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17 - Economics of Fresh Data Trading
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Edited by Nikolaos Pappas, Linköpings Universitet, Sweden, Mohamed A. Abd-Elmagid, Virginia Tech, Bo Zhou, Nanjing University of Aeronautics and Astronautics, China, Walid Saad, Virginia Tech, Harpreet S. Dhillon, Virginia Tech
Book: Age of Information
Published online: 02 February 2023
Print publication: 09 February 2023, pp 429-455
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Summary

In this chapter, we study the economic issues of fresh data trading markets, where the data freshness is captured by Age-of-Information (AoI). In our model, a destination user requests, and pays for, fresh data updates from a source provider. In this work, the destination incurs an age-related cost, modeled as a general increasing function of the AoI. To understand economic viability and profitability of fresh data markets, we consider a pricing mechanism to maximize the source’s profit, while the destination chooses a data update schedule to trade off its payments to the source and its age-related cost. The problem is exacerbated when the source has incomplete information regarding the destination’s age-related cost, which requires one to exploit (economic) mechanism design to induce the truthful information. This chapter attempts to build such a fresh data trading framework that centers around the following two key questions: (a) How should a source choose the pricing scheme to maximize its profit in a fresh data market under complete market information? (b) Under incomplete information, how should a source design an optimal mechanism to maximize its profit while ensuring the destination’s truthful report of its age-related cost information?

15 - Over-the-Air Computation for Distributed Learning over Wireless Networks
from Part II - Wireless Networks for Machine Learning
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 434-456
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7 - Constrained Unsupervised Learning for Wireless Network Optimization
from Part I - Machine Learning for Wireless Networks
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 182-211
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16 - Federated Knowledge Distillation
from Part II - Wireless Networks for Machine Learning
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 457-485
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11 - Capacity Estimation Using Machine Learning
from Part I - Machine Learning for Wireless Networks
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 317-350
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9 - Reinforcement Learning for Physical Layer Communications
from Part I - Machine Learning for Wireless Networks
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 231-284
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2 - Deep Neural Networks for Joint Source-Channel Coding
from Part I - Machine Learning for Wireless Networks
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 23-54
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12 - Collaborative Learning over Wireless Networks: An Introductory Overview
from Part II - Wireless Networks for Machine Learning
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 353-384
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6 - Model-Based Machine Learning for Communications
from Part I - Machine Learning for Wireless Networks
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 145-181
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4 - Channel Coding via Machine Learning
from Part I - Machine Learning for Wireless Networks
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 77-109
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5 - Channel Estimation, Feedback, and Signal Detection
from Part I - Machine Learning for Wireless Networks
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 110-144
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Dedication
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp v-vi
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8 - Radio Resource Allocation in Smart Radio Environments
from Part I - Machine Learning for Wireless Networks
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 212-230
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Part II - Wireless Networks for Machine Learning
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 351-352
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18 - Timely Wireless Edge Inference
from Part II - Wireless Networks for Machine Learning
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 512-538
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Index
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 539-544
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13 - Optimized Federated Learning in Wireless Networks with Constrained Resources
from Part II - Wireless Networks for Machine Learning
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 385-408
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Contents
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp vii-viii
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14 - Quantized Federated Learning
from Part II - Wireless Networks for Machine Learning
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 409-433
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10 - Data-Driven Wireless Networks: Scalability and Uncertainty
from Part I - Machine Learning for Wireless Networks
Edited by Yonina C. Eldar, Weizmann Institute of Science, Israel, Andrea Goldsmith, Princeton University, New Jersey, Deniz Gündüz, Imperial College of Science, Technology and Medicine, London, H. Vincent Poor, Princeton University, New Jersey
Book: Machine Learning and Wireless Communications
Published online: 16 June 2022
Print publication: 04 August 2022, pp 285-316
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126 results

17 - Economics of Fresh Data Trading

Summary

15 - Over-the-Air Computation for Distributed Learning over Wireless Networks

7 - Constrained Unsupervised Learning for Wireless Network Optimization

16 - Federated Knowledge Distillation

11 - Capacity Estimation Using Machine Learning

9 - Reinforcement Learning for Physical Layer Communications

2 - Deep Neural Networks for Joint Source-Channel Coding

12 - Collaborative Learning over Wireless Networks: An Introductory Overview

6 - Model-Based Machine Learning for Communications

4 - Channel Coding via Machine Learning

5 - Channel Estimation, Feedback, and Signal Detection

Dedication

8 - Radio Resource Allocation in Smart Radio Environments

Part II - Wireless Networks for Machine Learning

18 - Timely Wireless Edge Inference

Index

13 - Optimized Federated Learning in Wireless Networks with Constrained Resources

Contents

14 - Quantized Federated Learning

10 - Data-Driven Wireless Networks: Scalability and Uncertainty

Search Results

Refine search

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Actions for selected content:

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126 results

Summary