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Title: INTRUSION DETECTION IN WIRELESS SENSOR NETWORKS.
Creator: NGUYEN, HONG NHUNG, Turgut, Damla, University of Central Florida
Abstract / Description: There are several applications that use sensor motes and researchers continue to explore additional applications. For this particular application of detecting the movement of humans through the sensor field, a set of Berkley mica2 motes on TinyOS operating system is used. Different sensors such as pressure, light, and so on can be used to identify the presence of an intruder in the field. In our case, the light sensor is chosen for the detection. When an intruder crosses the monitored...
Show moreThere are several applications that use sensor motes and researchers continue to explore additional applications. For this particular application of detecting the movement of humans through the sensor field, a set of Berkley mica2 motes on TinyOS operating system is used. Different sensors such as pressure, light, and so on can be used to identify the presence of an intruder in the field. In our case, the light sensor is chosen for the detection. When an intruder crosses the monitored environment, the system detects the changes of the light values, and any significant change meaning that a change greater than a pre-defined threshold. This indicates the presence of an intruder. An integrated web cam is used to take snapshot of the intruder and transmit the picture through the network to a remote station. The basic motivation of this thesis is that a sensor web system can be used to monitor and detect any intruder in a specific area from a remote location.
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Date Issued: 2006
Identifier: CFE0001027, ucf:46793
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001027

Title: Leveraging the Intrinsic Switching Behaviors of Spintronic Devices for Digital and Neuromorphic Circuits.
Creator: Pyle, Steven, DeMara, Ronald, Vosoughi, Azadeh, Chanda, Debashis, University of Central Florida
Abstract / Description: With semiconductor technology scaling approaching atomic limits, novel approaches utilizing new memory and computation elements are sought in order to realize increased density, enhanced functionality, and new computational paradigms. Spintronic devices offer intriguing avenues to improve digital circuits by leveraging non-volatility to reduce static power dissipation and vertical integration for increased density. Novel hybrid spintronic-CMOS digital circuits are developed herein that...
Show moreWith semiconductor technology scaling approaching atomic limits, novel approaches utilizing new memory and computation elements are sought in order to realize increased density, enhanced functionality, and new computational paradigms. Spintronic devices offer intriguing avenues to improve digital circuits by leveraging non-volatility to reduce static power dissipation and vertical integration for increased density. Novel hybrid spintronic-CMOS digital circuits are developed herein that illustrate enhanced functionality at reduced static power consumption and area cost. The developed spin-CMOS D Flip-Flop offers improved power-gating strategies by achieving instant store/restore capabilities while using 10 fewer transistors than typical CMOS-only implementations. The spin-CMOS Muller C-Element developed herein improves asynchronous pipelines by reducing the area overhead while adding enhanced functionality such as instant data store/restore and delay-element-free bundled data asynchronous pipelines.Spintronic devices also provide improved scaling for neuromorphic circuits by enabling compact and low power neuron and non-volatile synapse implementations while enabling new neuromorphic paradigms leveraging the stochastic behavior of spintronic devices to realize stochastic spiking neurons, which are more akin to biological neurons and commensurate with theories from computational neuroscience and probabilistic learning rules. Spintronic-based Probabilistic Activation Function circuits are utilized herein to provide a compact and low-power neuron for Binarized Neural Networks. Two implementations of stochastic spiking neurons with alternative speed, power, and area benefits are realized. Finally, a comprehensive neuromorphic architecture comprising stochastic spiking neurons, low-precision synapses with Probabilistic Hebbian Plasticity, and a novel non-volatile homeostasis mechanism is realized for subthreshold ultra-low-power unsupervised learning with robustness to process variations. Along with several case studies, implications for future spintronic digital and neuromorphic circuits are presented.
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Date Issued: 2019
Identifier: CFE0007514, ucf:52658
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007514

Title: MODELS TO ESTIMATE ARRIVAL COUNTS AND STAFFING REQUIREMENTS IN NONSTATIONARY QUEUEING SYSTEMS APPLIED TO LONG DISTANCE ROAD RACES.
Creator: Fairweather, Lindon, Reilly, Charles, University of Central Florida
Abstract / Description: We examine the problem of staffing refreshment stations at a long distance road race. A race is modeled as a mixed queueing network in which the required number of servers at each service station has to be estimated. Two models to represent the progress of runners along a long distance road race course are developed. One model is a single-class model that allows a road race manager to staff service stations assuming the runners are identical to those in some historical dataset. Another model...
Show moreWe examine the problem of staffing refreshment stations at a long distance road race. A race is modeled as a mixed queueing network in which the required number of servers at each service station has to be estimated. Two models to represent the progress of runners along a long distance road race course are developed. One model is a single-class model that allows a road race manager to staff service stations assuming the runners are identical to those in some historical dataset. Another model is a multi-class simulation model that allows a road race manager to simulate a race of any number of runners, classified based on their running pace into different runner classes. Both the single-class model and the multi-class model include estimates for the rates at which the runners arrive at specified locations along the course. The arrival rates, combined with assumed service rates, allow us to base staffing decisions on the Erlang loss formula or a lesser known staffing rule that gives a lower bound for the required number of servers. We develop a staffing strategy that we call the Peak Arrival Staffing Bound (PASB), which is based on this staffing bound. The PASB and the Erlang loss formula are implemented in the single-class model and the multi-class simulation model. By way of numerical experiments, we find that the PASB is numerically stable and can be used to get staffing results regardless of the traffic intensity. This finding is in contrast to the Erlang loss formula, which is known to become numerically unstable and overflows when the traffic intensity exceeds 171. We compare numerical results of the PASB and the Erlang loss formula with a blocking probability level of 5% and find that when the traffic intensity is high, staffing results based on the PASB are more conservative than staffing results based on the Erlang loss formula. As the traffic intensity gets lower, we find that staffing results based on the PASB are similar to staffing results based on the Erlang loss formula. These findings suggest that the PASB can be a valuable tool to aid race directors in making staffing decisions for races of all traffic intensities.
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Date Issued: 2011
Identifier: CFE0004055, ucf:49154
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004055

