• Journal of the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.46-55
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• 1997

This paper presents the development of intelligent performance management of computer communication networks for larger-scale integrated systems and the demonstration of its efficacy using computer simula- tion. The innermost core of the performance management is based on fuzzy set theory. This fuzzy perfor- mance manager has learning ability by using principles of neuro-fuzzy model, neuralnetwork, genetic algo- rithm(GA). Two types of performance managers are described in this paper. One is the Neuro-Fuzzy Per- formance Manager(NFPM) of which learning ability is based on the conventional gradient method, and the other is GA-based Neuro-Fuzzy Performance Manager(GNFPM)with its learning ability based on a genetic algorithm. These performance managers have been evaluated via discrete event simulation of a computer network.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.471-476
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• 1995

This paper focues on development and implementation of a perfomance management algorithm for IEEE802.4 token bus networks to serve large-scale integrated manufacturing systems. Such factory automation networks have to satisfy delay constraints imposed on time-critical messages while maintaining as much network capacity as possible for non-time-critical messages. This paper presents the structure of a network performance manager that possesses the knowledge about perfomance management in a set of fuzzy rules and deriving its action through fuzzy inference mechanism. The efficacy of the performance management has been demonstrated by a series of simulation experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.600-613
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• 1999

This paper focuses on development of a performance manager for IEEE 802.4 token bus networks to serve large-scale integrated systems. In order to construct the management algorithm, the principles of fuzzy logic, genetic algorithm, and neural network have been combined to represent human knowledge and to imitate of human inference mechanism. Through the simulation experiments, it is shown that the proposed performance manager is capable of improving the network performance without a priori knowledge.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.8
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• pp.2436-2448
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• 1996

This paper presents the development of three types of network performance manager for IEEE 802.4 token bus networks that are a part of Manufacturing Automation Protocol(MAP). The performance managers attempt to keep the average data latency below a certain level specified for each priority class. All of the three performance managers are based on a set of fuzzy rules incorporating the knowledge on the relationship between data latency and parameters of the priority mechanism. These Fuzzy Network Performance Managers(FNPMs) have been evaluated via discrete event simulation to demonstrate their efficacy.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.6
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• pp.152-160
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• 1996

This paper focuses on development and evaluation of a performance management algorithm for IEEE 802.4 token bus networks to serve large-scale integrated manufacturing systems. Such factory automation networks have to satisfy delay constraints imposed on time-critical messages while maintaining as much network capacity as possible for non-time-critical messages. This paper presents a network performance manager that adjusts queue capacity as well as timers by using a set of fuzzy rules and fuzzy inference mechanism. The efficacy of the performance management has been demonstrated by a series of simulation experiments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.664-669
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• 1994

This paper focuses on development and implementation of a performance management algorithm for IEEE802.4 token bus networks to serve large-scale integrated manufacturing systems. Such factory automation networks have to satisgy delay constraints imposed on time-critical messages while maintaining as much network capacity as possible for non-time-critical messages. This paper presents a network perfomance manager that adjusts queue apacity as well as timers by using a set of fuzzy rules and fuzzy inference mechanism. The efficacy of the performance management has been demonstrated by a series of simulation experiments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.461-466
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• 1993

This paper focuses on development and implementation of a performance management algorithm for IEEE802.4 token bus networks to serve large-sale integrated systems. The delivery of time critical messages within delay constraints is an important criterion in the design and management of computer communication networks. In order to achieve this goal, the theory of fuzzy sets has been employed to imitate human's reasoning. The Fuzzy Network Performance Manager(FNPM) is composed of two parts: FNPM1 & FNPM2. FNPM1 is solily intended to satisfy the data latencyfor the highest priority while the other part is trying to satisfy those for the lower priorities. The FNPM requires average data latency, throughput, and token circulation time for its inputs. The efficacy of the FNPM has been evaluated by a series of simulation experiments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.514-518
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• 1996

This paper focuses on automated generation of the knowledge base for a fuzzy network performance manager in order to satisfy delay constraints imposed on time-critical messages while maintaining as much network capacity as possible for non-time-critical messages. Therefore, the bowlegs base is formulated to minimize a certain penalty function by using a type of genetic algorithm. The efficacy of the formulation method has been demonstrated by a series of simulation experiments.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.2
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• pp.5-13
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• 2000

Most networks for automation are tuned to an expected traffic condition ar their design stage. During their actual operations, however, the networks experience considerable changes in traffic from time to time. These traffic changes caused by common events like machine failure and production schedule change may adversely affect th network performance and, in turn , the performance of the connected devices. This paper presents experimental results for performance management of a Profibus-FMS network. The performance management aims to maintain a uniform level of network performance at all stations under changing network traffic. The performance management algorithm monitors the performance of individual network stations and commands the stations to change their timer values in order to have comparable performance at all stations. In order to determine the amount of timer change, the algorithm employs a set of fuzzy rules. The algorithm has been evaluated on a Profibus network.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.379-383
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• 1997

This paper focuses on self-organization of fuzzy rules for performance management of computer communication networks serving manufacturingsystems. The performance managment aims to improve the network performance in handling various types of messages by on-line adjustment of protocol parameters. The principle of fuzzy logic has been used in repressenting the knowledge of human expert on the performance management and in deriving manafement decisions. In this paper, we present an of this self-organization is domonstrated by discrete simulation of an IEEE 802.4 network.