A Replication Strategy for Distributed Real-Time Object-Oriented Databases
ISORC '02 Proceedings of the Fifth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing
Feedback Control Scheduling in Distributed Real-Time Systems
RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
QoS Management in Replicated Real Time Databases
RTSS '03 Proceedings of the 24th IEEE International Real-Time Systems Symposium
Feedback Control of Computing Systems
Feedback Control of Computing Systems
Managing Deadline Miss Ratio and Sensor Data Freshness in Real-Time Databases
IEEE Transactions on Knowledge and Data Engineering
Prediction-Based QoS Management for Real-Time Data Streams
RTSS '06 Proceedings of the 27th IEEE International Real-Time Systems Symposium
DEUCON: Decentralized End-to-End Utilization Control for Distributed Real-Time Systems
IEEE Transactions on Parallel and Distributed Systems
I/O-Aware Deadline Miss Ratio Management in Real-Time Embedded Databases
RTSS '07 Proceedings of the 28th IEEE International Real-Time Systems Symposium
SENSORCOMM '08 Proceedings of the 2008 Second International Conference on Sensor Technologies and Applications
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The computing systems are becoming deeply embedded into ordinary life and interact with physical processes and events. They monitor the physical world with sensors and provide appropriate reaction and control over it. This cyber-physical interaction, which occurs through ubiquitous embedded systems, has the potential to transform how humans interact with and control the physical world. Applications of such systems include infrastructure management and environmental monitoring. For these applications, the demand for real-time data services is increasing since they are inherently data-intensive. However, providing real-time data services in such large-scale and geographically distributed environment is a challenging task. In particular, both unpredictable communicational delays and computational workloads of large-scale distributed systems can lead to large number of deadline misses. In this paper, we propose a real-time data service architecture called DRACON (Decentralized data Replication And CONtrol), which is designed to support large-scale distributed real-time applications. DRACON uses cluster-based replica-sharing and a decentralized control structure to address communication and computational unpredictability.