The Contributory Effect of Latency on the Quality of Voice Transmitted over the Internet

Deployment of Voice over Internet Protocol (VoIP) is rapidly growing worldwide due to the new services it provides and cost savings derived from using a converged IP network. However, voice quality is affected by bandwidth, delay, latency, jitter, packet loss e.t.c. Latency is the dominant factor that degrades quality of voice transfer. There is therefore strong need for a study on the effect of Latency with the view to improving Quality of Voice (QoV) in VoIP network. In this work, Poisson probability theorem, Markov Chain, Probability distribution theorems and Network performance metric were used to study the effect of latency on QoS in VoIP network. This is achieved by considering the effect of latency resulting from several components between two points in multiple networks. The NetQoS Latency Calculator, Net-Cracker Professional® for Modeling and Matlab/Simulink® for simulating network were tools used and the results obtained compare favourably well with theoretical facts

Developed Model to Control Congestion on Converge Network

Congestion control techniques like Active Queue Management (AQM), Carrier Sense Multiple Access/Carrier Detection (CSMA/CD) have not proven to be very efficient in the presence of overwhelming complex converge network. Thus, vast packets in a complex converged network leads to collisions, network degradation and high degree of packet loss. Bandwidth utilization factor has a high effect on the network such that controlling the level of utilization via the management of the number of users and the amount of packets on the network rendered the latency very insignificant. As a consequence of this, high throughput and very minimal packet loss was achieved in the experiment. This was confirmed analytically by varying the utilization factor between 40% and 90% while keeping other parameters in the experiment constan

Small Resolution Proofs for QBF using Dependency Treewidth

In spite of the close connection between the evaluation of quantified Boolean formulas (QBF) and propositional satisfiability (SAT), tools and techniques which exploit structural properties of SAT instances are known to fail for QBF. This is especially true for the structural parameter treewidth, which has allowed the design of successful algorithms for SAT but cannot be straightforwardly applied to QBF since it does not take into account the interdependencies between quantified variables. In this work we introduce and develop dependency treewidth, a new structural parameter based on treewidth which allows the efficient solution of QBF instances. Dependency treewidth pushes the frontiers of tractability for QBF by overcoming the limitations of previously introduced variants of treewidth for QBF. We augment our results by developing algorithms for computing the decompositions that are required to use the parameter

Proceedings, MSVSCC 2017

Proceedings of the 11th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 20, 2017 at VMASC in Suffolk, Virginia. 211 pp

THREE ESSAYS ON OFFSHORING DECISION-MAKING

This thesis studies biases in offshoring decisions and proposes a tool to improve understanding of the value of lead-time. Recent research results show local responsive production reduces mismatch between supply and demand, but this aspect of the cost is often overlooked in offshoring decisions, leading to suboptimal decisions. The tradeoff between lower unit costs and mismatch cost under demand uncertainty as lead-time increases, and the benefits of a local portfolio of products with different demand volatility, make the offshoring decision complex and the optimal solution sometimes counterintuitive. Building on behavioral research, I designed software-based laboratory trials to explore patterns of decisions in an offshoring problem, and a simulation-game to help teach and communicate research insights. In the first paper, I find that participants facing an offshoring problem fail to apply the economically optimal strategy. In the second paper, I find that non-economic factors like peer influence play a role in offshoring decisions. These trials are exploratory in nature and do not provide generalizable results, rather, they are a step towards a better understanding of the fundamental research questions and the conception of experiments. In the third paper, I describe the development and use of a simulation-game to help students, managers and policy makers understand the value of lead-time and volatility portfolio through an active learning approach. My work contributes to the understanding of the impact of bounded rationality in offshoring decisions and proposes a teaching method adapted to the challenges posed by the concepts involved