An Efficient Data Maintenance Strategy for Data Service Mashup Based on Materialized View Selection

摘要

While end-users enjoy the full-fledged data service mashup with high convenience and flexibility, such issues as the response efficiency and the maintenance cost have popped up as the major concerns. In this paper, an efficient data maintenance strategy for the data service mashup is proposed. The strategy proposes a data maintenance model to measure the response cost and update cost of a group of data service mashups in terms of the request frequency and update frequency. Based on the model, a materialized view selection for data service mashup is proposed. Experiments show that our strategy can effectively reduce the maintenance cost of a lot of hosted data service mashups.