Title :
Valuating Queries for Data Trading in Modern Cities
Author :
Ruiming Tang;Huayu Wu;Xiuqiang He;St?phane
Author_Institution :
Huawei Noah´s Ark Lab., Hong Kong, China
Abstract :
The availability of data trading mechanisms and platforms is a paramount prerequisite to the development of effective smart city services. In order for data to become a commodity ready for consumption, transformation and exploitation by smart services, it must be made available and tradable on data market places. For such data market places to be viable there is a compelling need for a sound data pricing model that is conducive of the healthiness of the market. In this paper, we discuss the definition of a pricing model in which views are priced and queries are valuated using views. We define the price of a query as the cheapest combination of the prices of a set of views that can answer the query. We discuss the devising of effective and efficient algorithms of the computation of the price of a query. We show that the problem of computing the price is similar but not identical to the problem of answering queries using views. We therefore adapt the MiniCon algorithm, which was designed to answer queries using views, to the task at hand. We finally discuss further challenges created by the definition of a framework for valuating queries using views.
Keywords :
"Pricing","Database languages","Context","Cities and towns","Data models","Query processing"
Conference_Titel :
Data Mining Workshop (ICDMW), 2015 IEEE International Conference on
Electronic_ISBN :
2375-9259
DOI :
10.1109/ICDMW.2015.11