Adaptive Update Policy for Proactive Management of Deadline Miss Ratio and Data Freshness in Real-Time Database Models

Important applications, like e-commerce, online stock trading, traffic control demand real-time data services. Conventional database perform poor at these applications. A database for real-time data services has to support timing constraints and temporal consistency in addition to supporting characteristics of a conventional database system. In other words, it is desirable to execute transactions within its deadline using updated data reflecting the current world status. In order to achieve these objectives, the Quality of Service (QoS) metrics like miss ratio, data freshness, perceived freshness and Quality of Data (QoD) management schemes along with architectures for effective QoS management are introduced in Literature. These architectures accommodate the unpredictable change in user transactions and maintain QoS metrics by changing the update pattern of data items, which are periodically updated to reflect the real world status. In this study, we present architecture with an improved update policy and propose an algorithm to change the update pattern in such a manner that the system is able to maintain QoS metrics even under busty traffic conditions. The simulation results show that the proposed model can keep QoS metrics, like miss ratio and perceived freshness within limits under busty traffic conditions .