A pattern-based prediction: An empirical approach to predict end-to-end network latency

Understanding latency in network-based applications has received considerable attention to provide consistent and acceptable levels of services. This paper presents an empirical approach, a pattern-based prediction method, to predict end-to-end network latency. The key idea of the approach is to utilize past history of latency and their variation patterns in latency predictions. After some preliminary study on simple numerical prediction models we examine the effectiveness of the proposed method with real latency data and various definitions of network stability. Our results show that the pattern-based method outperforms any single numerical model obtaining an overall prediction accuracy of 86.2%.