Profit Maximization in Edge-Enabled Multimedia Data Market: A Game-Based Pricing Approach

被引:0
|
作者
Shen, Bo [1 ]
Ma, Qian [1 ]
Yang, Gang [1 ]
Wang, Ru [2 ]
机构
[1] Northwestern Polytech Univ, Sch Comp Sci & Engn, Xian, Peoples R China
[2] Northwest A&F Univ, Coll Informat Engn, Yangling, Peoples R China
基金
中国国家自然科学基金;
关键词
Data market; knowledge management; Stackelberg game; profit maximization; edge computing;
D O I
10.1007/978-981-97-5489-2_16
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A huge amount of multimedia data is generated everyday. The value of data determines that it can be viewed as a kind of commodity for sale. Processing raw data to extract knowledge can increase the value of data. However, processing cost determine the profits of data providers. Processing delay affect the purchasing willingness of data buyers. In this paper, we propose an economics framework for data trading. A data market with the aid of edge computing is established to describe the interaction between data providers and data buyers. The problem of pricing and purchasing data is discussed to maximize the profits of the whole participants in multimedia data market. A Stackelberg game is then proposed to derive the best pricing and purchasing strategies. The knapsack strategy is also used to select the candidate data providers. Extensive experimental results show the effectiveness of the proposed framework.
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页码:176 / 187
页数:12
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