Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2006. / Nolan Hertel, Committee Chair ; John Aarsvold, Committee Co-Chair ; Rebecca Howell, Committee Member.

Undergraduate honors paper--Mount Holyoke College, 2007. Dept. of Biological Sciences. / Includes bibliographical references (leaves 69-70).

Vehicular ad hoc networks (VANETs) facilitate vehicles to broadcast beacon messages to ensure road safety. The rogue nodes in VANETs broadcast malicious information leading to potential hazards, including the collision of vehicles. Previous researchers used either cryptography, trust values, or past vehicle data to detect rogue nodes, but they suffer from high processing delay, overhead, and false-positive rate (FPR). We propose fog-based rogue nodes detection (F-RouND), a fog computing scheme, which dynamically creates a fog utilizing the on-board units (OBUs) of all vehicles in the region for rogue nodes detection. The novelty of F-RouND lies in providing low processing delays and FPR at high vehicle densities. The performance of our F-RouND framework was carried out with simulations using OMNET ++ and SUMO simulators. Results show that F-RouND ensures 45% lower processing delays, 12% lower overhead, and 36% lower FPR at high vehicle densities compared to existing rogue nodes detection schemes.

Wireless sensor networks are composed of sensor nodes, which can monitor an environment and observe events of interest. These networks are applied in various fields including but not limited to environmental, industrial and habitat monitoring. In many applications, the exact location of the sensor nodes is unknown after deployment. Localization is a process used to find sensor node's positional coordinates, which is vital information. The localization is generally assisted by anchor nodes that are also sensor nodes but with known locations. Anchor nodes generally are expensive and need to be optimally placed for effective localization. Passive localization is one of the localization techniques where the sensor nodes silently listen to the global events like thunder sounds, seismic waves, lighting, etc. According to previous studies, the ideal location to place anchor nodes was on the perimeter of the sensor network. This may not be the case in passive localization, since the function of anchor nodes here is different than the anchor nodes used in other localization systems. I do extensive studies on positioning anchor nodes for effective localization. Several simulations are run in dense and sparse networks for proper positioning of anchor nodes. I show that, for effective passive localization, the optimal placement of the anchor nodes is at the center of the network in such a way that no three anchor nodes share linearity. The more the non-linearity, the better the localization. The localization for our network design proves better when I place anchor nodes at right angles.

Cette thèse s’inscrit dans la problématique générale de la caractérisation et de la classification des systèmes. Plus précisément, nos contributions s’orientent vers les applications robotiques et, plus particulièrement, vers la classification de manipulateurs. Les algorithmes et méthodologies proposés dans ce document s’appuient sur plusieurs théories mathématiques dont la théorie des singularités et l’Analyse par Intervalles, qui sont formalisés dans la première partie de cette Thèse.Classifier des systèmes induit deux objectifs que sont la formalisation des éléments communs aux systèmes dans la même classe ainsi que leur détection formelle et pratique. Ainsi, ce mémoire compile, pour chacun dans un chapitre dédié, nos contributions vis-à-vis de ces deux objectifs associés à la classification. Une méthodologie générale est proposée, afin de distinguer plusieurs sous ensembles singuliers caractéristiques et génériquement non vides. Cette méthodologie est illustrée pour des fonctions entre espaces de même dimension, allant de 1à 3. Chaque application met en lumière des propriétés différentes de la méthodologie générale proposée.Complémentairement, chacune de ces applications mène à la conception d’algorithmes, basé sur l’Analyse par Intervalles, mettant en œuvre cette méthodologie.Complémentairement à la détection de points d’intérêt,nous présentons une méthodologie générale pour définir un objet combinatoire codant le comportement d’une fonction. Cette méthodologie s’appuie sur la détection préalable d’ensembles d’intérêt dont les topologies sont invariantes pour l’équivalence choisie. Ces développements ouvrent vers de nombreuses perspectives futures qui concluent ce mémoire. / This thesis is within the scope of the general problematic of characterizing and classifying systems. More precisely, our contributions are aimed toward robotic applications and, more particularly, at the classification of manipulators. The algorithms and methodologies proposed in this document are based upon several mathematical theories including Singularity Theory and Interval Analysis, which are formalized in the first part of this Phd Thesis report. Classifying systems induces two objectives that are the formalization of the elements commons to systems in the same class as well as their formal and practical detection. Then, this report compiles, for each one in a dedicated chapter, our contributions regarding these two objectives associated with the classification. A general methodology is proposed, with the objective to distinguish several characteristic singular subsets that prove to be generically not empty. This methodology is illustrated for functions between spaces of the same dimension, ranging from 1 to 3. Each application highlights different properties that are admitted by the proposed general methodology. Furthermore, each of these applications leads to the conception of severalalgorithms, based on Interval Analysis, that enforce the proposed methodology. Complementarily to the detection of interest points, we introduce a general methodology to define a combinatorial object encoding the behavior of a function. This methodology is based on the preliminary detection of interest sets whose topologies are invariant for the chosen equivalence. These developments open up to numerous future perspectives that conclude this report.

