Title :
Neural network based admission controller for proximity aware mobile services
Author :
Quah, Jon Tong-Seng ; Lim, Luo-Ren
Abstract :
Technological advancement in mobile devices is driving the demand for valued added services. Proximity aware mobile application is one such service which user consumes services offered by service providers in the user´s environment. One key issue in providing proximity aware services in a wireless networking environment is congestion control at the server. To handle this problem, an effective connection admission control (CAC) mechanism is required. This paper investigate the feasibility of such a mechanism by comparing simulated back-propagation and learning vector quantization neural networks. The back-propagation neural networks was shown to have a higher performance.
Keywords :
backpropagation; learning systems; mobile radio; neurocontrollers; telecommunication congestion control; telecommunication network management; telecommunication traffic; vector quantisation; back-propagation neural network; connection admission control; learning vector quantization; proximity aware mobile service; server congestion control; valued added service; wireless network traffic management; wireless networking environment; Admission control; Artificial neural networks; Communication system traffic control; Fuzzy logic; Network servers; Neural networks; Quality of service; Traffic control; Vector quantization; Wireless networks; Back-Propagation; Learning Vector Quantization; Neural Network; Proximity;
Conference_Titel :
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-3548-7
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2009.5178781
