Simple Traffic Prediction Mechanism and its Applications in Wireless Networks

Abstract

Several studies have analyzed traffic traces collected from real world deployments of wireless networks. The vast majority of these studies have employed descriptive statistics with the aim of obtaining insights into the different aspects of wireless networks. While the contributions of all these studies are valuable, they mainly provide guidelines on design and deployment of wireless networks on a longer term perspective. The ability to predict at shorter timescales such as on the order of a few minutes empowers the network management entity with extra intelligence to optimize network performance taking into account anticipated traffic conditions. This paper proposes a simple traffic prediction mechanism using the Recursive Least Squares algorithm and highlights its applications in proactive network management. The performance of the proposed prediction mechanism is also evaluated using publicly available data set collected from a real world wireless network. Results from this study show that the RLS algorithm is capable of accurately predicting the traffic load and shows good adaptive behaviour. Moreover it is intuitively simple and results in a lightweight implementation.