Title: A SELF-ORGANIZING HYBRID SENSOR SYSTEM WITH DISTRIBUTED DATA FUSION FOR INTRUDER TRACKING AND SURVEILLANCE.
Creator: Palaniappan, Ravishankar, Wahid, Parveen, University of Central Florida
Abstract / Description: A wireless sensor network is a network of distributed nodes each equipped with its own sensors, computational resources and transceivers. These sensors are designed to be able to sense specific phenomenon over a large geographic area and communicate this information to the user. Most sensor networks are designed to be stand-alone systems that can operate without user intervention for long periods of time. While the use of wireless sensor networks have been demonstrated in various military and...
Show moreA wireless sensor network is a network of distributed nodes each equipped with its own sensors, computational resources and transceivers. These sensors are designed to be able to sense specific phenomenon over a large geographic area and communicate this information to the user. Most sensor networks are designed to be stand-alone systems that can operate without user intervention for long periods of time. While the use of wireless sensor networks have been demonstrated in various military and commercial applications, their full potential has not been realized primarily due to the lack of efficient methods to self organize and cover the entire area of interest. Techniques currently available focus solely on homogeneous wireless sensor networks either in terms of static networks or mobile networks and suffers from device specific inadequacies such as lack of coverage, power and fault tolerance. Failing nodes result in coverage loss and breakage in communication connectivity and hence there is a pressing need for a fault tolerant system to allow replacing of the failed nodes. In this dissertation, a unique hybrid sensor network is demonstrated that includes a host of mobile sensor platforms. It is shown that the coverage area of the static sensor network can be improved by self-organizing the mobile sensor platforms to allow interaction with the static sensor nodes and thereby increase the coverage area. The performance of the hybrid sensor network is analyzed for a set of N mobile sensors to determine and optimize parameters such as the position of the mobile nodes for maximum coverage of the sensing area without loss of signal between the mobile sensors, static nodes and the central control station. A novel approach to tracking dynamic targets is also presented. Unlike other tracking methods that are based on computationally complex methods, the strategy adopted in this work is based on a computationally simple but effective technique of received signal strength indicator measurements. The algorithms developed in this dissertation are based on a number of reasonable assumptions that are easily verified in a densely distributed sensor network and require simple computations that efficiently tracks the target in the sensor field. False alarm rate, probability of detection and latency are computed and compared with other published techniques. The performance analysis of the tracking system is done on an experimental testbed and also through simulation and the improvement in accuracy over other methods is demonstrated.
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Date Issued: 2010
Identifier: CFE0003024, ucf:48347
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0003024

Title: A ROBUST WIRELESS MESH ACCESS ENVIRONMENT FOR MOBILE VIDEO USERS.
Creator: Xie, Fei, Hua, Kien, University of Central Florida
Abstract / Description: The rapid advances in networking technology have enabled large-scale deployments of online video streaming services in todayÃ‚Â's Internet. In particular, wireless Internet access technology has been one of the most transforming and empowering technologies in recent years. We have witnessed a dramatic increase in the number of mobile users who access online video services through wireless access networks, such as wireless mesh networks and 3G cellular networks. Unlike in...
Show moreThe rapid advances in networking technology have enabled large-scale deployments of online video streaming services in todayÃ‚Â's Internet. In particular, wireless Internet access technology has been one of the most transforming and empowering technologies in recent years. We have witnessed a dramatic increase in the number of mobile users who access online video services through wireless access networks, such as wireless mesh networks and 3G cellular networks. Unlike in wired environment, using a dedicated stream for each video service request is very expensive for wireless networks. This simple strategy also has limited scalability when popular content is demanded by a large number of users. It is desirable to have a robust wireless access environment that can sustain a sudden spurt of interest for certain videos due to, say a current event. Moreover, due to the mobility of the video users, smooth streaming performance during the handoff is a key requirement to the robustness of the wireless access networks for mobile video users.　In this dissertation, the author focuses on the robustness of the wireless mesh access (WMA) environment for mobile video users. Novel video sharing techniques are proposed to reduce the burden of video streaming in different WMA environments. The author proposes a cross-layer framework for scalable Video-on-Demand (VOD) service in multi-hop WiMax mesh networks. The author also studies the optimization problems for video multicast in a general wireless mesh networks. The WMA environment is modeled as a connected graph with a video source in one of the nodes and the video requests randomly generated from other nodes in the graph. The optimal video multicast problem in such environment is formulated as two sub-problems. The proposed solutions of the sub-problems are justified using simulation and numerical study. In the case of online video streaming, online video server does not cooperate with the access networks. In this case, the centralized data sharing technique fails since they assume the cooperation between the video server and the network. To tackle this problem, a novel distributed video sharing technique called Dynamic Stream Merging (DSM) is proposed. DSM improves the robustness of the WMA environment without the cooperation from the online video server. It optimizes the per link sharing performance with small time complexity and message complexity. The performance of DSM has been studied using simulations in Network Simulator 2 (NS2) as well as real experiments in a wireless mesh testbed. The Mobile YouTube website (http://m.youtube.com) is used as the online video website in the experiment. Last but not the least; a cross-layer scheme is proposed to avoid the degradation on the video quality during the handoff in the WMA environment. Novel video quality related triggers and the routing metrics at the mesh routers are utilized in the handoff decision making process. A redirection scheme is also proposed to eliminate packet loss caused by the handoff.
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Date Issued: 2010
Identifier: CFE0003241, ucf:48541
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0003241

