Coexisting Parallelogram Method to Handle Jump Point on Hough Transform-based Clock Skew Measurement

In this paper, we improve the robustness of the Hough transform-based clock skew measurement on the occurrence of a jump point. The current Hough transform-based skew method uses angle (θ), thickness (ω), and region (β), to create a parallelogram that covers the densest part of an offset-set. However, the assumption that all offsets are considered to line up roughly in only one direction restricts the ability of the current method when handling an offset-set in which its densest part is located separately, the jump point condition. By acquiring the parallelogram from coexisting angle-region tuples at the beginning and the ending parts of the offset-set, we completed the ability of the Hough transform-based method to handle the jump point. When handling the jump point problem, the proposed coexisting parallelogram method could reach 0.35 ppm accuracy compared with tens ppm by the current methods

A framework for evaluating countermeasures against sybil attacks in wireless sensor networks

Although Wireless Sensor Networks (WSNs) have found a niche in numerous applications, they are constrained by numerous factors. One of these important factors is security in WSNs. There are various types of security attacks that WSNs are susceptible to. The focus of this study is centred on Sybil attacks, a denial of service attack. In this type of attack, rogue nodes impersonate valid nodes by falsely claiming to possess authentic identities, thereby rendering numerous core WSN operations ineffective. The diverse nature of existing solutions poses a difficult problem for system engineers wanting to employ a best fit countermeasure. This problem is the largely unanswered question posed to all system engineers and developers alike whose goal is to design/develop a secure WSN. Resolving this dilemma proves to be quite a fascinating task, since there are numerous factors to consider and more especially one cannot assume that every application is affected by all identified factors. A framework methodology presented in this study addresses the abovementioned challenges by evaluating countermeasure effectiveness based on theoretical and practical security factors. Furthermore, a process is outlined to determine the application’s engineering requirements and the framework also suggests what security components the system engineer ought to incorporate into the application, depending on the application’s risk profile. The framework then numerically aligns these considerations, ensuring an accurate and fairly unbiased best fit countermeasure selection. Although the framework concentrates on Sybil countermeasures, the methodology can be applied to other classes of countermeasures since it answers the question of how to objectively study and compare security mechanisms that are both diverse and intended for different application environments. The report documents the design and development of a comparative framework that can be used to evaluate countermeasures against Sybil attacks in wireless sensor networks based on various criteria that will be discussed in detail. This report looks briefly at the aims and description of the research. Following this, a literature survey on the body of knowledge concerning WSN security and a discussion on the proposed methodology of a specific design approach are given. Assumptions and a short list of factors that were considered are then described. Metrics, the taxonomy for WSN countermeasures, the framework and a formal model are developed. Risk analysis and the best fit methodology are also discussed. Finally, the results and recommendations are shown for the research, after which the document is concluded.Dissertation (MEng)--University of Pretoria, 2011.Electrical, Electronic and Computer Engineeringunrestricte

Monitoring, Modeling, and Hybrid Simulation An Integrated Bayesian-based Approach to High-fidelity Fragility Analysis

Fragility functions are one of the key technical ingredients in seismic risk assessment. The derivation of fragility functions has been extensively studied in the past; however, large uncertainties still exist, mainly due to limited collaboration between the interdependent components involved in the course of fragility estimation. This research aims to develop a systematic Bayesian-based framework to estimate high-fidelity fragility functions by integrating monitoring, modeling, and hybrid simulation, with the final goal of improving the accuracy of seismic risk assessment to support both pre- and post-disaster decision-making. In particular, this research addresses the following five aspects of the problem: (1) monitoring with wireless smart sensor networks to facilitate efficient and accurate pre- and post-disaster data collection, (2) new modeling techniques including innovative system identification strategies and model updating to enable accurate structural modeling, (3) hybrid simulation as an advanced numerical experimental simulation tool to generate highly realistic and accurate response data for structures subject to earthquakes, (4) Bayesian-updating as a systematic way of incorporating hybrid simulation data to generate composite fragility functions with higher fidelity, and 5) the implementation of an integrated fragility analysis approach as a part of a seismic risk assessment framework. This research not only delivers an extensible and scalable framework for high fidelity fragility analysis and reliable seismic risk assessment, but also provides advances in wireless smart sensor networks, system identification, and pseudo-dynamic testing in civil engineering applications.Financial support for this research was provided in part by the National Science Foundation under NSF Grants No. CMS-060043, CMMI-0724172, CMMI-0928886, and CNS-1035573.Ope

