Performance Models Preventing Multi-Agent Systems from Overloading Computational Resources
Automation, Control and Intelligent Systems
Volume 2, Issue 6, December 2014, Pages: 105-111
Received: Nov. 12, 2014;
Accepted: Nov. 27, 2014;
Published: Dec. 5, 2014
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Petr Kadera, Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, CZ-169 00, Prague, Czech Republic
Petr Novak, Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, CZ-169 00, Prague, Czech Republic; Christian Doppler Laboratory for Software Engineering Integration for Flexible Automation Systems, Vienna University of Technology, A-1040, Vienna, Austria
Vaclav Jirkovsky, Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, CZ-169 00, Prague, Czech Republic; Rockwell Automation Research and Development Center, CZ-150 00, Prague, Czech Republic
Pavel Vrba, Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, CZ-169 00, Prague, Czech Republic
Multi-Agent Systems (MASs) suffer from low immunity against burst of arrival requests which can result in a permanent outage of such systems. This factor limits the suitability of MASs for control of real-world manufacturing systems with strict requirements on performance and reliability. This manuscript explains the origins of the performance degradation of MASs based on Contract-Net Protocol and proposes a method that protects the systems against the destructive effect of temporal overloads. The proposed method continuously observes the communication among agents and analyzes it in order to identify possible saturation of a system resource. If triggering a new action saturates a system resource, the carrying out of the action will be postponed. The impacts of the method are demonstrated on a test-bed consisted of six mini-computers Raspberry Pi. It shows that the proposed method avoids overloading of the system and thus guarantees a specific system throughput effectively and efficiently.
Performance Models Preventing Multi-Agent Systems from Overloading Computational Resources, Automation, Control and Intelligent Systems.
Vol. 2, No. 6,
2014, pp. 105-111.
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