Title: Opportunistic Networks in Campus Environments.
Creator: Bacanli, Salih Safa, Turgut, Damla, Guha, Ratan, Bassiouni, Mostafa, University of Central Florida
Abstract / Description: Opportunistic communication is an active research area in wireless sensor networks. Exploiting the opportunities to communicate between devices in an unstable network is one of the main challenges of the opportunistic communication. In this thesis, we propose an infrastructure-independent opportunistic mobile social networking strategy for efficient message broadcasting in campus environments. Specifically, we focus on the application scenario of university campuses. In our model, the...
Show moreOpportunistic communication is an active research area in wireless sensor networks. Exploiting the opportunities to communicate between devices in an unstable network is one of the main challenges of the opportunistic communication. In this thesis, we propose an infrastructure-independent opportunistic mobile social networking strategy for efficient message broadcasting in campus environments. Specifically, we focus on the application scenario of university campuses. In our model, the students' smartphones forward messages to each other. The messages are created spontaneously as independent events in various places of the campus. The events can be either urgent security alerts or private announcements to the students who are currently on the campus. Our proposed state-based campus routing (SCR) protocol is based on the idle and active states of the students in indoor and outdoor environments. The proposed model is analyzed through extensive network simulations using mobility datasets collected from students on University of Milano, University of Cambridge and University of St Andrews campuses. The opportunistic network model and the SCR protocol is compared with epidemic, epidemic with TTS (Times-To-Send), PROPHET(Probabilistic Routing on History of Encounters), NDAO (Nodes Density Aware Opportunistic) and random routing protocols. We observe that the message delivery performance of SCR is close to Epidemic, PROPHET and NDAO while SCR reduces the amount of message transmissions.
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Date Issued: 2015
Identifier: CFE0006258, ucf:51038
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006258

Title: A HYBRID ROUTING PROTOCOL FOR COMMUNICATIONS AMONG NODES WITHHIGH RELATIVE SPEED IN WIRELESS MESH NETWORKS.
Creator: PEPPAS, NIKOLAOS, Turgut, Damla, University of Central Florida
Abstract / Description: Wireless mesh networks (WMN) is a new promising wireless technology which uses already available hardware and software components. This thesis proposes a routing algorithm for military applications. More specifically, a specialized scenario consisting of a network of flying Unmanned Aerial Vehicles (UAVs) executing reconnaissance missions is investigated. The proposed routing algorithm is hybrid in nature and uses both reactive and proactive routing characteristics to transmit information....
Show moreWireless mesh networks (WMN) is a new promising wireless technology which uses already available hardware and software components. This thesis proposes a routing algorithm for military applications. More specifically, a specialized scenario consisting of a network of flying Unmanned Aerial Vehicles (UAVs) executing reconnaissance missions is investigated. The proposed routing algorithm is hybrid in nature and uses both reactive and proactive routing characteristics to transmit information. Through simulations run on a specially built stand alone simulator, based on Java, packet overhead, delivery ratio and latency metrics were monitored with respect to varying number of nodes, node density and mobility. The results showed that the high overhead leads to high delivery ratio while latency tends to increase as the network grows larger. All the metrics revealed sensitivity in high mobility conditions.
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Date Issued: 2007
Identifier: CFE0001607, ucf:47165
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001607

Title: Rethinking Routing and Peering in the era of Vertical Integration of Network Functions.
Creator: Dey, Prasun, Yuksel, Murat, Wang, Jun, Ewetz, Rickard, Zhang, Wei, Hasan, Samiul, University of Central Florida
Abstract / Description: Content providers typically control the digital content consumption services and are getting the most revenue by implementing an (")all-you-can-eat(") model via subscription or hyper-targeted advertisements. Revamping the existing Internet architecture and design, a vertical integration where a content provider and access ISP will act as unibody in a sugarcane form seems to be the recent trend. As this vertical integration trend is emerging in the ISP market, it is questionable if existing...
Show moreContent providers typically control the digital content consumption services and are getting the most revenue by implementing an (")all-you-can-eat(") model via subscription or hyper-targeted advertisements. Revamping the existing Internet architecture and design, a vertical integration where a content provider and access ISP will act as unibody in a sugarcane form seems to be the recent trend. As this vertical integration trend is emerging in the ISP market, it is questionable if existing routing architecture will suffice in terms of sustainable economics, peering, and scalability. It is expected that the current routing will need careful modifications and smart innovations to ensure effective and reliable end-to-end packet delivery. This involves new feature developments for handling traffic with reduced latency to tackle routing scalability issues in a more secure way and to offer new services at cheaper costs. Considering the fact that prices of DRAM or TCAM in legacy routers are not necessarily decreasing at the desired pace, cloud computing can be a great solution to manage the increasing computation and memory complexity of routing functions in a centralized manner with optimized expenses. Focusing on the attributes associated with existing routing cost models and by exploring a hybrid approach to SDN, we also compare recent trends in cloud pricing (for both storage and service) to evaluate whether it would be economically beneficial to integrate cloud services with legacy routing for improved cost-efficiency. In terms of peering, using the US as a case study, we show the overlaps between access ISPs and content providers to explore the viability of a future in terms of peering between the new emerging content-dominated sugarcane ISPs and the healthiness of Internet economics. To this end, we introduce meta-peering, a term that encompasses automation efforts related to peering (-) from identifying a list of ISPs likely to peer, to injecting control-plane rules, to continuous monitoring and notifying any violation (-) one of the many outcroppings of vertical integration procedure which could be offered to the ISPs as a standalone service.
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Date Issued: 2019
Identifier: CFE0007797, ucf:52351
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007797

