireless sensor networks have gained significant attention industrially and academically due to their wide range of uses in various fields. Because of their vast amount of applications, wireless sensor networks are vulnerable to a variety of security attacks. The protection of wireless sensor networks remains a challenge due to their resource-constrained nature, which is why researchers have begun applying several branches of artificial intelligence to advance the security of these networks. Research is needed on the development of security practices in wireless sensor networks by using smart technologies. Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks provides emerging research exploring the theoretical and practical advancements of security protocols in wireless sensor networks using artificial intelligence-based techniques. Featuring coverage on a broad range of topics such as clustering protocols, intrusion detection, and energy harvesting, this book is ideally designed for researchers, developers, IT professionals, educators, policymakers, practitioners, scientists, theorists, engineers, academicians, and students seeking current research on integrating intelligent techniques into sensor networks for more reliable security practices.

IoT Security Paradigms and Applications

IoT Security Paradigms and Applications PDF Author: Sudhir Kumar Sharma
Publisher: CRC Press
ISBN: 1000172244
Category : Computers
Languages : en
Pages : 338

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Book Description
Integration of IoT (Internet of Things) with big data and cloud computing has brought forward numerous advantages and challenges such as data analytics, integration, and storage. This book highlights these challenges and provides an integrating framework for these technologies, illustrating the role of blockchain in all possible facets of IoT security. Furthermore, it investigates the security and privacy issues associated with various IoT systems along with exploring various machine learning-based IoT security solutions. This book brings together state-of-the-art innovations, research activities (both in academia and in industry), and the corresponding standardization impacts of 5G as well. Aimed at graduate students, researchers in computer science and engineering, communication networking, IoT, machine learning and pattern recognition, this book Showcases the basics of both IoT and various security paradigms supporting IoT, including Blockchain Explores various machine learning-based IoT security solutions and highlights the importance of IoT for industries and smart cities Presents various competitive technologies of Blockchain, especially concerned with IoT security Provides insights into the taxonomy of challenges, issues, and research directions in IoT-based applications Includes examples and illustrations to effectively demonstrate the principles, algorithm, applications, and practices of security in the IoT environment

Explainable Edge AI: A Futuristic Computing Perspective

Explainable Edge AI: A Futuristic Computing Perspective PDF Author: Aboul Ella Hassanien
Publisher: Springer Nature
ISBN: 3031182928
Category : Technology & Engineering
Languages : en
Pages : 187

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Book Description
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.