하이브리드형 신경망을 이용한 ATM망에서의 호 수락제어에 관한 연구

Study on Call Admission Control in ATM Networks Using a Hybrid Neural Network.

In this paper, a new real-time neural network connection admission controller is proposed. The proposed controller measures traffic flows, cell loss rate and cell delay periodically each classes. The Neural network learns the relation between those measured information and service quality by real-time. Also the proposed controller uses the DWRR multiplexer with buffer dedicated to every traffic source in order to measure the delay that cells experience in buffer. Experimental result shows that the proposed method can control effectively heterogeneous traffic sources with diverse QoS requirement.