Title: Routing, Localization and Positioning Protocols for Wireless Sensor and Actor Networks.
Creator: Akbas, Mustafa, Turgut, Damla, Boloni, Ladislau, Georgiopoulos, Michael, Brust, Matthias, Bassiouni, Mostafa, Zhao, Yue, University of Central Florida
Abstract / Description: Wireless sensor and actor networks (WSANs) are distributed systems of sensor nodes and actors that are interconnected over the wireless medium. Sensor nodes collect information about the physical world and transmit the data to actors by using one-hop or multi-hop communications. Actors collect information from the sensor nodes, process the information, take decisions and react to the events.This dissertation presents contributions to the methods of routing, localization and positioning in...
Show moreWireless sensor and actor networks (WSANs) are distributed systems of sensor nodes and actors that are interconnected over the wireless medium. Sensor nodes collect information about the physical world and transmit the data to actors by using one-hop or multi-hop communications. Actors collect information from the sensor nodes, process the information, take decisions and react to the events.This dissertation presents contributions to the methods of routing, localization and positioning in WSANs for practical applications. We first propose a routing protocol with service differentiation for WSANs with stationary nodes. In this setting, we also adapt a sports ranking algorithm to dynamically prioritize the events in the environment depending on the collected data. We extend this routing protocol for an application, in which sensor nodes float in a river to gather observations and actors are deployed at accessible points on the coastline. We develop a method with locally acting adaptive overlay network formation to organize the network with actor areas and to collect data by using locality-preserving communication.We also present a multi-hop localization approach for enriching the information collected from the river with the estimated locations of mobile sensor nodes without using positioning adapters. As an extension to this application, we model the movements of sensor nodes by a subsurface meandering current mobility model with random surface motion. Then we adapt the introduced routing and network organization methods to model a complete primate monitoring system. A novel spatial cut-off preferential attachment model and center of mass concept are developed according to the characteristics of the primate groups. We also present a role determination algorithm for primates, which uses the collection of spatial-temporal relationships. We apply a similar approach to human social networks to tackle the problem of automatic generation and organization of social networks by analyzing and assessing interaction data. The introduced routing and localization protocols in this dissertation are also extended with a novel three dimensional actor positioning strategy inspired by the molecular geometry. Extensive simulations are conducted in OPNET simulation tool for the performance evaluation of the proposed protocols.
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Date Issued: 2013
Identifier: CFE0005292, ucf:50564
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005292

