This document is downloaded from DR‑NTU (https://dr.ntu.edu.sg) Nanyang Technological University, Singapore. Mechanism design for internet of things services market Jiao, Yutao 2020 Jiao, Y (2020). Mechanism Design for internet of things services market. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/137397 https://doi.org/10.32657/10356/137397 This work is licensed under a Creative Commons Attribution‑NonCommercial 4.0 International License (CC BY‑NC 4.0). Downloaded on 05 Oct 2021 17:37:30 SGT Mechanism Design for Internet of Things Services Market Jiao Yutao School of Computer Science and Engineering A thesis submitted to the Nanyang Technological University in partial fulfillment of the requirements for the degree of Doctor of Philosophy 2020 Statement of Originality I hereby certify that the work embodied in this thesis is the result of original research, is free of plagiarised materials, and has not been submitted for a higher degree to any other University or Institution. 18/11/2019 ............................................ Date Jiao Yutao Supervisor Declaration Statement I have reviewed the content and presentation style of this thesis and declare it is free of plagiarism and of sufficient grammatical clarity to be examined. To the best of my knowledge, the research and writing are those of the candidate except as acknowledged in the Author At- tribution Statement. I confirm that the investigations were conducted in accord with the ethics policies and integrity standards of Nanyang Technological University and that the research data are presented hon- estly and without prejudice. 18/11/2019 ............................................ Date Dr. Dusit Niyato Authorship Attribution Statement This thesis contains material from 6 paper(s) published in the follow- ing peer-reviewed journal(s) / from papers accepted at conferences in which I am listed as an author. Chapter 3 is published as Y. Jiao, P. Wang, S. Feng, and D. Niyato, “Profit Max- imization Mechanism and Data Management for Data Analytics Services," IEEE Internet of Things Journal, vol. 5, no. 3, pp. 2001{2014, Jun. 2018, and is partially published as Y. Jiao P. Wang, D. Niyato, M.A. Alsheikh, and S. Feng, “Profit Max- imization Auction and Data Management in Big Data Markets," in Proceedings of IEEE WCNC, San Francisco, CA, 19-22 Mar. 2017. The contributions of the co-authors are as follows: • Dr. Niyato and Dr. Wang provided the initial project direction and edited the manuscript drafts. • Mr. Feng assisted in the proof of Proposition 3 of the journal paper. • Dr. Alsheikh revised the manuscript of the conference paper. • I conducted the experiments and simulations, and prepared the manuscript drafts. Chapter 4 is published as Y. Jiao, P. Wang, D. Niyato, and K. Suankaewma- nee, \Auction mechanisms in cloud/fog computing resource allocation for public blockchain networks," IEEE Transactions on Parallel and Distributed Systems, vol. 30, no. 9, pp. 1975-1989, 1 Sep. 2019, and is partially published as Y. Jiao, P. Wang, D. Niyato, and Z. Xiong, \Social welfare maximization auction in edge computing resource allocation for mobile blockchain," in Proceedings of IEEE ICC, Kansas City, MO, USA, 20-24 May 2018. The contributions of the co-authors are as follows: • Dr. Niyato and Dr. Wang provided the initial project direction and edited the manuscript drafts. • Mr. Xiong assisted in building the system model in Section III of the conference paper. • Mr. Suankaewmanee assisted in the experiments in Section 6.1 of the journal paper. • I completed the theoretical analysis, performed the simulations, and wrote the manuscript drafts. viii Chapter 5 is published as Y. Jiao, P. Wang, D. Niyato, B. Lin, and D. I. Kim, \Mechanism design for wireless powered spatial crowdsourcing networks," IEEE Transactions on Vehicular Technology (accepted with minor revision), and is par- tially published as Y. Jiao, P. Wang, D. Niyato, J. Zhao, B. Lin, and D. I. Kim, \ask allocation and mobile base station deployment in wireless powered spatial crowd- sourcing" in Proceedings of IEEE SmartGridComm, Beijing, China, 21-24 Oct. 2019. The contributions of the co-authors are as follows: • Dr. Niyato and Dr. Wang provided the initial project direction and edited the manuscript drafts. • Dr. Zhao assisted in the proof of Proposition 2 of the conference paper. • Dr. Lin, Dr. Kim and Dr. Zhao revised the manuscripts. • I completed the theoretical analysis, performed the experiments and simula- tions, and wrote the manuscript drafts. 18/11/2019 ............................................ Date Jiao Yutao Acknowledgements First and foremost, I would like to express my most enormous gratitude to my super- visors, Professor Ping Wang and Professor Dusit Niyato, for providing me with the valuable opportunity to pursue my doctorate degree at Nanyang Technological Uni- versity. They not only always spare time to discuss my encountered research prob- lems, but also point out the promising directions sharply. Without their continuous guidance and instructions, I would not start my research on the mechanism design and explore the frontier topics in Internet of Things. This dissertation definitely would not be possible without their invaluable support. Their rigorous scholarship, insight, infectious enthusiasm, and unlimited patience affected me deeply and will inspire me to be an outstanding researcher in the future. I would like to take this opportunity to express my sincere thankfulness to all my colleagues in Computer Networks and Communications Lab (CNCL) and my friends at Nanyang Technological University and Singapore. They have always supported me with their warmhearted assistance, great advice and encouragement in research and daily life. Last but not least, my deepest love is devoted to all of my family members: my grandparents, my parents, my aunts, my uncles and my fianc´ee. Their everlasting support and endless love give me the power to overcome the difficulties and strive for growth during my PhD study. I believe my grandfather would be very proud and happy in heaven. I miss him. Abstract Over the past decade, the Internet of Things (IoT) adoption and applications have significantly increased. Massive amounts of data are continuously generated and transmitted among connected people and devices over wired and wireless networks. The IoT networks involve different kinds of resources, such as data, communication, and computing, which can become valuable commodities that are exchanged and traded between the service providers and the customers in online marketplaces. For efficient and sustainable resource usage, there is an immediate need for establishing market models for various IoT services and investigating the optimal resource allo- cation. In this thesis, we focus on designing novel and practical trading mechanisms for the IoT services market, where data, computing, and communication are three main types of resources. Accordingly, we investigate three typical IoT services, in- cluding the data analytics services, the cloud/fog computing services for blockchain, and the wireless powered data crowdsourcing services. The thesis presents three major contributions. First, we study the optimal pricing mechanisms and data management for data analytics services and further discuss the perishable services in the time-varying environment. We establish a data market model and define the data utility based on the impact of data size on the perfor- mance of data analytics. For perishable services, we study the perishability of data and provide a quality decay function. We apply the Bayesian profit maximization mechanism to selling data analytics services, which is strategyproof and compu- tationally efficient. Our proposed data market model and pricing mechanism can effectively solve the profit maximization problem and provide useful strategies for the data analytics service provider. Second, we discuss the trading between the cloud/fog computing service provider and miners in blockchain networks and propose an auction-based market model for efficient computing resource allocation. We consider the proof-of-work based blockchain that relies on the computing resource. The allocative externalities are particularly addressed due to the competition among miners. We first study the xi xii constant-demand scheme where each miner bids for a fixed quantity of resources, and propose an auction mechanism that achieves optimal social welfare. Also, we consider a multi-demand scheme where the miners submit their preferable demands and bids. Since the social welfare maximization problem is NP-hard, we design an approximate algorithm which also guarantees the truthfulness, individual rationality, and computational efficiency. Third, we propose a wireless powered spatial crowdsourcing framework that consists of two mutually dependent phases: task allocation phase and data crowdsourcing phase. In the task allocation phase, we propose a Stackelberg game based mecha- nism for the spatial crowdsourcing platform to efficiently allocate spatial tasks and wireless charging power to each worker. In the data crowdsourcing phase, we present three strategyproof deployment mechanisms for the spatial crowdsourcing platform to place a mobile base station. We first apply the classical median mechanism and evaluate its worst-case performance. Given the workers' geographical distribution, we propose the second strategyproof deployment mechanism to improve the spatial crowdsourcing platform's expected utility. For a