Details

Fog Computing for Intelligent Cloud IoT Systems


Fog Computing for Intelligent Cloud IoT Systems


Advances in Learning Analytics for Intelligent Cloud-IoT Systems 1. Aufl.

von: Chandan Banerjee, Anupam Ghosh, Rajdeep Chakraborty, Ahmed A. Elngar

173,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 20.05.2024
ISBN/EAN: 9781394175338
Sprache: englisch
Anzahl Seiten: 464

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Beschreibungen

<b>FOG COMPUTING FOR INTELLIGENT CLOUD IOT SYSTEMS</b> <p> <b>This book is a comprehensive guide on fog computing and how it facilitates computing, storage, and networking services</b> <p>Fog computing is a decentralized computing structure that connects data, devices, and the cloud. It is an extension of cloud computing and is an essential concept in IoT (Internet of Things), as it reduces the burden of processing in cloud computing. It brings intelligence and processing closer to where the data is created and transmitted to other sources. <p>Fog computing has many benefits, such as reduced latency in processing data, better response time that helps the user’s experience, and security and privacy compliance that assures protecting the vital data in the cloud. It also reduces the cost of bandwidth, because the processing is achieved in the cloud, which reduces network bandwidth usage and increases efficiency as user devices share data in the local processing infrastructure rather than the cloud service. <p>Fog computing has various applications across industries, such as agriculture and farming, the healthcare industry, smart cities, education, and entertainment. For example, in the agriculture industry, a very prominent example is the SWAMP project, which stands for Smart Water Management Platform. With fog computing’s help, SWAMP develops a precision-based smart irrigation system concept used in agriculture, minimizing water wastage. <p>This book is divided into three sections. The first section studies fog computing and machine learning, covering fog computing architecture, application perspective, computational offloading in mobile cloud computing, intelligent Cloud-IoT systems, machine learning fundamentals, and data visualization. The second section focuses on applications and analytics, spanning various applications of fog computing, such as in healthcare, Industry 4.0, cancer cell detection systems, smart farming, and precision farming. This section also covers analytics in fog computing using big data and patient monitoring systems, and the emergence of fog computing concerning applications and potentialities in traditional and digital educational systems. Security aspects in fog computing through blockchain and IoT, and fine-grained access through attribute-based encryption for fog computing are also covered. <p><b>Audience</b> <p>The book will be read by researchers and engineers in computer science, information technology, electronics, and communication specializing in machine learning, deep learning, the cyber world, IoT, and security systems.
<p>Preface xvii</p> <p><b>Part I: Study of Fog Computing and Machine Learning 1</b></p> <p>1 Fog Computing: Architecture and Application 3<br /><i>Soumen Swarnakar</i></p> <p>2 A Comparative Review on Different Techniques of Computation Offloading in Mobile Cloud Computing 33<br /><i>Priyajit Sen, Tamanna Islam, Rajat Pandit and Debabrata Sarddar</i></p> <p>3 Fog Computing for Intelligent Cloud–IoT System: Optimization of Fog Computing in Industry 4.0 45</p> <p>Mayank Patel, Monika Bhatt and Ankush Patel</p> <p>4 Machine Learning Integration in Agriculture Domain: Concepts and Applications 71<br /><i>Ankur Biswas and Rita Banik</i></p> <p>5 Role of Intelligent IoT Applications in Fog Computing 99<br /><i>Pawan Whig, Dhaya Sindhu Battina, Srinivas Venkata, Ashima Bhatnagar Bhatia and Yusuf Jibrin Alkali</i></p> <p>6 SaaS-Based Data Visualization Platform—A Study in COVID-19 Perspective 119<br /><i>S. Majumder, A. Shaw, R. Keshri and A. Chakraborty</i></p> <p>7 A Complete Study on Machine Learning Algorithms for Medical Data Analysis Inderdeep 137<br /><i>Kaur and Aleem Ali</i></p> <p><b>Part II: Applications and Analytics 173</b></p> <p>8 Fog Computing in Healthcare: Application Taxonomy, Challenges and Opportunities 175<br /><i>Subrata Datta and Priyanka Datta</i></p> <p>9 IoT-Driven Predictive Maintenance Approach in Industry 4.0: A Fiber Bragg Grating (FBG) Sensor Application 203<br /><i>Dipak Ranjan Nayak, Pramod Sharma, Ambarish G. Mohapatra, Narayan Nayak, Bright Keswani and Ashish Khanna</i></p> <p>10 Fog Computing-Enabled Cancer Cell Detection System Using Convolution Neural Network in Internet of Medical Things 229<br /><i>Soumen Santra, Dipankar Majumdar and Surajit Mandal</i></p> <p>11 Application of IoT in Smart Farming and Precision Farming: A Review 245<br /><i>Suparna Biswas and Soumik Podder</i></p> <p>12 Big IoT Data Analytics in Fog Computing 279<br /><i>Manash Kumar Mondal, Riman Mandal and Utpal Biswas</i></p> <p>13 IOT-Based Patient Monitoring System in Real Time 309<br /><i>Suparna Biswas, Tirtha Chakraborty, Souvik Mitra, Shubham Banerjee, Tuhin Sarkar and Sourav Paul</i></p> <p>14 Fog Computing and Its Emergence with Reference to Applications and Potentialities in Traditional and Digital Educational Systems: A Scientific Review 331<br /><i>P. K. Paul</i></p> <p><b>Part III: Security in Fog Computing 355</b></p> <p>15 Blockchain Security for Fog Computing 357<br /><i>Saiyam Varshney and Gur Mauj Saran Srivastava</i></p> <p>16 Blockchain Security for Fog Computing and Internet of Things 379<br /><i>Awais Khan Jumani, Waqas Ahmed Siddique, Muhammad Farhan Siddiqui and Kanwal</i></p> <p>17 Fine-Grained Access Through Attribute-Based Encryption for Fog Computing 405<br /><i>Malabika Das</i></p> <p>References 421</p> <p>Index 425</p>
