Cluster Computing and the Grid, IEEE International Symposium on (2006)
May 16, 2006 to May 19, 2006
Alaknantha Eswaradass , Illinois Institute of Technology, USA
Xian-He Sun , Illinois Institute of Technology, USA
Ming Wu , Illinois Institute of Technology, USA
The applicability of network-based computing depends on the availability of the underlying network bandwidth. However, network resources are shared and the available network bandwidth varies with time. There is no satisfactory solution available for network performance predictions. In this research, we propose, design, and implement the NBP (Network Bandwidth Predictor) for rapid network performance prediction. NBP is a new system that employs a neural network based approach for network bandwidth forecasting. This system is designed to integrate with most advanced technologies. It employs the NWS (Network Weather Service) monitoring subsystem to measure the network traffic, and provides an improved, more accurate performance prediction than that of NWS, especially with applications with a network usage pattern. The NBP system has been tested on real time data collected by NWS monitoring subsystem and on trace files. Experimental results confirm that NBP has an improved prediction.
Performance prediction, Network bandwidth, Artificial Neural Network, Distributed computing
X. Sun, M. Wu and A. Eswaradass, "Network Bandwidth Predictor (NBP): A System for Online Network performance Forecasting," Cluster Computing and the Grid, IEEE International Symposium on(CCGRID), Singapore, 2006, pp. 265-268.