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2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
An Adaptive Performance Management Method for Failure Detection
August 06-August 08
ISBN: 978-0-7695-3263-9
ASCII Text
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Ke Liang, Xingshe Zhou, Kailong Zhang, Ruiqing Sheng, "An Adaptive Performance Management Method for Failure Detection," Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on, pp. 51-56, 2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2008.
 
 
BibTex
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@article{ 10.1109/SNPD.2008.69,
author = {Ke Liang and Xingshe Zhou and Kailong Zhang and Ruiqing Sheng},
title = {An Adaptive Performance Management Method for Failure Detection},
journal ={Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on},
volume = {0},
year = {2008},
isbn = {978-0-7695-3263-9},
pages = {51-56},
doi = {http://doi.ieeecomputersociety.org/10.1109/SNPD.2008.69},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on
TI - An Adaptive Performance Management Method for Failure Detection
SN - 978-0-7695-3263-9
SP51
EP56
A1 - Ke Liang,
A1 - Xingshe Zhou,
A1 - Kailong Zhang,
A1 - Ruiqing Sheng,
PY - 2008
KW - null
VL - 0
JA - Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on
ER -
 
Failure detection is an essential part to build high dependable distributed real-time embedded systems. However, the performance degradation of production work due to the execution of failure detection cannot be omitted. We present an adaptive performance management method for failure detection based on feedback control theory. This method is autonomous and thus allows the system to self-manage the CPU resources allocated for failure detection, with only the high-level policy input. Therefore, it limits the performance impact due to the execution of failure detection, even in the dynamic environment.
Citation:
Ke Liang, Xingshe Zhou, Kailong Zhang, Ruiqing Sheng, "An Adaptive Performance Management Method for Failure Detection," snpd, pp.51-56, 2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2008
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