<p>The cyber-attacks have increased, and with everything going digital, data theft has become a significant issue. This raises an alarm on the security of the source code. Sometimes, to release products early, the security of the code is compromised. Static analysis tools can help in finding possible security issues. Identifying and fixing the security issues may overwhelm the software developers. This process of "fixing" the errors or securing the code may take a lot of time, and the product may be released before all the errors are fixed. But these vulnerabilities in the source code may cost millions of dollars in case of a data breach. It is important to fix the security issues in the source code before releasing the product. This leads to the question of how to fix errors quickly so products can be rolled out with fewer security issues? A possible solution is to use temporal networks to find the influencer nodes in the source code. If these influencer variables are fixed, the connected security issues depending on the influencer in the community (functions) will also get fixed. The research question of the study: Can we identify the influencer node of the buggy site in the source code using temporal networks (K-tool) if the buggy sites present in the source code are identified using static analysis? The study also aims to know if it is faster to find the influencer node using the K-tool than the betweenness centrality algorithm. This research is an "Applied research" and will target the code written in C programming language. Possible vulnerabilities that can be fixed include "Integer Overflow", "Out of bounds", and "Buffer overflow." In the future, we plan to extend to other errors such as "Improper input validation." In this research, we will discuss how we can find the influencer node of the vulnerability (buggy site) in the source code after running the static analysis. Fixing this influencer node will fix the remaining errors pointed out by the static analysis. This will help in reducing the number of fixes to be done in the source code so that the product can be rolled out faster with less security issues.</p> <p><br></p>

Energy harvesting (EH) nodes, which harvest energy from the environment in order to communicate over a wireless link, promise perpetual operation of wireless networks. The primary focus of the communication system design shifts from being as energy conservative as possible to judiciously handling the randomness in the energy harvesting process in order to enhance the system performance. This engenders a significant redesign of the physical and multiple access layers of communication. In this thesis, we address the problem of maximizing the throughput of a system that consists of rate-adaptive EH nodes that transmit data to a common sink node. We consider the practical case of discrete rate adaptation in which a node selects its transmission power from a set of finitely many rates and adjusts its transmit power to meet a bit error rate (BER) constraint. When there is only one EH node in the network, the problem involves determining the rate and power at which the node should transmit as a function of its channel gain and battery state. For the system with multiple EH nodes, which node should be selected also needs to be determined. We first prove that the energy neutrality constraint, which governs the operation of an EH node, is tighter than the average power constraint. We then propose a simple rate and power adaptation scheme for a system with a single EH node and prove that its throughput approaches the optimal throughput arbitrarily closely. We then arrive at the optimal selection and rate adaptation rules for a multi-EH node system that opportunistically selects at most one node to transmit at any time. The optimal scheme is shown to significantly outperform other ad hoc selection and transmission schemes. The effect of energy overheads, such as battery storage inefficiencies and the energy required for sensing and processing, on the transmission scheme and its overall throughput is also analytically characterized. Further, we show how the time and energy overheads incurred by the opportunistic selection process itself affect the adaptation and selection rules and the overall system throughput. Insights into the scaling behavior of the average system throughput in the asymptotic regime, in which the number of nodes tend to infinity, are also obtained. We also optimize the maximum time allotted for selection, so as to maximize the overall system throughput. For systems with EH nodes or non-EH nodes, which are subject to an average power constraint, the optimal rate and power adaptation depends on a power control parameter, which hitherto has been calculated numerically. We derive novel asymptotically tight bounds and approximations for the same, when the average rate of energy harvesting is large. These new expressions are analytically insightful, computationally useful, and are also quite accurate even in the non-asymptotic regime when average rate of energy harvesting is relatively small. In summary, this work develops several useful insights into the design of selection and transmission schemes for a wireless network with rate-adaptive EH nodes.

ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California / This paper presents a method for managing a Mixed Network with multiple ground stations and Test Articles (TA) preferences. The main difference between a Ground Station (cellular) network and the over the horizon (ad-hoc) network is that the ad-hoc method has no fixed infrastructure. This paper presents the computation and performance of a clustering technique for mobile nodes within the simulated mixed network environment with multiple ground stations and users preferences for those ground stations. This includes organization for multiple ground stations and for TA's gravitating toward a ground station of their choice on the basis of service and performance.

BACKGROUND:The aim of the study is to assess the effectiveness of intensity-modulated radiotherapy (IMRT) or image-guided radiotherapy (IGRT) for the prevention of retropharyngeal nodal recurrences in locally advanced head and neck cancer.METHODS:A retrospective review of 76 patients with head and neck cancer undergoing concurrent chemoradiation or postoperative radiotherapy with IMRT or IGRT who were at risk for retropharyngeal nodal recurrences because of anatomic site (hypopharynx, nasopharynx, oropharynx) and/or the presence of nodal metastases was undertaken.The prevalence of retropharyngeal nodal recurrences was assessed on follow-up positron emission tomography (PET)-CT scans.RESULTS:At a median follow-up of 22months (4-53months), no patient developed retropharyngeal nodal recurrences.CONCLUSION:Prophylactic irradiation of retropharyngeal lymph nodes with IMRT or IGRT provides effective regional control for individuals at risk for recurrence in these nodes.

In Mobile Ad Hoc Networks (MANETs), nodes depend on each other for routing and forwarding packets. However, to save power and other resources, nodes belonging to independent authorities may behave selfishly, and may not be willing to help other nodes. Such selfish behavior poses a real threat to the proper functioning of MANETs. One way to foster node cooperation is to introduce punishment for selfish nodes. Based on neighbor-monitoring techniques, a fully distributed solution to detect, punish, and re-admit selfish nodes, is proposed here. This solution provides nodes the same opportunity to serve/and be served by others. A light-weight solution regarding battery status is also proposed here. This solution requires neighbor monitoring only when necessary, thereby saving nodes battery power. Another effective way to solve the selfish-node problem is to reward nodes for their service according to their cost. To force nodes to show their true cost, truthful protocols are needed. A low overhead truthful routing protocol to find optimal routes is proposed in this thesis. The most prominent feature of this protocol is the reduction of overhead from existing solutions O(n3) to O(n2). A light-weight scalable truthful routing protocol (LSTOP) is further proposed, which finds near-least-cost paths in dense networks. LSTOP reduces overhead to O(n) on average, and O(n2) in worst case scenarios. Multiple path routing protocols are an effective alternative to single path routing protocols. A generic mechanism that can turn any table-driven multipath routing protocol into a truthful one, is outlined here. A truthful multipath routing protocol (TMRP), based on well-known AOMDV protocol, is presented as an example. TMRP incurs an only 2n message overhead for a route discovery, and can also achieve load balancing without compromising truthfulness. To cope with the selfish-node problem in the area of position-based routing, a truthful geographic forwarding (TGF) algorithm is presented. TGF utilizes three auction-based forwarding schemes to stimulate node cooperation. The truthfulness of these schemes is proven, and their performance is evaluated through statistical analysis and simulation studies.