Paper Info
Title
A Novel Auction-Based Query Pricing Schema
Abstract
As a common processing method, query is widely used in many areas, such as graph processing, machine learning, statistics. However, queries are usually priced according to vendor-specified fixed views (API) or number of transactions, which ignores query heterogeneity(computing resource consumption for query and information that the answer brings) and violates the microeconomic principles. In this work we study the relational query pricing problem and design efficient auctions by taking into account both information (i.e., data) value and query resource consumption. Different from the existing query pricing schemes, query auction determines data prices that reflect the demand–supply of shared computing resources and information value (i.e., price discovery). We target query auction that runs in polynomial time and achieves near-optimal social welfare with a good approximation ratio, while elicits truthful bids from consumers. Towards these goals, we adapt the posted pricing framework in game-theoretic perspective by casting the query auction design into an Integer Linear Programming problem, and design a primal-dual algorithm to approximate the NP-hard optimization problem. Theoretical analysis and empirical studies driven by a real-world data market benchmark verify the efficiency of our query auction schema.
Year
DOI
Venue
2019
10.1007/s10766-017-0534-x
International Journal of Parallel Programming
Keywords
Field
DocType
Query pricing, Auction design, Query processing
Query optimization,Web search query,Query language,Query expansion,Information retrieval,Computer science,Sargable,View,Theoretical computer science,Common value auction,Optimization problem
Journal
Volume
Issue
ISSN
47
4
1573-7640
Citations 
PageRank 
References 
0
0.34
23
Authors
5
Name
Order
Citations
PageRank
Bin Lu1708.22
Xiaohui Wei239154.44
Shang Gao323.06
Yuanyuan Liu426129.20
Zongpeng Li52054153.21