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E-grāmata: Auction Theory for Computer Networks

(University of Houston), (Nanyang Technological University, Singapore), (York University, Toronto),
  • Formāts: PDF+DRM
  • Izdošanas datums: 11-Jun-2020
  • Izdevniecība: Cambridge University Press
  • Valoda: eng
  • ISBN-13: 9781108575652
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Auction Theory for Computer NetworksPalielināt
  • Formāts: PDF+DRM
  • Izdošanas datums: 11-Jun-2020
  • Izdevniecība: Cambridge University Press
  • Valoda: eng
  • ISBN-13: 9781108575652
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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.

Papildus informācija

Acquire the tools to address emerging challenges in modern computer networks with this multidisciplinary review of the fundamentals.
1 Introduction page
1(10)
1.1 A Brief Overview of the History of Auctions
1(1)
1.2 Auction Theory in Computer Networks
2(1)
1.3 Organization and Timeliness of This Book
3(7)
1.3.1 Organization
3(4)
1.3.2 Timeliness of the Book
7(3)
1.4 Acknowledgments
10(1)
2 Overview of Modern Computer Networks
11(41)
2.1 Internet of Things
11(7)
2.1.1 Definitions
11(1)
2.1.2 IoT Architecture
12(2)
2.1.3 Resources and Services of IoT
14(1)
2.1.4 Wireless Sensor Network
15(1)
2.1.5 Mobile Crowdsensing Network
16(2)
2.2 Cloud Networking
18(7)
2.2.1 General Architecture
18(2)
2.2.2 Cloud Data Center Networking
20(1)
2.2.3 Mobile Cloud Networking
21(1)
2.2.4 Edge Computing
22(2)
2.2.5 Cloud-Based Video-on-Demand System
24(1)
2.3 5G Wireless Networks
25(9)
2.3.1 Massive Multiple-Input and Multiple-Output
26(1)
2.3.2 Heterogeneous Networks
27(2)
2.3.3 Millimeter Wave Communications
29(1)
2.3.4 Cognitive Radio
30(1)
2.3.5 Device-to-Device Communications
31(2)
2.3.6 Machine-to-Machine Communications
33(1)
2.4 Data Collection and Resource Management
34(9)
2.4.1 Data Aggregation
34(1)
2.4.2 Task Allocation
35(2)
2.4.3 User Association
37(1)
2.4.4 Interference Management
38(2)
2.4.5 Wireless Caching
40(2)
2.4.6 Mobile Data Offloading
42(1)
2.5 Wireless Network Security
43(8)
2.5.1 Users and Attackers in Wireless Networks
44(1)
2.5.2 Eavesdropping Attack
44(3)
2.5.3 Denial-of-Service Attack
47(2)
2.5.4 Information Security Issues
49(1)
2.5.5 Illegitimate Behaviors in Wireless Networks
50(1)
2.6 Summary
51(1)
3 Mechanism Design and Auction Theory in Computer Networks
52(20)
3.1 Mechanism Design
52(8)
3.1.1 Mechanism
52(1)
3.1.2 Mechanism Design
53(2)
3.1.3 Revelation Principle
55(2)
3.1.4 Incentive Compatibility
57(1)
3.1.5 Individual Rationality
58(1)
3.1.6 Economic Efficiency and Budget Balance
59(1)
3.2 Optimal Mechanisms
60(4)
3.2.1 Social Surplus and Profit
60(1)
3.2.2 Social Surplus Maximization Problem
61(2)
3.2.3 Profit Maximization Problem
63(1)
3.3 Auction Theory in Computer Networks
64(7)
3.3.1 Auction Basics
65(3)
3.3.2 Auction Theory for Computer Networks
68(1)
3.3.3 Basic Terminology in Auction Theory
69(2)
3.4 Summary
71(1)
4 Open-Cry Auction
72(28)
4.1 English Auction
72(6)
4.1.1 English Auction Process
72(2)
4.1.2 Equilibrium Strategies
74(4)
4.2 Development of English Auction for Computer Networks
78(5)
4.2.1 System Model and Problem Formulation
79(2)
4.2.2 Walrasian Equilibrium
81(1)
4.2.3 English Auction for Walrasian Equilibrium
82(1)
4.3 Dutch Auction
83(4)
4.3.1 Dutch Auction Process
83(2)
4.3.2 Revenue Equivalence Theorem
