Auction Theory for Computer Networks

by Dusit Niyato, Nguyen Cong Luong, Ping Wang, Zhu Han

Overview

Do you have the tools to address recent challenges and problems in modern computer networks? Discover a unified view of auction theoretic applications and develop auction models, solution concepts, and algorithms with this multidisciplinary review. Devise distributed, dynamic, and adaptive algorithms for ensuring robust network operation over time-varying and heterogeneous environments, and for optimizing decisions about services, resource allocation, and usage of all network entities. Topics including cloud networking models, MIMO, mmWave communications, 5G, data aggregation, task allocation, user association, interference management, wireless caching, mobile data offloading, and security. Introducing fundamental concepts from an engineering perspective and describing a wide range of state-of-the-art techniques, this is an excellent resource for graduate and senior undergraduate students, network and software engineers, economists, and researchers.

Product Details

ISBN-13:	9781108480765
Publisher:	Cambridge University Press
Publication date:	06/11/2020
Pages:	288
Product dimensions:	7.09(w) x 9.96(h) x 0.79(d)

About the Author

Dusit Niyato is a professor in the School of Computer Science and Engineering at Nanyang Technological University, Singapore and a Fellow of the IEEE.

Nguyen Cong Luong is a senior lecturer at Phenikaa University, Vietnam. He is also a researcher at the Phenikaa Research and Technology Institute (PRATI).

Ping Wang is an Associate Professor at the Department of Electrical Engineering and Computer Science, York University.

Zhu Han is a John and Rebecca Moores Professor in the Department of Electrical and Computer Engineering as well as the Computer Science Department at the University of Houston, and a Fellows of the IEEE and AAAS.

Table of Contents

1. Introduction; 2. Overview of modern computer networks; 3. Mechanism design and auction theory in computer networks; 4. Open-cry auction; 5. First-price sealed-bid auction; 6. Second-price sealed-bid auction; 7. Combinatorial auction; 8. Double-sided auction; 9. Other auctions; 10. Optimal auction using machine learning.