John A. Stankovic, Tian He, Tarek Abdelzaher, Mike Marley, Gang Tao, Sang Son, Cenyan Lu, "Feedback Control Scheduling in Distributed Real-Time Systems," 2011 IEEE 32nd Real-Time Systems Symposium, pp. 59, 22nd IEEE Real-Time Systems Symposium (RTSS'01), 2001.

@article{ 10.1109/REAL.2001.990596,
author = {John A. Stankovic and Tian He and Tarek Abdelzaher and Mike Marley and Gang Tao and Sang Son and Cenyan Lu},
title = {Feedback Control Scheduling in Distributed Real-Time Systems},
journal ={2011 IEEE 32nd Real-Time Systems Symposium},
volume = {0},
year = {2001},
isbn = {0-7695-1420-0},
pages = {59},
doi = {http://doi.ieeecomputersociety.org/10.1109/REAL.2001.990596},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}

TY - CONF
JO - 2011 IEEE 32nd Real-Time Systems Symposium
TI - Feedback Control Scheduling in Distributed Real-Time Systems
SN - 0-7695-1420-0
SP
EP
A1 - John A. Stankovic,
A1 - Tian He,
A1 - Tarek Abdelzaher,
A1 - Mike Marley,
A1 - Gang Tao,
A1 - Sang Son,
A1 - Cenyan Lu,
PY - 2001
KW - Distributed soft real-time systems are becoming increasingly unpredictable due to several important factors such as the increasing use of commercial-off-the-shelf components
KW - the trend towards open systems
KW - and the proliferation of data-driven applications whose execution parameters vary significantly with input data. Such systems are less amenable to traditional worst-case real-time analysis. Instead
KW - system-wide feedback control is needed to meet performance requirements. In this paper
KW - we ex-tend our previous work on developing software control algorithms based on a theory of feedback control to distributed systems. Our approach makes three important contributions. First
KW - it allows the designer for a distributed real-time application to specify the desired temporal behavior of system adaptation
KW - such as the speed of convergence to desired performance upon load or resource changes. This is in contrast to specifying only steady-state metrics
KW - e.g.
KW - deadline miss ratio. Second
KW - unlike QoS optimization approaches
KW - our solution meets performance guarantees without accurate knowledge of task execution parameters - a key advantage in an unpredictable environment. Third
KW - in contrast to ad hoc algorithms based on intuition and testing
KW - our solution has a basis in the theory and practice of feedback control scheduling. Performance evaluation reveals that the solution not only has excellent steady state behavior
KW - but also meets stability
KW - overshoot
KW - and settling time requirements. We also show that the solution outperforms several other algorithms available in the literature.
VL - 0
JA - 2011 IEEE 32nd Real-Time Systems Symposium
ER -