標題: | PSD-based neural-net connection admission control |
作者: | Chang, CJ Lin, SY Cheng, RG Shiue, YR 交大名義發表 電信工程研究所 National Chiao Tung University Institute of Communications Engineering |
公開日期: | 1997 |
摘要: | ATM (asynchronous transfer mode) systems can support services with bursty traffic. An ATM system needs a sophisticated and real-time connection admission controller not only to guarantee the required quality-of-service (QoS) for existing calls but also to raise the system efficiency. Input process has a power-spectral-density (PSD) which explicitly contains the correlation behavior of input traffic and has a great impact on the system performance. Also, a neural network has been widely applied to deal with traffic control related problems in ATM systems because of its self-learning capability. In this paper, we propose a PSD-based neural-net connection admission control (PNCAC) method for an ATM system. Under the QoS constraint, we construct a decision hyperplane of the connection admission control according to parameters of the power spectrum. We further adopt the learning/adapting capabilities of the neural network to adjust the optimum location of the boundary between these two decision spaces. Simulation results show that the PNCAC method provides a superior system utilization over the conventional CAC schemes by an amount of 18%, while keeping the QoS contract. |
URI: | http://hdl.handle.net/11536/19627 |
ISBN: | 0-8186-7780-5 |
ISSN: | 0743-166X |
期刊: | IEEE INFOCOM '97 - THE CONFERENCE ON COMPUTER COMMUNICATIONS, PROCEEDINGS, VOLS 1-3: SIXTEENTH ANNUAL JOINT CONFERENCE OF THE IEEE COMPUTER AND COMMUNICATIONS SOCIETIES - DRIVING THE INFORMATION REVOLUTION |
起始頁: | 955 |
結束頁: | 962 |
顯示於類別: | 會議論文 |