Most algorithms for computing diagnoses within a modelbased diagnosis framework are deterministic. Such algorithms guarantee soundness and completeness, but are P 2 hard. To overc...
Alexander Feldman, Gregory M. Provan, Arjan J. C. ...
This paper proposes a Bayesian algorithm to estimate the parameters of a smooth transition regression model. With in this model, time series are divided into segments and a linear...
Performance modeling is important for the purpose of developing efficient dimensioning tools for large complicated networks. But it is difficult to achieve in heterogeneous wireles...
1 A new method for detecting anomalies in the usage of protocols in computer networks is presented in this work. The proposed methodology is applied to TCP and disposed in two step...
In this paper, we develop a queuing theory based analytical model to evaluate the performance of transactional memory. Based on the statistical characteristics observed on actual e...