Autoregression Models for Trust Management in Wireless Ad Hoc Networks

Title: Autoregression Models for Trust Management in Wireless Ad Hoc Networks
Authors: Li, Zhi
Date: 2011
Abstract: In this thesis, we propose a novel trust management scheme for improving routing reliability in wireless ad hoc networks. It is grounded on two classic autoregression models, namely Autoregressive (AR) model and Autoregressive with exogenous inputs (ARX) model. According to this scheme, a node periodically measures the packet forwarding ratio of its every neighbor as the trust observation about that neighbor. These measurements constitute a time series of data. The node has such a time series for each neighbor. By applying an autoregression model to these time series, it predicts the neighbors future packet forwarding ratios as their trust estimates, which in turn facilitate it to make intelligent routing decisions. With an AR model being applied, the node only uses its own observations for prediction; with an ARX model, it will also take into account recommendations from other neighbors. We evaluate the performance of the scheme when an AR, ARX or Bayesian model is used. Simulation results indicate that the ARX model is the best choice in terms of accuracy.
CollectionThèses, 2009 - // Theses, 2009 -
Li_Zhi_thesis_2011.pdfGraduation Thesis for M.A.Sc degree1.48 MBAdobe PDFOpen