Bandwidth Utilization Prediction in LAN Network Using Time Series Modeling

monitoring the behavior of computer networks is essential for problem identification and optimal management. Part of this behavior to be monitored is the utilization of the network bandwidth. Several techniques are used to model and forecast network traffic such as time series models, modern data mining techniques, soft computing approaches, and neural networks are used for network traffic analysis and prediction. Efficient bandwidth utilization and optimization are very interesting research issues in effective networks because bandwidth is one of the most required and expensive Internet components needed today. It is generally known that the higher the bandwidth available, the better the network performance, thus an essential aid for network design and bandwidth wastage control and a need for traffic models which can capture the characteristics is necessary. In this paper, a time series prediction models were proposed for LAN office network bandwidth utilization. The proposed prediction models are tested by using evaluation metrics used in time series such as MSE and performance evaluation plot. Testing results show that the proposed models can enhance the detection of bandwidth traffic and provide an efficient tool for bandwidth utilization.