TY - GEN
T1 - Optimal state prediction for feedback-based QoS adaptations
AU - Li, Baochun
AU - Xu, Dongyan
AU - Nahrstedt, K.
N1 - Funding Information:
‘This research was supported by the Air Force Grant under contract number F30602-97-2-0121, National Science Foundation Grant under contract number NSF EIS 98-70736, and National Science Foundation Career Grant under contract number NSF CCR 96-23867.
Publisher Copyright:
© 1999 IEEE.
PY - 1999
Y1 - 1999
N2 - In heterogeneous network environments with performance variations present, complex distributed applications, such as distributed visual tracking applications, are desired to adapt themselves and to adjust their resource demands dynamically, in response to fluctuations in either end system or network resources. By such adaptations, they are able to preserve the user-perceptible critical QoS parameters, and trade off non-critical ones. However, correct decisions on adaptation timing and scale, such as determining data rate transmitted from the server to clients in an application, depend on accurate observations of system states, such as quantities of data in transit or arrived at the destination. Significant end-to-end delay may obstruct the desired accurate observation. We present an optimal state prediction approach to estimate current states based on available state observations. Once accurate predictions are made, the applications can be adjusted dynamically based on a control-theoretical model. Finally, we show the effectiveness of our approach with experimental results in a client-server based visual tracking application, where application control and state estimations are accomplished by middleware components.
AB - In heterogeneous network environments with performance variations present, complex distributed applications, such as distributed visual tracking applications, are desired to adapt themselves and to adjust their resource demands dynamically, in response to fluctuations in either end system or network resources. By such adaptations, they are able to preserve the user-perceptible critical QoS parameters, and trade off non-critical ones. However, correct decisions on adaptation timing and scale, such as determining data rate transmitted from the server to clients in an application, depend on accurate observations of system states, such as quantities of data in transit or arrived at the destination. Significant end-to-end delay may obstruct the desired accurate observation. We present an optimal state prediction approach to estimate current states based on available state observations. Once accurate predictions are made, the applications can be adjusted dynamically based on a control-theoretical model. Finally, we show the effectiveness of our approach with experimental results in a client-server based visual tracking application, where application control and state estimations are accomplished by middleware components.
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U2 - 10.1109/IWQOS.1999.766476
DO - 10.1109/IWQOS.1999.766476
M3 - Conference contribution
AN - SCOPUS:84962015427
T3 - IEEE International Workshop on Quality of Service, IWQoS
SP - 37
EP - 46
BT - 1999 7th International Workshop on Quality of Service, IWQOS 1999
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Workshop on Quality of Service, IWQOS 1999
Y2 - 31 May 1999 through 4 June 1999
ER -