Distributed and Parallel Computing

Master the growing field of distributed and parallel computing with this essential guide, offering expert insights into the fundamentals and real-world applications for intelligent and collaborative systems. Distributed computing, or running programs across multiple computers over a network, is becoming a popular solution for addressing the demands for increased performance across industries, including scientific computing, oil exploration, biotechnology, and medicine. Distributed computing enables seamless communication and collaboration by allowing users from different locations to access and interact with their digital twin simultaneously. Distributed computing enhances the capabilities of digital twins by providing scalability, parallel processing, real-time data integration, collaboration support, resource optimization, fault tolerance, and security features. Distributed and Parallel Computing explores the fundamentals and innovations in intelligent and distributed computing systems and applications, including adaptivity and learning, agents and multi-agent systems, argumentation, case-based reasoning, and collaborative systems. Through expert insights, readers will discover promising real-world applications for this emerging technology.

Table of Contents:
Preface xvii 1 Introduction to Distributed Systems 1 K. Karthikeyan, S. Hemalatha and S. Vignesh 1.1 Introduction 2 2 Topology in Network Technologies 39 Mohit Malik, Varun Dogra, Ramandeep Sandhu, Ratesh Kumar and Deepika Ghai 2.1 Introduction 40 2.2 Related Work 41 2.3 Network Topology Design 44 2.4 Advantages of Network Topologies 47 2.5 Case Studies of Network Topologies 48 2.6 Distributed and Parallel Computing in Network Topology 49 2.7 Conclusion 53 3 Distributed Processing Technology and Advancements 57 Saranya. N., Shermy. R.P., Sindhu. V., Karthika Renuka. D. and Renugadevi. G. 3.1 Introduction 58 3.2 Distributed Processing in Modern Computing 60 3.3 Evolution of Distributed Processing 61 3.4 Key Concepts and Technologies Driving the Evolution of Distributed Processing 63 3.5 Recent Advancements in Distributed Processing 64 3.6 Changing Landscape of Computing 65 3.7 Security and Privacy Considerations 68 3.8 Opportunities and Challenges in Distributed Computing 71 3.9 Conclusion 73 4 Distributed System Architecture and Computing Models 77 Sandhya Avasthi and Suman Lata Tripathi 4.1 Introduction 77 4.2 Distributed System Architecture 78 4.3 Middleware in Distributed Systems 85 4.4 Distributed Cloud Architecture 88 4.5 Distributed Machine Learning 90 4.6 Conclusion 91 5 Parallel Computing Models and Architecture 95 Aastha Sharma, Swati Sharma and Divya Mishra 5.1 Introduction 96 5.2 Evolution of Parallel Computing Models 98 5.3 Parallel Computing Models 100 6 Network Issues and High-Level Communication Tools in Distributed Computing 115 Sandhya Avasthi and Sachin Kumar Vishwakarma 6.1 Introduction 116 6.2 Latency in Distributed and Parallel Computing 118 6.3 Straggler Effect 122 6.4 Packet Loss in the Distributed Network 125 6.5 Network Congestion 128 6.6 Communication Load 129 6.7 Conclusion 132 7 Infinite Horizons: Empowering Business Education Through Metaverse 135 Shikha Mishra and Sujit S. Nair 7.1 Introduction 136 7.2 Challenges and Concerns 137 7.3 Rules of Law–Based Governance 139 7.4 Possible Implementations in Educational Framework of Metaverse Technology 140 7.5 Understanding Metaverse 141 7.6 Explore the Transformational Potential of Metaverse for Business Education 142 7.7 Innovation and Design Ideas Forum 145 7.8 Continuing Education and Career Development 147 7.9 Takeaways 147 7.10 Ethical and Legal Issues 148 7.11 Future Prospects and Innovations 149 7.12 Conclusion 149 8 Paradigm Shifts and Future Directions in Distributed Data Management for Decentralized Networks 153 Bishnu Kant Shukla, Bhupender Parashar, Vikas Kumar Singla and Shivam Verma 8.1 Introduction 154 8.2 Paradigm Shifts in Distributed Data Management 155 8.3 Emergent Architectures and Frameworks 156 8.4 Integration of IoT 160 8.5 Edge Computing and Big Data Analytics 163 8.6 Data Aggregation and Summarization Techniques 164 8.7 Advanced Applications and Case Studies 168 8.8 Future Directions in Distributed