85(1)
4.3.3 Equilibrium in Dutch Auction
86(1)
4.4 Development of Dutch Auction for Computer Networks
87(10)
4.4.1 Prevention of Black Hole Attacks in Mobile Ad Hoc Networks
87(4)
4.4.2 Relay Selection in the Internet of Things
91(2)
4.4.3 Channel Allocation in 5G Heterogeneous Networks
93(4)
4.5 English-Dutch Auction
97(2)
4.6 Summary
99(1)
5 First-Price Sealed-Bid Auction
100(19)
5.1 Definition
100(1)
5.2 Equilibrium
101(3)
5.2.1 Strategic Analysis
101(1)
5.2.2 Bayesian-Nash Equilibrium
102(2)
5.3 First-Price Sealed-Bid Reverse Auction
104(1)
5.4 Development of First-Price Sealed-Bid Auction for Computer Networks
105(12)
5.4.1 Incentive Mechanism for Data Aggregation
105(4)
5.4.2 Market-Based Adaptive Task Allocation
109(3)
5.4.3 Market-Based Relay Selection
112(2)
5.4.4 Denial-of-Service Attack Prevention
114(3)
5.5 Summary
117(2)
6 Second-Price Sealed-Bid Auction
119(39)
6.1 Second-Price Sealed-Bid Auction
119(16)
6.1.1 Definition
119(2)
6.1.2 Dominant Strategy and Nash Equilibrium
121(2)
6.1.3 Second-Price Sealed-Bid Reverse Auction
123(1)
6.1.4 Development of Second-Price Sealed-Bid Auction for Computer Networks
124(11)
6.2 Vickrey-Clarke-Groves Auction
135(22)
6.2.1 Definition
135(1)
6.2.2 Description
136(3)
6.2.3 Dominant Strategy
139(1)
6.2.4 Examples
140(1)
6.2.5 Virtues
141(1)
6.2.6 Development of VCG Auction for Computer Networks
142(15)
6.3 Summary
157(1)
7 Combinatorial Auction
158(31)
7.1 Introduction
158(1)
7.2 Substitutable and Complementary Items
159(2)
7.3 Single-Round Combinatorial Auction
161(4)
7.3.1 Bidding Language
161(2)
7.3.2 Winner Determination Problem
163(2)
7.4 Iterative Combinatorial Auctions
165(5)
7.4.1 Ascending Proxy Auction
165(2)
7.4.2 Clock-Proxy Auction
167(3)
7.5 Development of the Combinatorial Auction for Computer Networks
170(18)
7.5.1 Spectrum Allocation in Cognitive Radio
170(4)
7.5.2 Virtualization of 5G Massive MIMO
174(6)
7.5.3 Mobile Data Offloading in 5G HetNets
180(4)
7.5.4 Resource Allocation in D2D Communication Underlying Cellular Networks
184(4)
7.6 Summary
188(1)
8 Double-Sided Auction
189(26)
8.1 Introduction
189(1)
8.2 Single-Round Double Auction
189(5)
8.2.1 Uniform Pricing Policy
192(1)
8.2.2 Discriminatory Pricing Policy
193(1)
8.3 Continuous Double Auction
194(2)
8.4 Development of Double Auction for Computer Networks
196(18)
8.4.1 Sensing Task Allocation in Participatory Sensing
197(4)
8.4.2 Location Privacy in Participatory Sensing
201(3)
8.4.3 Spectrum Allocation in Heterogeneous Networks
204(5)
8.4.4 Cloud Resource Allocation in Edge Computing
209(5)
8.5 Summary
214(1)
9 Other Auctions
215(21)
9.1 Ascending Clock Auction
216(5)
9.1.1 Auction Process
216(1)
9.1.2 Application of Ascending Clock Auction for Physical Layer Security
217(4)
9.2 Share Auction
221(3)
9.3 Online Auction
224(7)
9.3.1 Basic Terminologies
224(2)
9.3.2 Development of Online Auction for Cloud Resource Pooling
226(5)
9.4 Waiting-Line Auction
231(4)
9.5 Summary
235(1)
10 Optimal Auction Using Machine Learning
236(24)
10.1 Optimal Auction
236(2)
10.2 Machine Learning
238(1)
10.3 Machine Learning for Optimal Auction
239(10)
10.3.1 Design
239(5)
10.3.2 Example
244(5)
10.4 Machine Learning for Myerson Auction
249(10)
10.4.1 Design
250(4)
10.4.2 Example
254(5)
10.5 Summary
259(1)
References 260(18)
Index 278
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.
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