Untersuchung von ausbringungspezifischer Simulation zur Optimierung drahtloser Sensornetzwerke

This theses researches whether it is possible to map existing deployments to a simulator accurately enough to use simulation to optimize for this specific deployment. For this purpose DrySim was developed as an approach to achieve more realistic simulation of Wireless Sensor Networks (WSNs). DrySim has two components, RealSim and DryRun: RealSim traces the network connectivity of a deployed WSN and allows replaying it in a simulator, whereas DryRun supports exploring a configuration space by running simulations and extracting and preparing data for further analysis. Two different test beds located in office environments were used to evaluate and verify the approach. Measurements in the two test beds showed that they required different configuration options. This was reflected in simulation as well as trial results. The evaluation presents a solid data basis for three scenarios, with a total of 1320 test bed and 8800 simulation runs between 5 and 20 minutes. During the evaluation care was taken to avoid systematic or probe effects. Analysis of the test beds also revealed that the default settings of ContikiOS, a popular WSN operating system, are unsuitable for most WSN deployments. The theses also features an analysis of the impact of different components on a WSN node. Specifically it was evaluated how accurately they can and must be simulated to achieve realistic results. These studies revealed two important points: Firstly the micro controller must be emulated to achieve real time accuracy. Secondly the radio characteristics of a network cannot be predicted and thus must be measured in the final deployment. In previous work, only specific aspects of simulating WSNs were researched. The research done in the context of DrySim, however, shows that to achieve realistic WSN simulation the main components, which are software, micro controller and radio chip and the radio network, must not be treated separately. With DrySim a solution is presented that allows for realistic enough simulation to tune configuration parameters to a specific deployment, while keeping the effort of tweaking the simulation model at a minimum.Diese Arbeit untersucht, ob es möglich ist bestehendes Sensornetzwerk in einem Simulator abzubilden, so dass dieses auf im Simulator ausbringungspezifisch optimiert werden kann. Hierzu wurde DrySim entwickelt. Ein Ansatz um eine realistischere Simulation von drahtlosen Sensornetzwerken (WSN) zu erzielen. DrySim besteht aus zwei Komponenten, RealSim und DryRun: RealSim zeichnet die Netzwerkkonnektivität eines ausgebrachten WSN auf und kann diese im einem Simulator wiedergeben. DryRun hingeben kann durch die Ausführung von Simulationen einen Konfigurationsraum erkunden und die gewonnenen Daten aufbereiten. Der Ansatz wurde in zwei Testnetzwerke, die in Büroräumen ausgebracht waren evaluiert. Die Messungen in den beiden Netzwerken haben gezeigt, dass sie unterschiedliche Konfigurationen benötigen, was sich auch in den Simulationen widergespiegelt hat. Die Evaluation präsentiert eine solide Datenbasis für drei Szenarien, mit 1320 Versuchen auf den Testnetzwerken und 8800 Simulationen zwischen 5 und 20 Minuten. Es wurde darauf geachtet den Einfluss durch systematische Fehler und die Beobachtung zu vermeiden. Die Untersuchung hat auch gezeigt, dass die Standardeinstellungen von ContikiOS, eines verbreiteten WSN-Betriebssystems für die meisten Umgebungen ungeeignet sind. Die Arbeit analysiert auch den Einfluss der verschiedenen Komponenten auf einen WSN-Knoten. Insbesondere wurde untersucht, wie akkurat diese simuliert werden können und müssen um realistische Simulationsergebnisse zu erzielen. Hierbei wurden zwei wichtige Punkte herausgearbeitet: Erstens muss der Mikrocontroller emuliert werden, um Echtzeitgenauigkeit zu erreichen. Zweitens können die Funkcharakteristiken eines Netzwerks nicht vorhergesagt werden und müssen daher vermessen werden. Vorhergehenden Arbeiten haben sich meist auf spezifische Aspekte der Simulation von Sensornetzwerken konzentriert. Die in Kontext von DrySim betriebene Forschung zeigt jedoch, dass realistische Simulationsergebnisse nur erreicht werden können, wenn die Hauptkomponenten, Software, Mikrocontroller, Radio-Chip und Funknetzwerk nicht getrennt betrachtet werden. Mit DrySim wird eine Lösung präsentiert, die es erlaubt bestehende Netzwerke so akkurat zu simulieren, dass man die Konfigurationsparameter auf dieses spezifische Netzwerk anpassen kann. Dabei bleibt der Konfigurationsaufwand bei einem Minimum