TY - GEN
T1 - Prediction-based QoS management for real-time data streams
AU - Wei, Yuan
AU - Prasad, Vibha
AU - Son, Sang H.
AU - Stankovic, John A.
PY - 2006
Y1 - 2006
N2 - With the emergence of large wired and wireless sensor networks, many real-time applications need to operate on continuous unbounded data streams. At the same time, many of these systems have inherent timing constraints. Providing deadline guarantees for queries over dynamic data streams is a challenging problem due to bursty data stream arrival rates and time-varying stream contents. In this paper, we propose a prediction-based Quality-of-Service (QoS) management scheme for periodic queries over dynamic data streams. Our QoS management scheme features novel query workload estimators, which predict the query workload using execution time profiling and input data sampling, and adjusts the query QoS levels based on online query execution time prediction. We implement our QoS management algorithm on a real-time data stream query system prototype called RTStream. Our experimental evaluation of the scheme shows that our query workload estimator performs very well even with workload fluctuations and our QoS management scheme yields better overall system utility than the existing approaches for QoS management.
AB - With the emergence of large wired and wireless sensor networks, many real-time applications need to operate on continuous unbounded data streams. At the same time, many of these systems have inherent timing constraints. Providing deadline guarantees for queries over dynamic data streams is a challenging problem due to bursty data stream arrival rates and time-varying stream contents. In this paper, we propose a prediction-based Quality-of-Service (QoS) management scheme for periodic queries over dynamic data streams. Our QoS management scheme features novel query workload estimators, which predict the query workload using execution time profiling and input data sampling, and adjusts the query QoS levels based on online query execution time prediction. We implement our QoS management algorithm on a real-time data stream query system prototype called RTStream. Our experimental evaluation of the scheme shows that our query workload estimator performs very well even with workload fluctuations and our QoS management scheme yields better overall system utility than the existing approaches for QoS management.
UR - http://www.scopus.com/inward/record.url?scp=38949123310&partnerID=8YFLogxK
U2 - 10.1109/RTSS.2006.34
DO - 10.1109/RTSS.2006.34
M3 - Conference contribution
AN - SCOPUS:38949123310
SN - 0769527612
SN - 9780769527611
T3 - Proceedings - Real-Time Systems Symposium
SP - 344
EP - 355
BT - Proceedings of 27th IEEE International Real-Time Systems Symposium, RTSS 2006
T2 - 27th IEEE International Real-Time Systems Symposium, RTSS 2006
Y2 - 5 December 2006 through 8 December 2006
ER -