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.
|Journal||Proceedings of the IEEE International Conference on Systems, Man and Cybernetics|
|Publication status||Published - 1999 Dec 1|
|Event||1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics' - Tokyo, Jpn|
Duration: 1999 Oct 12 → 1999 Oct 15
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Hardware and Architecture