Data Management 172 8.9 Conclusion 174 9 Autonomy and Adaptive Architectures in Distributed Systems 183 Bishnu Kant Shukla, Bhupender Parashar, Vikas Kumar Singla and Shivam Verma 9.1 Introduction 184 9.2 Conceptual Framework 185 9.3 Architectural Models 187 9.4 Adaptive Strategies in Distributed Systems 188 9.5 Case Studies 191 9.6 Application of MASs 195 9.7 Autonomous Navigation Systems 199 9.8 Collision Avoidance Algorithms 202 9.9 Network Properties in Distributed Systems 206 9.10 Challenges and Future Directions 207 9.11 Conclusion 210 10 Distributed Consensus Frequency Control in Networked Microgrid 219 Jeevitha Kandasamy, J. Jenitha, M.R. Mohanraj, Jenifer Amla. L., G. Mahalakshmi and Ponrekha M. 10.1 Introduction 220 10.2 System Model 224 10.3 Distributed Control Technique 225 10.4 Results and Discussion 228 10.5 Conclusion 231 11 Navigating Trust in Distributed Systems 235 Pooja Dehankar and Susanta Das 11.1 Introduction 236 11.2 Transparency Basics 240 11.3 Heterogeneous and Homogeneous DSs 240 11.4 Trust Management 242 11.5 Components' Roles 243 11.6 User Authentication and Access Control 244 11.7 Trust Framework Pillars 244 11.8 Trust Metrics 244 11.9 Trust Models and Mechanisms 245 11.10 Trust in Sensor Networks 247 11.11 Apps of TMSs 248 11.12 DSs Advantages and Challenges 249 11.13 Artificial Intelligence for Trust Management 250 11.14 Conclusion 251 12 Trust in Distributed Systems, Distributed Ledger, Blockchain, and Related Technologies 257 Shikha Verma, Priya Mishra and Sandhya Avasthi 12.1 Introduction 257 12.2 Trust in Distributed Ledger 258 12.3 Trust Management in Edge-Based IoT Systems 260 12.4 A Taxonomy of Trust Computation Frameworks for Edge-Based IoT Systems 261 12.5 Trust in Distributed Databases 262 12.6 Trust in Blockchain 263 12.7 Serverless Computing 268 12.8 Trust in Cloud Computing 273 12.9 Conclusion 275 13 Strategy to Improve Psychological Elements and Customer Service in Intelligent Health Systems 281 Mani Dublish, Anita Pati Mishra and Shikha Mittal 13.1 Introduction 282 13.2 Design with User in Mind 284 13.3 Designing Networked Medication Equipment with a Human Center 285 13.4 Testing Usability with End Users 285 13.5 Framework Required in Healthcare Fiction for Human-Based Design 287 13.6 A Necessary Step to Enable Quick Learning Processes 287 13.7 Requirement for a Planned Approach Setup 288 13.8 Limitations 291 13.9 Conclusion 292 14 New Age Techs Backbone: Role of Distributed Systems in Paving Path for a Durable Future 299 Kadambri Agarwal and Saijal Dahiya 14.1 Introduction 300 14.2 Distributed Systems in Smart Grids 303 14.3 Distributed Systems in IoT 305 14.4 Distributed Systems in Blockchain 308 14.5 Distributed Systems in Machine Learning 310 14.6 Distributed Systems in AR 313 14.7 Distributed Systems in Distributed Databases 315 14.8 Distributed Systems in Metaverse 317 14.9 Conclusion 320 15 Power Optimization in 4Bit Comparator Architecture Through Precomputation Technique 323 Adarsh Sharma, Suman Lata Tripathi, Deepika Ghai and Khilda Afifah 15.1 Introduction 324 15.2 Comparator 327 15.3 Precomputation Technique 328 15.4 Reported Precomputation Circuit 329 15.5 Comparator Design with Cadence Virtuoso 330 15.6 Future Scopes 331 15.7 Conclusion 335 Acknowledgement 335 References 335 Index 339

About the Author :
Sandhya Avasthi, PhD is an assistant professor in the Computer Science and Engineering Department at ABES Engineering College at Dr. Abdul Kalam Technical University with over 18 years of teaching experience. She has published numerous research articles in refereed international journals, conference proceedings, and book chapters. Her research interests include natural language processing, information extraction, information retrieval, data science, and business intelligence.   Suman Lata Tripathi, PhD is a professor at Lovely Professional University with more than 22 years of experience in academics and research. She has published more than 19 books, 125 research papers in refereed science journals, conference proceedings, 13 Indian patents, and four copyrights. Her area of expertise includes microelectronics device modeling and characterization, low-power VLSI circuit design, VLSI design testing, and advanced FET design for IoT.