Auction-based High Timeliness Data Pricing under Mobile and Wireless Networks

Data is the cornerstone of intelligent algorithms such as deep learning, and the explosive development of mobile and wireless networks has prompted more devices to share data in time via the Internet. Meanwhile, data is highly time sensitive. It has been found that the value of data is becoming more and more critical to any application areas, significantly highlighting the importance of data pricing mechanisms in data transactions. Although traditional auction mechanisms for ordinary commodities are gradually becoming matures, they fail in the high timeliness data pricing market due to the following key challenges: Firstly, the value and price of the high timeliness data is ever changing with time, making existing mechanisms with fixed prices expired. Secondly, the price changing of such data is uncertain and dynamic, requiring the auction mechanisms to work stably under different price variations of the high timeliness data. To address these challenges, we for the first time innovatively propose an efficient auction mechanism for High Timeliness Data Pricing, namely HTDP. The newly proposed HTDP can maximize the profit of auctioneer in the high timeliness data transactions. And the key factor for HTDP's success is the consideration of the price changing in the high timeliness data, which fills the blank of traditional auction mechanisms in this area. We further evaluate the newly proposed HTDP on the overall auction profit, and compare the results with the benchmark. Experimental results demonstrate that HTDP not only achieves high profit under proper settings, but also is stable and efficient.