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Title Optimal social welfare: A many-to-many data transaction mechanism based on double auctions
ID_Doc 41041
Authors Duan, JY; Tian, L; Mao, JQ; Li, JX
Title Optimal social welfare: A many-to-many data transaction mechanism based on double auctions
Year 2023
Published Digital Communications And Networks, 9, 5
DOI 10.1016/j.dcan.2022.04.020
Abstract With the development of Big Data and the Internet of Things (IoT), the data value is more significant in both academia and industry. Trading can achieve maximal data value and prepare data for smart city services. Due to data's unique characteristics, such as dispersion, heterogeneity and distributed storage, an unbiased platform is necessary for the data trading market with rational trading entities. Meanwhile, there are multiple buyers and sellers in a practical data trading market, and this makes it challenging to maximize social welfare. To solve these problems, this paper proposes a Social-Welfare-Oriented Many-to-Many Trading Mechanism (SOMTM), which integrates three entities, a trading process and an algorithm named Many-to-Many Trading Algorithm (MMTA). Based on the market scale, market dominated-side and market fixed-side, simulations verify the convergency, economic properties and efficiency of SOMTM.
Author Keywords Data trading; Double auction; Social welfare; Game theory; Smart city
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:001107313900001
WoS Category Telecommunications
Research Area Telecommunications
PDF https://doi.org/10.1016/j.dcan.2022.04.020
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