This book initially delves into its fundamentals to initiate the exploration of online incentive mechanisms in wireless communications. Three case studies are provided to elaborate details on designing online mechanism design in practical system. For crowdsensing with random task arrivals, this book introduces a linear online incentive mechanism model with insurance of the quality of information for each incoming task. In the context of edge computing systems, the authors model a nonlinear online incentive mechanism with the consideration of mobile users' energy budget constraints. It also explores online incentive mechanism for collaborative task offloading in mobile edge computing to achieve on-arrival instant responses. This book not only disseminates current knowledge but also sheds light on future research directions.

The design of incentive mechanisms in wireless communication systems is of paramount importance as it encourages dormant terminals within networks to contribute their valuable resources. The consideration of randomness of network processes enhances the mechanism design under online settings and decision making on the fly. This book endeavours to bridge existing knowledge gaps by comprehensively presenting and developing fundamental insights into online incentive mechanisms and their design methods in the realm of wireless communications. It's one of the first books to provide a comprehensive understanding of the fundamental principles of online incentive mechanisms and their intricately designed methods in the dynamic world of wireless communications. Future research directions include an investigation in the evolving domain of online incentive mechanism designs within wireless communications.

This book strikes a balance between theoretical knowledge and practical application, making it a valuable resource for both researchers and practitioners in the field of wireless communications and network economics. Advanced-level students majoring in computer science and/or electrical engineering will want to purchase this book as a study guide.

Autorentext

Dr. Aswani Kumar Cherukuri is a Professor (Higher Academic Grade) of School of Computer Science Engineering & Information Systems, Vellore Institute of Technology, Vellore, India. His research interests are machine learning, information security and quantum computing. In particular, his work is focused on encrypted network traffic analysis, machine learning techniques. Also, he has interests in post quantum cryptography. He published more than 190 research papers and has 4100+ citations and h-index of 31 as per Google scholar. He executed as principal investigator, different research projects of worth 10 million USD from various funding agencies of India. He has guided 8 PhD research scholars and few foreign interns. He has received awards including Young Scientist Fellowship, Inspiring Teacher Award, Educator excellence award, etc. He is editorial board member of several international journals. He is a member of IEEE, Senior Member of ACM, Vice Chair of IEEE Educational Taskforce on Datamining. Dr. Sumaiya Thaseen Ikram is an Associate Professor (Senior) in the School of Computer Science and Information Systems in Vellore Institute of Technology, Vellore with 18 years of teaching and research experience. She has expertise in Cryptography, Network Security, Software Security, Intrusion Detection Systems, Artificial Intelligence, Image Processing, Ethical hacking, Vulnerability Assessment and Penetration Testing. She has 1400+ citations and h-index of 15 in google scholar and most of her research works are published in high impact factor journals. She is a reviewer for many journals of Wiley, Elsevier, and Springer publishers. She is a certified ethical hacker, certified penetration testing engineer and certified computer hacking forensic investigator. She has successfully completed a research project as a Co-PI funded by MHRD worth Rs.63 lakhs between 2019-2023 in collaboration with Deakin University, Australia. She also completed a consultancy project worth Rs.6 lakhs in the domain of full stack development in the year 2022. She has delivered many expert talks in the domain of Intrusion detection Systems in Taylors University, Malaysia and Deakin University, Australia. Dr. Gang Li is the university academic board member and full professor at Deakin University, and he is the AI director in the Strategic Research Center of Cyber Resilience and Trust (CREST). His research includes data mining, privacy preservation, group behavior analysis and business intelligence. He holds one international patent, and he has co-authored nine papers that won best paper prizes, including Springer's Journal of IT & Tourism best paper award in 2023, KSEM 2018 best paper award, IFITT Journal Paper of the Year 2018/2015, ACM/IEEE ASONAM2012 best paper award, the 2008 Nightingale Prize by Springer, etc. Dr. Xiao Liu received his bachelor's and master's degrees in information management and information system from the School of Management, Hefei University of Technology, Hefei, China, in 2004 and 2007, respectively, and his Ph.D. degree in computer science and software engineering from the Faculty of Information and Communication Technologies, Swinburne University of Technology, Melbourne, Australia, in 2011. He was an Associate Professor at the Software Engineering Institute, East China Normal University, Shanghai, China, during 2013 to 2015. He is currently an Associate Professor and Director for the Software Engineering Innovation Lab with the School of Information Technology, Deakin University, Australia. His research interests include workflow systems, cloud and edge computing, big data analytics, social network, and human-centric software engineering. He is a Senior Member of ACM and IEEE.

Inhalt

Chapter 1 Introduction of Online Incentive Mechanism in Wireless Communications.- Chapter 2 Linear Online Incentive Mechanism Design Case Study of Crowdsensing with Random Task Arrivals.- Chapter 3 Nonlinear Online Incentive Mechanism Design: Case Study of Edge Computing with Energy Budget.- Chapter 4 Online Incentive Mechanism Design for Real-time Decision Making: Case Study of Collaborative Task Offloading in Mobile Edge Computing.- Chapter 5 Conclusions and Future Research Directions.