Maintaining Data Freshness in Distributed Real-Time Databases

Many real-time systems need to maintain fresh views which are derived from shared data that are distributed among multiple sites. When a base data item changes, all derived views that are based on it need to be recomputed. There are two major derived data recomputation strategies - immediate update and ondemand update. However, they both have their advantages and limitations. In this paper, we study the performance of derived data update using immediate and on-demand strategies in distributed real-time databases and identify several criteria for choosing proper update policies. Based on these criteria, we propose a derived data update algorithm. In our algorithm, the update policy of a particular derived data item is determined dynamically by its access frequency, current transaction miss ratio and the system utilization. A thorough simulation study shows that our algorithm outperforms immediate and on-demand update in most cases.

• Type: Conference
• Year: 2004
• Where: ECRTS
• Authors: Yuan Wei, Sang Hyuk Son, John A. Stankovic
• Keywords: Data Update, Data Update Algorithm, ECRTS 2004, Embedded Systems, Update