Specification and management of QoS in real-time databases supporting imprecise computations

TLDR

Real‑time applications increasingly demand sophisticated data services, but unpredictable workloads can overload databases and cause temporal violations; imprecise computation techniques mitigate this by allowing graceful degradation. The paper proposes a QoS specification and management framework for real‑time databases. The framework includes a QoS requirement model, a feedback‑control scheduling architecture, and algorithms for various policies and behaviors. Experiments demonstrate that the framework yields robust, controlled behavior under transient overloads and inaccurate runtime estimates, outperforming baseline feedback‑control algorithms.

Abstract

Real-time applications such as e-commerce, flight control, chemical and nuclear control, and telecommunication are becoming increasingly sophisticated in their data needs, resulting in greater demands for real-time data services that are provided by real-time databases. Since the workload of real-time databases cannot be precisely predicted, they can become overloaded and thereby cause temporal violations, resulting in damage or even a catastrophe. Imprecise computation techniques address this problem and allow graceful degradation during overloads. In this paper, we present a framework for QoS specification and management consisting of a model for expressing QoS requirements, an architecture based on feedback control scheduling, and a set of algorithms implementing different policies and behaviors. Our approach gives a robust and controlled behavior of real-time databases, even for transient overloads and with inaccurate runtime estimates of the transactions. Further, performance experiments show that the proposed algorithms outperform a set of baseline algorithms that uses feedback control.