UNT Libraries - 8 Matching Results

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Capacity and Throughput Optimization in Multi-cell 3G WCDMA Networks

Description: User modeling enables in the computation of the traffic density in a cellular network, which can be used to optimize the placement of base stations and radio network controllers as well as to analyze the performance of resource management algorithms towards meeting the final goal: the calculation and maximization of network capacity and throughput for different data rate services. An analytical model is presented for approximating the user distributions in multi-cell third generation wideband code division multiple access (WCDMA) networks using 2-dimensional Gaussian distributions by determining the means and the standard deviations of the distributions for every cell. This model allows for the calculation of the inter-cell interference and the reverse-link capacity of the network. An analytical model for optimizing capacity in multi-cell WCDMA networks is presented. Capacity is optimized for different spreading factors and for perfect and imperfect power control. Numerical results show that the SIR threshold for the received signals is decreased by 0.5 to 1.5 dB due to the imperfect power control. The results also show that the determined parameters of the 2-dimensional Gaussian model match well with traditional methods for modeling user distribution. A call admission control algorithm is designed that maximizes the throughput in multi-cell WCDMA networks. Numerical results are presented for different spreading factors and for several mobility scenarios. Our methods of optimizing capacity and throughput are computationally efficient, accurate, and can be implemented in large WCDMA networks.
Date: December 2005
Creator: Nguyen, Son

Resource Management in Wireless Networks

Description: A local call admission control (CAC) algorithm for third generation wireless networks was designed and implemented, which allows for the simulation of network throughput for different spreading factors and various mobility scenarios. A global CAC algorithm is also implemented and used as a benchmark since it is inherently optimized; it yields the best possible performance but has an intensive computational complexity. Optimized local CAC algorithm achieves similar performance as global CAC algorithm at a fraction of the computational cost. Design of a dynamic channel assignment algorithm for IEEE 802.11 wireless systems is also presented. Channels are assigned dynamically depending on the minimal interference generated by the neighboring access points on a reference access point. Analysis of dynamic channel assignment algorithm shows an improvement by a factor of 4 over the default settings of having all access points use the same channel, resulting significantly higher network throughput.
Date: August 2006
Creator: Arepally, Anurag

Comparative Study of RSS-Based Collaborative Localization Methods in Wireless Sensor Networks

Description: In this thesis two collaborative localization techniques are studied: multidimensional scaling (MDS) and maximum likelihood estimator (MLE). A synthesis of a new location estimation method through a serial integration of these two techniques, such that an estimate is first obtained using MDS and then MLE is employed to fine-tune the MDS solution, was the subject of this research using various simulation and experimental studies. In the simulations, important issues including the effects of sensor node density, reference node density and different deployment strategies of reference nodes were addressed. In the experimental study, the path loss model of indoor environments is developed by determining the environment-specific parameters from the experimental measurement data. Then, the empirical path loss model is employed in the analysis and simulation study of the performance of collaborative localization techniques.
Date: December 2006
Creator: Koneru, Avanthi

Models to Combat Email Spam Botnets and Unwanted Phone Calls

Description: With the amount of email spam received these days it is hard to imagine that spammers act individually. Nowadays, most of the spam emails have been sent from a collection of compromised machines controlled by some spammers. These compromised computers are often called bots, using which the spammers can send massive volume of spam within a short period of time. The motivation of this work is to understand and analyze the behavior of spammers through a large collection of spam mails. My research examined a the data set collected over a 2.5-year period and developed an algorithm which would give the botnet features and then classify them into various groups. Principal component analysis was used to study the association patterns of group of spammers and the individual behavior of a spammer in a given domain. This is based on the features which capture maximum variance of information we have clustered. Presence information is a growing tool towards more efficient communication and providing new services and features within a business setting and much more. The main contribution in my thesis is to propose the willingness estimator that can estimate the callee's willingness without his/her involvement, the model estimates willingness level based on call history. Finally, the accuracy of the proposed willingness estimator is validated with the actual call logs.
Date: May 2008
Creator: Husna, Husain