Title: CONNECTIONLESS APPROACH – A LOCALIZED SCHEME TO MOBILE AD HOC NETWORKS.
Creator: Ho, Yao, Hua, Kien, University of Central Florida
Abstract / Description: According to a Gartner Group (www.gartner.com) report in September 2008, the worldwide telecommunications market is on pace to reach $2 trillion in 2008. Gartner predicts that by 2012, the ratio of mobile to fixed connections will exceed 4-to-1. The North American mobile data market grew to 141.1 million connections in 2007, with a compound annual growth rate of 41.7 percent. It is believed that a large portion will be ad hoc and multi-hop connections, which will open many opportunities for...
Show moreAccording to a Gartner Group (www.gartner.com) report in September 2008, the worldwide telecommunications market is on pace to reach $2 trillion in 2008. Gartner predicts that by 2012, the ratio of mobile to fixed connections will exceed 4-to-1. The North American mobile data market grew to 141.1 million connections in 2007, with a compound annual growth rate of 41.7 percent. It is believed that a large portion will be ad hoc and multi-hop connections, which will open many opportunities for Mobile Ad hoc NETwork (MANET) applications and Wireless Mesh Network (WMN) applications. A MANET is a self-organizing multi-hop wireless network where all nodes participate in the routing and data forwarding process. Such a network can be easily deployed in situations where no base station is available, and a network must be build spontaneously. In applications such as battlefield communications, national crises, disaster recovery, and sensor deployment, a wired network is not available and ad hoc networks provide the only feasible means of communications and information access. Ad hoc networks have also become commonplace for gaming, conferencing, electronic classrooms, and particularly vehicle-to-vehicle communications. A Wireless mash network (WMN) is collection of mesh clients and mesh nodes (routers), with mesh nodes forming the backbone of the network and providing connection to the Internet and other network. Their rapid deployment and ease of maintenance are suitable for on-demand network such as disaster recovery, homeland security, convention centers, hard-to-wire buildings and unfriendly terrains. One important problem with MANET is the routing protocol that needs to work well not just with a small network, but also sustain efficiency and scalability as the network gets expanded and the application transmits data in greater volume. In such an environment, mobility, channel error, and congestion are the main causes for packet loss. Due to mobility of mobile hosts, addressing frequent and unpredictable topology changes is fundamental to MANET research. Two general approaches have been considered: connection-oriented approach and connectionless-oriented approach. In the former, the emphasis is on how to reconnect quickly with low overhead when a broken link occurs. Examples of this approach includes , , , , , , , , , and . In contrast, connectionless-oriented approach focuses on minimizing the occurrence of broken links. We proposed one such scheme called Connectionless Approach (CLA) and . In CLA, the network area is divided into non-overlapping grid cells, each serving as a virtual router. Any physical router (i.e., mobile host), currently inside a virtual router, can help forward the data packet to the next virtual router along the virtual link. This process is repeated until the packet reaches its final destination. Since a virtual link is based on virtual routers which do not move, it is much more robust than physical links used in the connection-oriented techniques. Simulation results in our previous works and , based on GloMoSim , indicate that CLA performs significantly better than connection-oriented techniques (i.e., AODV, DSR, LAR, GRID, TMNR, and GPSR). The contribution of this work consists of investigating and developing new Connectionless-Oriented Approach for Mobile Ad Hoc Network. Two of the greatest impacts of this research are as follows. First, the new approach is targeted towards robustly support high mobility and large scale environment which has been adapted for vehicle-to-vehicle environment in . Second, the detailed simulations which compare eight representative routing protocols, namely AODV, DSR, LAR, GRID, TMNR, GPSR, CBF, and CLA, under high-mobility environments. As many important emergent applications of the technology involved high-mobility nodes, very little is known about the existing routing methods perform relative to each other in high-mobility environments. The simulation results provide insight into ad hoc routing protocols and offer guidelines for mobile ad hoc network applications. Next, we enhanced and extend the connectionless-oriented approach. The current connectionless-oriented approach, however, may suffer from packet drops since traffic congestion is not considered in the packet forwarding policy. We address this weakness by considering the connectionless-oriented approach with a collision avoidance routing technique. After that, we investigate techniques to enforce collaboration among mobile devices in supporting the virtual router functionality. Many works have been published to combat such problem - misbehaving nodes are detected and a routing algorithm is employed to avoid and penalize misbehaving nodes. These techniques, however, cannot be applied to the connectionless-oriented approach since any node in the general direction towards the destination node can potentially help forward the data packets. To address the security and cooperation issues for connectionless-oriented approach, we introduce a cooperation enforcement technique called 3CE (3-Counter Enforcement). In addition, wireless mesh networks have become increasingly popular in recent years. Wireless mash network (WMNs) are collection of mesh clients and mesh nodes (routers), with mesh nodes forming the backbone of the network and providing connection to the Internet and other network. We propose a paradigm that combines virtual routers and mesh nodes to create a hybrid network call VR-Mesh Network. This hybrid network can reduce number of mesh node needed without decrease the performance of the network.
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Date Issued: 2009
Identifier: CFE0002742, ucf:48146
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002742

Title: Managing Effective Collaboration among Law Enforcement, Intelligence Services, and Military Forces in Fight against Terrorism and Organized Crime.
Creator: Demirhan, Cihan, Kapucu, Naim, Hu, Qian, Feldheim, Mary Ann, Rivera, Fernando, University of Central Florida
Abstract / Description: The fight against terrorism and organized crime require strong collaboration between public security organizations. Public security networks include several agencies that are not bound to each other with strong hierarchical ties. Because of a lack of the strong hierarchical structure, managing public networks is not similar to managing a single government agency. This study aims to examine the factors influencing network effectiveness in the public security sector. The main research questions...
Show moreThe fight against terrorism and organized crime require strong collaboration between public security organizations. Public security networks include several agencies that are not bound to each other with strong hierarchical ties. Because of a lack of the strong hierarchical structure, managing public networks is not similar to managing a single government agency. This study aims to examine the factors influencing network effectiveness in the public security sector. The main research questions of the study are: Which factors are important for effectiveness in public security networks? What is the role of inter-organizational trust among partner agencies? Which kind of leadership style will achieve the highest performance in public security networks? What is the relative importance of goal convergence and organizational culture in network effectiveness? How does the relationship between inter-organizational trust, leadership style, goal convergence and organizational culture impact network effectiveness? In order to find these relations, a self-reported survey was sent to 2,095 current and previous Turkish public security network managers. The study found that inter-organizational trust and goal convergence have a positive relationship with network effectiveness. Although facilitator leadership is found to be the most common leadership style in Turkish public security networks, it is found as inappropriate to achieve higher network effectiveness. According to the results, the co-producer network leadership is the most convenient leadership style in terms of network effectiveness. While the results of the descriptive statistics confirm that six specific features of organizational culture in public security sector have negative influence on network effectiveness, the hypothesis testing with the covariance structure model only support the negative impact of competition among partner organization. This study contributes to the literature on network effectiveness with particular proposals for the public security managers and practitioners.
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Date Issued: 2014
Identifier: CFE0005479, ucf:50350
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005479

