Estimation of Network Performance: An approach based on Network Experience
ICOIN '01 Proceedings of the The 15th International Conference on Information Networking
SPAND: Shared Passive Network Performance Discovery
SPAND: Shared Passive Network Performance Discovery
Self-similar and fractal nature of internet traffic
International Journal of Network Management
An architecture for large scale Internet measurement
IEEE Communications Magazine
Network traffic characterization and network information services-R&D on JGN
Computer Communications
Journal of Network and Systems Management
Resource utilization prediction: long term network web service traffic
Proceedings of the 2nd annual conference on Research in information technology
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Network measurement traces contain information regarding network behavior over the period of observation. Research carried out from different contexts shows predictions of network behavior can be made depending on network past history. Existing works on network performance prediction use a complicated stochastic modeling approach that extrapolates past data to yield a rough estimate of long-term future network performance. However, prediction of network performance in the immediate future is still an unresolved problem. In this paper, we address network performance prediction as an engineering problem. The main contribution of this paper is to predict network performance dynamically for the immediate future. Our proposal also considers the practical implication of prediction. Therefore, instead of following the conventional approach to predict one single value, we predict a range within which network performance may lie. This range is bounded by our two newly proposed indices, namely, Optimistic Network Performance Index (ONPI) and Robust Network Performance Index (RNPI). Experiments carried out using one-year-long traffic traces between several pairs of real-life networks validate the usefulness of our model.