Network state estimation in wireless multi-hop networks

Abstract: Multi-hop wireless networks in general and those built upon IEEE 802.11 standard in particular are known for their highly dynamic and unstable performance. The commonly accepted way for improving the situation is to jointly optimize the performance of protocols across different communications layers. Being able to characterize a state of the network is essential to enable the cross-layer optimization. This licentiate thesis investigates methods for passive characterization of network state at medium access control and transport layers based on information accessible from the corresponding layers below.Firstly, the thesis investigates a possibility for characterizing traffic intensity relying solely on the statistics of measurements from the physical layer. An advantage of this method is that it does not require decoding of the captured packets, by this accounting for the effect from long-range interferences introduced by transmissions at the border of the communication range of a receiver.Secondly, a question of predicting TCP throughput over a multi-hop wireless path is addressed. The proposed predictor is a practically usable function of statistically significant parameters at transport, medium access control and physical communication layers. The presented model is able to predict the TCP throughput with 99% accuracy, which provides an essential input for various cross-layer optimization processes.Finally, during the course of the experimental work the issues of accuracy of simulation-based modeling of communication processes were investigated. The thesis is concluded by presenting a comparative study of the performance characteristics measured in a single channel multi-hop wireless network test-bed and the corresponding measurements obtained from popular network simulators ns-2 and ns-3 when configured with identical settings. The thesis presents the evaluation of the mismatch between the results obtained in the test-bed and the simulators with their standard empirical radio models.