4.8 Article

A Novel Debt-Credit Mechanism for Blockchain-Based Data-Trading in Internet of Vehicles

期刊

IEEE INTERNET OF THINGS JOURNAL
卷 6, 期 5, 页码 9098-9111

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2019.2927682

关键词

Blockchain; data-trading; debt-credit; Internet of Vehicles (IoV); Stackelberg game

资金

  1. National Key Research and Development Plan [2018YFB1003803]
  2. National Natural Science Foundation of China [61802450, 61722214]
  3. Natural Science Foundation of Guangdong [2018A030313005]
  4. Program for Guangdong Introducing Innovative and Entrepreneurial Teams [2017ZT07X355]

向作者/读者索取更多资源

With the advancement and emergence of diverse network services in Internet of Vehicles (IoV), large volume of data are collected and stored, making data important properties. Data will be one of the most important commodities in the future blockchain-based IoV systems. However, efficiency challenges have been commonly found in blockchain-based data markets, which is mainly caused by transaction confirmation delays and the cold-start problems for new users. To address the efficiency challenges, we propose a secure, decentralized IoV data-trading system by exploiting the blockchain technology, and design an efficient debt-credit mechamism to support efficient data-trading in IoV. In the debt-credit mechanism, a vehicle with loan demand could loan from multivehicles by promising to pay interest and reward. In particular, we encourage loaning among vehicles by a motivation-based investing and pricing mechanism. We formulate a two-stage Stackelberg game to maximize the profits of borrower vehicle and lender vehicles jointly. In the first stage, the borrower vehicle set the interest rate and reward for the loan as its pricing strategies. In the second stage, the lender vehicles decide on their investing strategies. We apply backward induction to analyze the subgame perfect equilibrium at each stage for both independent and uniform pricing schemes. We also validate the existence and uniqueness of Stackelberg equilibrium. The numerical results illustrate the efficiency of the proposed pricing schemes.

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