Title: ATMOSPHERIC ENTRY.
Creator: Martin, Dillon A, Elgohary, Tarek, University of Central Florida
Abstract / Description: The development of atmospheric entry guidance methods is crucial to achieving the requirements for future missions to Mars; however, many missions implement a unique controller which are spacecraft specific. Here we look at the implementation of neural networks as a baseline controller that will work for a variety of different spacecraft. To accomplish this, a simulation is developed and validated with the Apollo controller. A feedforward neural network controller is then analyzed and...
Show moreThe development of atmospheric entry guidance methods is crucial to achieving the requirements for future missions to Mars; however, many missions implement a unique controller which are spacecraft specific. Here we look at the implementation of neural networks as a baseline controller that will work for a variety of different spacecraft. To accomplish this, a simulation is developed and validated with the Apollo controller. A feedforward neural network controller is then analyzed and compared to the Apollo case.
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Date Issued: 2017
Identifier: CFH2000354, ucf:45874
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFH2000354

Title: GAUSS-NEWTON BASED LEARNING FOR FULLY RECURRENT NEURAL NETWORKS.
Creator: Vartak, Aniket Arun, Georgiopoulos, Michael, University of Central Florida
Abstract / Description: The thesis discusses a novel off-line and on-line learning approach for Fully Recurrent Neural Networks (FRNNs). The most popular algorithm for training FRNNs, the Real Time Recurrent Learning (RTRL) algorithm, employs the gradient descent technique for finding the optimum weight vectors in the recurrent neural network. Within the framework of the research presented, a new off-line and on-line variation of RTRL is presented, that is based on the Gauss-Newton method. The method itself is an...
Show moreThe thesis discusses a novel off-line and on-line learning approach for Fully Recurrent Neural Networks (FRNNs). The most popular algorithm for training FRNNs, the Real Time Recurrent Learning (RTRL) algorithm, employs the gradient descent technique for finding the optimum weight vectors in the recurrent neural network. Within the framework of the research presented, a new off-line and on-line variation of RTRL is presented, that is based on the Gauss-Newton method. The method itself is an approximate Newton's method tailored to the specific optimization problem, (non-linear least squares), which aims to speed up the process of FRNN training. The new approach stands as a robust and effective compromise between the original gradient-based RTRL (low computational complexity, slow convergence) and Newton-based variants of RTRL (high computational complexity, fast convergence). By gathering information over time in order to form Gauss-Newton search vectors, the new learning algorithm, GN-RTRL, is capable of converging faster to a better quality solution than the original algorithm. Experimental results reflect these qualities of GN-RTRL, as well as the fact that GN-RTRL may have in practice lower computational cost in comparison, again, to the original RTRL.
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Date Issued: 2004
Identifier: CFE0000091, ucf:46065
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0000091

Title: DEVELOPMENT OF AN ARTIFICIAL NEURAL NETWORKS MODEL TO ESTIMATE DELAY USING TOLL PLAZA TRANSACTION DATA.
Creator: Muppidi, Aparna, Al-Deek, Haitham, University of Central Florida
Abstract / Description: In spite of the most up-to-date investigation of the relevant techniques to analyze the traffic characteristics and traffic operations at a toll plaza, there has not been any note worthy explorations evaluating delay from toll transaction data and using Artificial Neural Networks (ANN) at a toll plaza. This thesis lays an emphasis on the application of ANN techniques to estimate the total vehicular delay according to the lane type at a toll plaza. This is done to avoid the laborious task of...
Show moreIn spite of the most up-to-date investigation of the relevant techniques to analyze the traffic characteristics and traffic operations at a toll plaza, there has not been any note worthy explorations evaluating delay from toll transaction data and using Artificial Neural Networks (ANN) at a toll plaza. This thesis lays an emphasis on the application of ANN techniques to estimate the total vehicular delay according to the lane type at a toll plaza. This is done to avoid the laborious task of extracting data from the video recordings at a toll plaza. Based on the lane type a general methodology was developed to estimate the total vehicular delay at a toll plaza using ANN. Since there is zero delay in an Electronic Toll Collection (ETC) lane, ANN models were developed for estimating the total vehicular delay in a manual lane and automatic coin machine lane. Therefore, there are two ANN models developed in this thesis. These two ANN models were trained with three hours of data and validated with one hour of data from AM and PM peak data. The two ANN models were built with the dependent and independent variables. The dependent variables in the two models were the total vehicular delay for both the manual and automatic coin machine lane. The independent variables are those, which influence delay. A correlation analysis was performed to see if there exists any strong relationship between the dependent (outputs) and independent variables (inputs). These inputs and outputs are fed into the ANN models. The MATLABTB code was written to run the two ANN models. ANN predictions were good at estimating delay in manual lane, and delay in automatic coin machine lane.
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Date Issued: 2005
Identifier: CFE0000334, ucf:46298
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0000334

Title: DESIGN AND IMPLEMENTATION OF A HARDWARE LEVEL CONTENT NETWORKING FRONT END DEVICE.
Creator: Buboltz, Jeremy, Kocak, Taskin, University of Central Florida
Abstract / Description: The bandwidth and speed of network connections are continually increasing. The speed increase in network technology is set to soon outpace the speed increase in CMOS technology. This asymmetrical growth is beginning to causing software applications that once worked with then current levels of network traffic to flounder under the new high data rates. Processes that were once executed in software now have to be executed, partially if not wholly in hardware. One such application that could...
Show moreThe bandwidth and speed of network connections are continually increasing. The speed increase in network technology is set to soon outpace the speed increase in CMOS technology. This asymmetrical growth is beginning to causing software applications that once worked with then current levels of network traffic to flounder under the new high data rates. Processes that were once executed in software now have to be executed, partially if not wholly in hardware. One such application that could benefit from hardware implementation is high layer routing. By allowing a network device to peer into higher layers of the OSI model, the device can scan for viruses, provide higher quality-of-service (QoS), and efficiently route packets. This thesis proposes an architecture for a device that will utilize hardware-level string matching to distribute incoming requests for a server farm. The proposed architecture is implemented in VHDL, synthesized, and laid out on an Altera FPGA.
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Date Issued: 2007
Identifier: CFE0001888, ucf:47390
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001888