<p><b>Chandan Banerjee, PhD, </b> is a professor in the Department of Information Technology, Netaji Subhash Engineering College, West Bengal, India. His research interests include cloud computing, computer networks, fog computing, data structure, and algorithms. With about 35 publications in referred international journals, he serves as a reviewer for many peer-reviewed international journals and international conferences. Banerjee is the recipient of several awards including the top-performing mentor award and the Silver Partner Faculty Recognition award. <p><b>Anupam Ghosh, PhD, </b> is a professor in the Department of Computer Science and Engineering, Netaji Subhash Engineering College, Kolkata, India. He has published more than 100 international papers in reputed international journals and conferences. His fields of interest are mainly AI, machine learning, deep learning, image processing, soft computing, bioinformatics, IoT, and data mining. <p><b>Rajdeep Chakraborty, PhD, </b> is an assistant professor in the Department of Computer Science and Engineering, Netaji Subhash Engineering College, Kolkata, India. His fields of interest are mainly in cryptography and computer security. He was awarded the Adarsh Vidya Saraswati Rashtriya Puraskar, National Award of Excellence 2019 conferred by Glacier Journal Research Foundation, <p><b>Ahmed A. Elngar, PhD, </b> is an associate professor in the Department of Computer Science and Engineering, University Institute of Engineering, Chandigarh University, Punjab, India. His field of interest focuses on cryptology and computer security. He has several publications in reputed journals along with a book on hardware cryptography. In 2019, Elngar was awarded the Adarsh Vidya Sarawati Rashtriya Puraskar, National Award of Excellence.
<p> <b>This book is a comprehensive guide on fog computing and how it facilitates computing, storage, and networking services</b> <p>Fog computing is a decentralized computing structure that connects data, devices, and the cloud. It is an extension of cloud computing and is an essential concept in IoT (Internet of Things), as it reduces the burden of processing in cloud computing. It brings intelligence and processing closer to where the data is created and transmitted to other sources. <p>Fog computing has many benefits, such as reduced latency in processing data, better response time that helps the user’s experience, and security and privacy compliance that assures protecting the vital data in the cloud. It also reduces the cost of bandwidth, because the processing is achieved in the cloud, which reduces network bandwidth usage and increases efficiency as user devices share data in the local processing infrastructure rather than the cloud service. <p>Fog computing has various applications across industries, such as agriculture and farming, the healthcare industry, smart cities, education, and entertainment. For example, in the agriculture industry, a very prominent example is the SWAMP project, which stands for Smart Water Management Platform. With fog computing’s help, SWAMP develops a precision-based smart irrigation system concept used in agriculture, minimizing water wastage. <p>This book is divided into three sections. The first section studies fog computing and machine learning, covering fog computing architecture, application perspective, computational offloading in mobile cloud computing, intelligent Cloud-IoT systems, machine learning fundamentals, and data visualization. The second section focuses on applications and analytics, spanning various applications of fog computing, such as in healthcare, Industry 4.0, cancer cell detection systems, smart farming, and precision farming. This section also covers analytics in fog computing using big data and patient monitoring systems, and the emergence of fog computing concerning applications and potentialities in traditional and digital educational systems. Security aspects in fog computing through blockchain and IoT, and fine-grained access through attribute-based encryption for fog computing are also covered. <p><b>Audience</b> <p>The book will be read by researchers and engineers in computer science, information technology, electronics, and communication specializing in machine learning, deep learning, the cyber world, IoT, and security systems.

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