Towards Forecasting Low Network Traffic for Software Patch Downloads: An ARMA Model Forecast Using CRONOS

The usage of the Internet has become ubiquitous, even for desktop applications to assume that the computer system it is running on is connected to the Internet. Desktop applications rely on the Internet connectivity for software license authentication and also for maintenance through downloading of software patches. However, the latter can pose an annoyance to the user when he or she is relying on the Internet for real-time gaming or during heavy downloading of multimedia files. In this paper, we study the effectiveness of using the ARMA model to provide short range forecasting of Internet network TCP traffic for a single broadband line. The outcome of the research is positive and indicates that a step size of 30 seconds and irrespective of the window size gives the most accurate forecast. Through amplification of the results, this method shows strong indication that it can be implemented by software application developers to determine the most appropriate non-disruptive period to download their software patches. For small sized software patches, the software application can activate the download and a period of 120 seconds would be sufficient.