Wireless networks congestion control

Congestion control in wireless networks is an important and open issue. Previous research has proven the poor performance of the Transport Control Protocol (TCP) in such networks. The factors that contribute to the poor performance of TCP in wireless environments concern its unsuitability to identify/detect and react properly to network events, its TCP window based ow control algorithm that is not suitable for the wireless channel, and the congestion collapse due to mobility. New rate based mechanisms have been proposed to mitigate TCP performance in wired and wireless networks. However, these mechanisms also present poor performance, as they lack of suitable bandwidth estimation techniques for multi-hop wireless networks. It is thus important to improve congestion control performance in wireless networks, incorporating components that are suitable for wireless environments. A congestion control scheme which provides an e - cient and fair sharing of the underlying network capacity and available bandwidth among multiple competing applications is crucial to the definition of new e cient and fair congestion control schemes on wireless multi-hop networks. The Thesis is divided in three parts. First, we present a performance evaluation study of several congestion control protocols against TCP, in wireless mesh and ad-hoc networks. The obtained results show that rate based congestion control protocols need an eficient and accurate underlying available bandwidth estimation technique. The second part of the Thesis presents a new link capacity and available bandwidth estimation mechanism denoted as rt-Winf (real time wireless inference). The estimation is performed in real-time and without the need to intrusively inject packets in the network. Simulation results show that rt-Winf obtains the available bandwidth and capacity estimation with accuracy and without introducing overhead trafic in the network. The third part of the Thesis proposes the development of new congestion control mechanisms to address the congestion control problems of wireless networks. These congestion control mechanisms use cross layer information, obtained by rt-Winf, to accurately and eficiently estimate the available bandwidth and the path capacity over a wireless network path. Evaluation of these new proposed mechanisms, through ns-2 simulations, shows that the cooperation between rt-Winf and the congestion control algorithms is able to significantly increase congestion control eficiency and network performance.

Optimal alarms systems and its application to financial time series

This thesis focuses on the application of optimal alarm systems to non linear time series models. The most common classes of models in the analysis of real-valued and integer-valued time series are described. The construction of optimal alarm systems is covered and its applications explored. Considering models with conditional heteroscedasticity, particular attention is given to the Fractionally Integrated Asymmetric Power ARCH, FIAPARCH(p; d; q) model and an optimal alarm system is implemented, following both classical and Bayesian methodologies. Taking into consideration the particular characteristics of the APARCH(p; q) representation for financial time series, the introduction of a possible counterpart for modelling time series of counts is proposed: the INteger-valued Asymmetric Power ARCH, INAPARCH(p; q). The probabilistic properties of the INAPARCH(1; 1) model are comprehensively studied, the conditional maximum likelihood (ML) estimation method is applied and the asymptotic properties of the conditional ML estimator are obtained. The final part of the work consists on the implementation of an optimal alarm system to the INAPARCH(1; 1) model. An application is presented to real data series.