A game theory based framework for materialized view selection in data warehouses

In this paper, a game theory based framework for the materialized view selection is proposed. In the proposed framework, query processing and view maintenance costs play a game against each other as two players and continue the game until reach the equilibrium. According to the framework, a new static method, called Game Theory based Materialized View selection (GTMV), has been proposed. Verification of proposed approach has been evaluated using several synthetic and real world datasets. Experimental results show that the GTMV method has better performance comparing previous algorithms and substantially outperform former methods.