Title
An engineering approach to dynamic prediction of network performance from application logs
Abstract
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.
Year
DOI
Venue
2005
10.1002/nem.554
Int. Journal of Network Management
Keywords
Field
DocType
dynamic prediction,network performance dynamically,immediate future,application log,network performance prediction,network past history,engineering approach,optimistic network performance index,network measurement trace,real-life network,network performance,network behavior,long-term future network performance,indexation,stochastic model
Dynamic network analysis,Traffic generation model,Data mining,Computer science,Network simulation,Dynamic prediction,Network traffic simulation,Network behavior,Bounded function,Network performance
Journal
Volume
Issue
Citations 
15
3
8
PageRank 
References 
Authors
0.58
9
6