@article{nayak_perros_2020, title={Automated real-time anomaly detection of temperature sensors through machine-learning}, volume={34}, ISSN={["1748-1287"]}, DOI={10.1504/IJSNET.2020.111233}, abstractNote={Fast identification of faulty sensors is necessary for guaranteeing their robust functions in diverse applications ranging from extreme weather prediction to energy saving to healthcare. We present an automated machine-learning based framework that can detect anomalies of temperature sensor data in real-time. We adopted a purely temporal approach that utilises a univariate time-series (UTS) generated by a single sensor. The framework divides the UTS into subsequences, models each subsequence stochastically as an autoregressive function, and finally mines the function parameters with a one-class support vector machines (OC-SVM) that classifies any outlier as an anomaly. Extensive experimentation showed that the framework identifies both normal and anomalous data correctly with high degrees of accuracy.}, number={3}, journal={INTERNATIONAL JOURNAL OF SENSOR NETWORKS}, author={Nayak, Debanjana and Perros, Harry}, year={2020}, pages={137–152} }
 @inproceedings{tanwir_nayak_perros_2016, title={Modeling 3D video traffic using a Markov Modulated Gamma Process}, DOI={10.1109/iccnc.2016.7440638}, abstractNote={Three-dimensional (3D) television and video streaming has become very popular over the last few years. Multiview encoded video is used to support 3D video applications. The statistical characteristics of multiview video are significantly different from the traditional single-view video and therefore existing video traffic models are no more applicable for this type of video. In this paper, we propose and evaluate a new model for multiview video that is based on a Markov process. To the best of our knowledge, there is only one other model for multiview video that has been proposed in the literature by Rossi et al. We compared the two models using Q-Q plots and the autocorrelation function of the frame sizes along with QoS metrics of the resulting packet traces estimated by simulation. The comparison results show that our model has less complexity and better accuracy.}, booktitle={2016 International Conference on Computing, Networking and Communications (ICNC)}, author={Tanwir, S. and Nayak, D. and Perros, H.}, year={2016} }