A novel non-intrusive objective method to predict voice quality of service in LTE networks.

This research aimed to introduce a novel approach for non-intrusive objective measurement of voice Quality of Service (QoS) in LTE networks. While achieving this aim, the thesis established a thorough knowledge of how voice traffic is handled in LTE networks, the LTE network architecture and its similarities and differences to its predecessors and traditional ground IP networks and most importantly those QoS affecting parameters which are exclusive to LTE environments. Mean Opinion Score (MOS) is the scoring system used to measure the QoS of voice traffic which can be measured subjectively (as originally intended). Subjective QoS measurement methods are costly and time-consuming, therefore, objective methods such as Perceptual Evaluation of Speech Quality (PESQ) were developed to address these limitations. These objective methods have a high correlation with subjective MOS scores. However, they either require individual calculation of many network parameters or have an intrusive nature that requires access to both the reference signal and the degraded signal for comparison by software. Therefore, the current objective methods are not suitable for application in real-time measurement and prediction scenarios. A major contribution of the research was identifying LTE-specific QoS affecting parameters. There is no previous work that combines these parameters to assess their impacts on QoS. The experiment was configured in a hardware in the loop environment. This configuration could serve as a platform for future research which requires simulation of voice traffic in LTE environments. The key contribution of this research is a novel non-intrusive objective method for QoS measurement and prediction using neural networks. A comparative analysis is presented that examines the performance of four neural network algorithms for non-intrusive measurement and prediction of voice quality over LTE networks. In conclusion, the Bayesian Regularization algorithm with 4 neurons in the hidden layer and sigmoid symmetric transfer function was identified as the best solution with a Mean Square Error (MSE) rate of 0.001 and regression value of 0.998 measured for the testing data set

Mitigating External Threats in Wireless Local Area Networks

As computer networks become more critical to enterprises, it is inevitable that efficient security policies are designed, case in point: wireless networks, in order to effectively ensure the confidentiality, availability, and integrity of the data traversing these networks. The primary objective of this paper is to appropriately simulate an enterprise network, and evaluate the threats, and possible mitigation approaches applicable. An analysis of an enterprise WLAN (Wireless Local Area Network) was carried out, to identify relevant vulnerabilities, and possible countermeasures against these threats. The primary threats analysed were those possible by an external adversary. Upon identification of said threats, a security model was developed, so as to improve enterprise network security, and ensure the levels are optimum. In addition, a number of the principles involved are applicable to non-wireless networks.   Keywords: WLAN, Wireless, Security, WPA 2, IEEE 802.11. 

Search and rescue operation in flooded areas: A survey on emerging sensor networking-enabled IoT-oriented technologies and applications

The climate and weather dynamics in the past few years has driven a massive increase in the number and intensity of flood disasters, which severely claim casualties in human, goods and properties. Aimed to reduce these casualties, emerging software-defined internet protocol-based communication technologies in the form of Internet of Things (IoT) have attracted strong interests from disaster mitigation stakeholders to rapidly locate victims and acquire their relevant information, which in turn can boost up the efficiency and effectiveness of Search and Rescue (SAR) missions. In order to capture state-of-the-art development and technological challenges, this paper presents an extensive review on the flood SAR systems, highlighting some of the key emerging IoT technologies that prove or are potentially useful in improving the SAR operation by the rescuers. Furthermore, a comprehensive study on different existing communication technologies for SAR is provided, covering the system architecture, communication network compositions and applications. Based on the critical analysis of existing works, this paper puts forward a proposal on an IoT-aided integrated flood management framework to support SAR in the flood-catchment areas, leveraging upon three-domain (ground, water and air) collaborative wireless networks