Title: CONGESTION AVOIDANCE AND FAIRNESS IN WIRELESS SENSOR NETWORKS.
Creator: Ahmad, Mohammad, Turgut, Damla, University of Central Florida
Abstract / Description: Sensor network congestion avoidance and control primarily aims to reduce packet drops while maintaining fair bandwidth allocation to existing network flows. The design of a congestion control algorithm suited for all types of applications in sensor networks is a challenging task due to the application-specific nature of these networks. With numerous sensors transmitting data simultaneously to one or more base stations (also called sinks), sensor nodes located near the base station will most...
Show moreSensor network congestion avoidance and control primarily aims to reduce packet drops while maintaining fair bandwidth allocation to existing network flows. The design of a congestion control algorithm suited for all types of applications in sensor networks is a challenging task due to the application-specific nature of these networks. With numerous sensors transmitting data simultaneously to one or more base stations (also called sinks), sensor nodes located near the base station will most likely experience congestion and packet loss. In this thesis, we propose a novel distributed congestion avoidance algorithm which calculates the ratio of the number of downstream and upstream nodes. This ratio value (named Characteristic ratio) is used to take a routing decision and incorporate load balancing while also serving as a pointer to the congestion state of the network. Available queue sizes of the downstream nodes are used to detect incipient congestion. Queue characteristics of candidate downstream nodes are used collectively to implement both congestion avoidance and fairness by adjusting the node's forwarding rate and next hop destination. Such an approach helps to minimize packet drops, improve energy efficiency and load balancing. In cases of severe congestion, the source is signaled to reduce its sending rate and enable the network recovery process. This is essentially a transport layer algorithm and would work best with a multi-path routing protocol and almost any MAC layer standard. We present the design and implementation of the proposed protocol and compare it with the existing avoidance protocols like Global rate control and Lightweight buffering. Our simulation results show a higher packet delivery ratio with greater node buffer utilization for our protocol in comparison with the conventional mechanisms.
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Date Issued: 2007
Identifier: CFE0001755, ucf:47255
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001755

Title: GRAPH THEORETIC MODELING: CASE STUDIES IN REDUNDANT ARRAYS OF INDEPENDENT DISKS AND NETWORK DEFENSE.
Creator: Nanda, Sanjeeb, Deo, Narsingh, University of Central Florida
Abstract / Description: Graph theoretic modeling has served as an invaluable tool for solving a variety of problems since its introduction in Euler's paper on the Bridges of Königsberg in 1736 . Two amongst them of contemporary interest are the modeling of Redundant Arrays of Inexpensive Disks (RAID), and the identification of network attacks. While the former is vital to the protection and uninterrupted availability of data, the latter is crucial to the integrity of systems comprising networks. Both are of...
Show moreGraph theoretic modeling has served as an invaluable tool for solving a variety of problems since its introduction in Euler's paper on the Bridges of Königsberg in 1736 . Two amongst them of contemporary interest are the modeling of Redundant Arrays of Inexpensive Disks (RAID), and the identification of network attacks. While the former is vital to the protection and uninterrupted availability of data, the latter is crucial to the integrity of systems comprising networks. Both are of practical importance due to the continuing growth of data and its demand at increasing numbers of geographically distributed locations through the use of networks such as the Internet. The popularity of RAID has soared because of the enhanced I/O bandwidths and large capacities they offer at low cost. However, the demand for bigger capacities has led to the use of larger arrays with increased probability of random disk failures. This has motivated the need for RAID systems to tolerate two or more disk failures, without sacrificing performance or storage space. To this end, we shall first perform a comparative study of the existing techniques that achieve this objective. Next, we shall devise novel graph-theoretic algorithms for placing data and parity in arrays of n disks (n ≥ 3) that can recover from two random disk failures, for n = p – 1, n = p and n = 2p – 2, where p is a prime number. Each shall be shown to utilize an optimal ratio of space for storing parity. We shall also show how to extend the algorithms to arrays with an arbitrary number of disks, albeit with non-optimal values for the aforementioned ratio. The growth of the Internet has led to the increased proliferation of malignant applications seeking to breach the security of networked systems. Hence, considerable effort has been focused on detecting and predicting the attacks they perpetrate. However, the enormity of the Internet poses a challenge to representing and analyzing them by using scalable models. Furthermore, forecasting the systems that they are likely to exploit in the future is difficult due to the unavailability of complete information on network vulnerabilities. We shall present a technique that identifies attacks on large networks using a scalable model, while filtering for false positives and negatives. Furthermore, it also forecasts the propagation of security failures proliferated by attacks over time and their likely targets in the future.
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Date Issued: 2007
Identifier: CFE0001919, ucf:47475
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001919

