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Algorithmic mechanism design for Internet of things services marketdesign incentive mechanisms to facilitate the efficiency and sustainability of IoT ecosystem /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Algorithmic mechanism design for Internet of things services marketby Yutao Jiao, Ping Wang, Dusit Niyato.
Reminder of title:	design incentive mechanisms to facilitate the efficiency and sustainability of IoT ecosystem /
Author:	Jiao, Yutao.
other author:	Wang, Ping.
Published:	Singapore :Springer Singapore :2022.
Description:	xiii, 110 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Internet of things.
Online resource:	https://doi.org/10.1007/978-981-16-7353-5
ISBN:	9789811673535$q(electronic bk.)

Algorithmic mechanism design for Internet of things services marketdesign incentive mechanisms to facilitate the efficiency and sustainability of IoT ecosystem /
Jiao, Yutao.

Algorithmic mechanism design for Internet of things services marketdesign incentive mechanisms to facilitate the efficiency and sustainability of IoT ecosystem /[electronic resource] :by Yutao Jiao, Ping Wang, Dusit Niyato. - Singapore :Springer Singapore :2022. - xiii, 110 p. :ill., digital ;24 cm.

Chapter1. Introduction -- Chapter2. Literature Review -- Chapter 3. Profit Maximization Mechanism and Data Management for Data Analytics Services -- Chapter 4. Auction Mechanisms in Cloud/Fog Computing Resource Allocation for Public Blockchain Networks -- Chapter 5. Mechanism Design for Wireless Powered Spatial Crowdsourcing Networks -- Chapter 6. Summary and Future Work.

This book establishes game-theoretical frameworks based on the mechanism design theory and proposes strategy-proof algorithms, to optimally allocate and price the related IoT services, so that the social welfare of IoT ecosystem or the service provider's revenue can be maximized and the IoT service provision can be sustainable. This book is written by experts based on the recent research results on the interaction between the service providers and users in the IoT system. Since the IoT networks are essentially supported by data, communication, and computing resources, the book focuses on three representative IoT services, including the data analytics services, the cloud/fog computing services for blockchain networks, and the wireless powered data crowdsourcing services. Researchers, scientists, and engineers in the field of resource allocation and service management for future IoT ecosystem can benefit from the book. As such, this book provides valuable insights and practical methods, especially the novel deep learning-based mechanism that can be considered in the emerging IoT technology.

ISBN: 9789811673535$q(electronic bk.)

Standard No.: 10.1007/978-981-16-7353-5doiSubjects--Topical Terms:

670954
Internet of things.

LC Class. No.: TK5105.8857 / .J53 2022

Dewey Class. No.: 004.678

Algorithmic mechanism design for Internet of things services marketdesign incentive mechanisms to facilitate the efficiency and sustainability of IoT ecosystem /
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505 0 $a Chapter1. Introduction -- Chapter2. Literature Review -- Chapter 3. Profit Maximization Mechanism and Data Management for Data Analytics Services -- Chapter 4. Auction Mechanisms in Cloud/Fog Computing Resource Allocation for Public Blockchain Networks -- Chapter 5. Mechanism Design for Wireless Powered Spatial Crowdsourcing Networks -- Chapter 6. Summary and Future Work.
520 $a This book establishes game-theoretical frameworks based on the mechanism design theory and proposes strategy-proof algorithms, to optimally allocate and price the related IoT services, so that the social welfare of IoT ecosystem or the service provider's revenue can be maximized and the IoT service provision can be sustainable. This book is written by experts based on the recent research results on the interaction between the service providers and users in the IoT system. Since the IoT networks are essentially supported by data, communication, and computing resources, the book focuses on three representative IoT services, including the data analytics services, the cloud/fog computing services for blockchain networks, and the wireless powered data crowdsourcing services. Researchers, scientists, and engineers in the field of resource allocation and service management for future IoT ecosystem can benefit from the book. As such, this book provides valuable insights and practical methods, especially the novel deep learning-based mechanism that can be considered in the emerging IoT technology.
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