Adaptive fuzzy traffic estimator of reservation protocols on IP-based networks

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3 Citations (Scopus)

Abstract

Traffic estimation is significant to ensure the reliability and realization of network resource in the next generation Internet. However it is difficult to estimate the network traffic with variable bit rate and bursty data flow. In this paper, an adaptive approach based on fuzzy clustering technique for traffic estimation in resource protocol is proposed. Fuzzy clustering scheme is deployed to estimate traffic flows and predict the data flow in future. All flow patterns are clustered to extract the knowledge about the traffic flows. Instead of adopting conventional cluster matching scheme for the traffic pattern clusters, a characteristic neural network (CNN) is generated to fuse the obtained clusters in a CNN adaptively to reduce the computation in clustering. Experiments demonstrated the proposed approach works well for variable bit rate (VBR) flows.

Original languageEnglish
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume1
Publication statusPublished - 1999

Fingerprint

Fuzzy clustering
Neural networks
Network protocols
Electric fuses
Flow patterns
Flow rate
Internet
Experiments

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Control and Systems Engineering

Cite this

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title = "Adaptive fuzzy traffic estimator of reservation protocols on IP-based networks",
abstract = "Traffic estimation is significant to ensure the reliability and realization of network resource in the next generation Internet. However it is difficult to estimate the network traffic with variable bit rate and bursty data flow. In this paper, an adaptive approach based on fuzzy clustering technique for traffic estimation in resource protocol is proposed. Fuzzy clustering scheme is deployed to estimate traffic flows and predict the data flow in future. All flow patterns are clustered to extract the knowledge about the traffic flows. Instead of adopting conventional cluster matching scheme for the traffic pattern clusters, a characteristic neural network (CNN) is generated to fuse the obtained clusters in a CNN adaptively to reduce the computation in clustering. Experiments demonstrated the proposed approach works well for variable bit rate (VBR) flows.",
author = "Yau-Hwang Kuo and Horng, {Mong Fong} and Jung-Hsien Chiang",
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N2 - Traffic estimation is significant to ensure the reliability and realization of network resource in the next generation Internet. However it is difficult to estimate the network traffic with variable bit rate and bursty data flow. In this paper, an adaptive approach based on fuzzy clustering technique for traffic estimation in resource protocol is proposed. Fuzzy clustering scheme is deployed to estimate traffic flows and predict the data flow in future. All flow patterns are clustered to extract the knowledge about the traffic flows. Instead of adopting conventional cluster matching scheme for the traffic pattern clusters, a characteristic neural network (CNN) is generated to fuse the obtained clusters in a CNN adaptively to reduce the computation in clustering. Experiments demonstrated the proposed approach works well for variable bit rate (VBR) flows.

AB - Traffic estimation is significant to ensure the reliability and realization of network resource in the next generation Internet. However it is difficult to estimate the network traffic with variable bit rate and bursty data flow. In this paper, an adaptive approach based on fuzzy clustering technique for traffic estimation in resource protocol is proposed. Fuzzy clustering scheme is deployed to estimate traffic flows and predict the data flow in future. All flow patterns are clustered to extract the knowledge about the traffic flows. Instead of adopting conventional cluster matching scheme for the traffic pattern clusters, a characteristic neural network (CNN) is generated to fuse the obtained clusters in a CNN adaptively to reduce the computation in clustering. Experiments demonstrated the proposed approach works well for variable bit rate (VBR) flows.

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