Title: A NEAT APPROACH TO GENETIC PROGRAMMING.
Creator: Rodriguez, Adelein, Wu, Annie, University of Central Florida
Abstract / Description: The evolution of explicitly represented topologies such as graphs involves devising methods for mutating, comparing and combining structures in meaningful ways and identifying and maintaining the necessary topological diversity. Research has been conducted in the area of the evolution of trees in genetic programming and of neural networks and some of these problems have been addressed independently by the different research communities. In the domain of neural networks, NEAT (Neuroevolution...
Show moreThe evolution of explicitly represented topologies such as graphs involves devising methods for mutating, comparing and combining structures in meaningful ways and identifying and maintaining the necessary topological diversity. Research has been conducted in the area of the evolution of trees in genetic programming and of neural networks and some of these problems have been addressed independently by the different research communities. In the domain of neural networks, NEAT (Neuroevolution of Augmenting Topologies) has shown to be a successful method for evolving increasingly complex networks. This system's success is based on three interrelated elements: speciation, marking of historical information in topologies, and initializing search in a small structures search space. This provides the dynamics necessary for the exploration of diverse solution spaces at once and a way to discriminate between different structures. Although different representations have emerged in the area of genetic programming, the study of the tree representation has remained of interest in great part because of its mapping to programming languages and also because of the observed phenomenon of unnecessary code growth or bloat which hinders performance. The structural similarity between trees and neural networks poses an interesting question: Is it possible to apply the techniques from NEAT to the evolution of trees and if so, how does it affect performance and the dynamics of code growth? In this work we address these questions and present analogous techniques to those in NEAT for genetic programming.
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Date Issued: 2007
Identifier: CFE0001971, ucf:47451
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001971

Title: HEURISTIC PRIORITIZATION OF EMERGENCY EVACUATION STAGING TO REDUCE CLEARANCE TIME.
Creator: Mitchell, Steven, Radwan, Essam, University of Central Florida
Abstract / Description: A region's evacuation strategy encompasses a variety of areas and needs. Primary among these is the minimization of total evacuation time, represented in models as the clearance time estimate (CTE). A generic testbed simulation network model was developed. An input/output (I/O) analysis was performed to establish a theoretical baseline CTE. Results were compared with simulations; analysis showed that the I/O method underestimated simulated CTE as a function of network size, with a correction...
Show moreA region's evacuation strategy encompasses a variety of areas and needs. Primary among these is the minimization of total evacuation time, represented in models as the clearance time estimate (CTE). A generic testbed simulation network model was developed. An input/output (I/O) analysis was performed to establish a theoretical baseline CTE. Results were compared with simulations; analysis showed that the I/O method underestimated simulated CTE as a function of network size, with a correction factor range of 1.09 to 1.19. A regression model was developed for the generic network. Predictors were total trips, and network size defined as a function of origin-destination distance. Total Trips ranged between 40,000 and 60,000. Holding size constant, R-squared values ranged from 97.1 to 99.3, indicating a high goodness of fit. Holding Total Trips constant, R-squared values ranged from 74.5 to 89.2. Finally, both Total Trips and size were used as predictors; the resulting regression model had an R-squared value of 97.3. This overall model is more useful, since real world situations are not fixed in nature. The overall regression model was compared to a case network. The generic network regression model provided a close CTE approximation; deltas ranged from -4.7% to 8.6%. It was concluded that a generic network can serve as a surrogate for a case network over these ranges. This study developed and evaluated heuristic strategies for evacuation using the generic network. Strategies were compared with a simultaneous departure loading scenario. Six different grouping strategies were evaluated. An initial evaluation was conducted using the generic network, and strategies that showed potential CTE reduction were implemented on the case study network. Analysis indicated that the HF-10 (half-far) grouping for 60k total trips showed potential reduction. A complete simulation was conducted on the case network for all HF scenarios; an ANOVA was run using Dunnett's comparison. Results indicated that the HF grouping with 20% and 30% departure shifts showed potential for CTE reduction. From this it was concluded that the generic network could be used as a testbed for strategies that would show success on a case network.
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Date Issued: 2006
Identifier: CFE0001098, ucf:46777
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001098

Title: SPARSIFICATION OF SOCIAL NETWORKS USING RANDOM WALKS.
Creator: Wilder, Bryan, Sukthankar, Gita, University of Central Florida
Abstract / Description: Analysis of large network datasets has become increasingly important. Algorithms have been designed to find many kinds of structure, with numerous applications across the social and biological sciences. However, a tradeoff is always present between accuracy and scalability; otherwise promising techniques can be computationally infeasible when applied to networks with huge numbers of nodes and edges. One way of extending the reach of network analysis is to sparsify the graph by retaining only...
Show moreAnalysis of large network datasets has become increasingly important. Algorithms have been designed to find many kinds of structure, with numerous applications across the social and biological sciences. However, a tradeoff is always present between accuracy and scalability; otherwise promising techniques can be computationally infeasible when applied to networks with huge numbers of nodes and edges. One way of extending the reach of network analysis is to sparsify the graph by retaining only a subset of its edges. The reduced network could prove much more tractable. For this thesis, I propose a new sparsification algorithm that preserves the properties of a random walk on the network. Specifically, the algorithm finds a subset of edges that best preserves the stationary distribution of a random walk by minimizing the Kullback-Leibler divergence between a walk on the original and sparsified graphs. A highly efficient greedy search strategy is developed to optimize this objective. Experimental results are presented that test the performance of the algorithm on the influence maximization task. These results demonstrate that sparsification allows near-optimal solutions to be found in a small fraction of the runtime that would required using the full network. Two cases are shown where sparsification allows an influence maximization algorithm to be applied to a dataset that previous work had considered intractable.
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Date Issued: 2015
Identifier: CFH0004732, ucf:45387
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFH0004732

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