Non-Uniform Grid-Based Coordinated Routing in Wireless Sensor Networks

Description: Wireless sensor networks are ad hoc networks of tiny battery powered sensor nodes that can organize themselves to form self-organized networks and collect information regarding temperature, light, and pressure in an area. Though the applications of sensor networks are very promising, sensor nodes are limited in their capability due to many factors. The main limitation of these battery powered nodes is energy. Sensor networks are expected to work for long periods of time once deployed and it becomes important to conserve the battery life of the nodes to extend network lifetime. This work examines non-uniform grid-based routing protocol as an effort to minimize energy consumption in the network and extend network lifetime. The entire test area is divided into non-uniformly shaped grids. Fixed source and sink nodes with unlimited energy are placed in the network. Sensor nodes with full battery life are deployed uniformly and randomly in the field. The source node floods the network with only the coordinator node active in each grid and the other nodes sleeping. The sink node traces the same route back to the source node through the same coordinators. This process continues till a coordinator node runs out of energy, when new coordinator nodes are elected to participate in routing. Thus the network stays alive till the link between the source and sink nodes is lost, i.e., the network is partitioned. This work explores the efficiency of the non-uniform grid-based routing protocol for different node densities and the non-uniform grid structure that best extends network lifetime.
Date: August 2008
Creator: Kadiyala, Priyanka

E‐Shape Analysis

Description: The motivation of this work is to understand E-shape analysis and how it can be applied to various classification tasks. It has a powerful feature to not only look at what information is contained, but rather how that information looks. This new technique gives E-shape analysis the ability to be language independent and to some extent size independent. In this thesis, I present a new mechanism to characterize an email without using content or context called E-shape analysis for email. I explore the applications of the email shape by carrying out a case study; botnet detection and two possible applications: spam filtering and social-context based finger printing. The second part of this thesis takes what I apply E-shape analysis to activity recognition of humans. Using the Android platform and a T-Mobile G1 phone I collect data from the triaxial accelerometer and use it to classify the motion behavior of a subject.
Date: December 2009
Creator: Sroufe, Paul

Evaluating Appropriateness of Emg and Flex Sensors for Classifying Hand Gestures

Description: Hand and arm gestures are a great way of communication when you don't want to be heard, quieter and often more reliable than whispering into a radio mike. In recent years hand gesture identification became a major active area of research due its use in various applications. The objective of my work is to develop an integrated sensor system, which will enable tactical squads and SWAT teams to communicate when there is absence of a Line of Sight or in the presence of any obstacles. The gesture set involved in this work is the standardized hand signals for close range engagement operations used by military and SWAT teams. The gesture sets involved in this work are broadly divided into finger movements and arm movements. The core components of the integrated sensor system are: Surface EMG sensors, Flex sensors and accelerometers. Surface EMG is the electrical activity produced by muscle contractions and measured by sensors directly attached to the skin. Bend Sensors use a piezo resistive material to detect the bend. The sensor output is determined by both the angle between the ends of the sensor as well as the flex radius. Accelerometers sense the dynamic acceleration and inclination in 3 directions simultaneously. EMG sensors are placed on the upper and lower forearm and assist in the classification of the finger and wrist movements. Bend sensors are mounted on a glove that is worn on the hand. The sensors are located over the first knuckle of each figure and can determine if the finger is bent or not. An accelerometer is attached to the glove at the base of the wrist and determines the speed and direction of the arm movement. Classification algorithm SVM is used to classify the gestures.
Date: May 2013
Creator: Akumalla, Sarath Chandra

Probabilistic Analysis of Contracting Ebola Virus Using Contextual Intelligence

Description: The outbreak of the Ebola virus was declared a Public Health Emergency of International Concern by the World Health Organisation (WHO). Due to the complex nature of the outbreak, the Centers for Disease Control and Prevention (CDC) had created interim guidance for monitoring people potentially exposed to Ebola and for evaluating their intended travel and restricting the movements of carriers when needed. Tools to evaluate the risk of individuals and groups of individuals contracting the disease could mitigate the growing anxiety and fear. The goal is to understand and analyze the nature of risk an individual would face when he/she comes in contact with a carrier. This thesis presents a tool that makes use of contextual data intelligence to predict the risk factor of individuals who come in contact with the carrier.
Date: May 2017
Creator: Gopala Krishnan, Arjun