Computer Science Masters Theses

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Athletic Fundraising and University Development Offices: A Structurational Relationship
(North Dakota State University, 2010) Dickhudt, Keith Michael
This case study examines the working relationship between an athletic department and a central development office within a university. This study focuses primarily on the coordination of fundraising efforts between the two offices. A qualitative approach, using a structuration theoretical framework, presents the working relationship at Midwestern State University (MWSU) through in-depth interviews. Results suggest the two offices could improve the coordination of fundraising efforts. Recommendations, based on the results and theoretical framework, are given.
Recruiting Through Identification: Identification Strategies and Tactics Used in External Higher Education Strategic Communication
(North Dakota State University, 2010) Anderson, Dana Raye
This exploratory study examines higher education strategic communication for identification inducement strategies and tactics using Cheney's (1983) typology as a guiding framework. The study also explores the differences in identification inducement strategies and tactics used between traditional public universities and for-profit online educators. The results of a deductive textual analysis indicate that identification inducement strategies are used in higher education strategic communication designed to recruit students, an external audience with a reverse paid relationship with the organization. A new strategy and two tactics are added to Cheney's typology to fully account for the identification appeals identified.
Optimization of Mobile Sensor Movement in Self-Healing Sensor Networks
(North Dakota State University, 2010) Basu, Samidip
This paper moves forward the key idea as proposed in past research works - a self-healing deployment approach for sensor networks, where a small percentage of mobile sensors are deployed along with the static sensors into a field of concern. Mobile sensors can move to make-up for a coverage holes or sensor failure and significantly boost network performance. However, since there are energy constraints on each individual mobile sensor, potentially receiving multiple requests from network holes, the decision to move a mobile sensor has to be optimum, one that maximizes network benefit. In this paper, I propose a hybrid distributed & central decision making algorithm to facilitate optimal moves by each mobile sensor. The algorithm uses several layered techniques like Rough Set analysis, sorting & multi-level auction to provide the best possible decision, given the network scenario and the approach is robust to incompleteness of information. The proposed solution also safeguards against network deadlocks and extensive simulations & statistical analysis have demonstrated superior performance of the algorithm when compared to its peers. Some traits of the algorithm proposed derive inspiration for decision support from Ants' swarm intelligence.
Resource and Bandwidth Allocation in Hybrid Wireless Mobile Networks
(North Dakota State University, 2010) Bengfort, Benjamin John
In the lead up to the implementation of 802.16 and 4G wireless networks, there have been many proposals for addition of multi-hop MANET zones or relay stations in order to cut the cost of building a new backbone infrastructure from the ground up. These types of Hybrid Wireless Networks will certainly be a part of wireless network architecture in the future, and as such, simple problems such as resource allocation must be explored to maximize their potential. This study explores the resource allocation problem in three distinct ways. First, this study highlights two existing backbone architectures: max-coverage and max-resource, and how hybridization will affect bandwidth allocation, with special emphasis on OFDM-TMA wireless networks. Secondly, because of the different goals of these types of networks, the addition of relay stations or MANET zones will affect resource availability differently, and I will show how the addition of relay stations impacts the backbone network. Finally, I will discuss specific allocation algorithms and policies such as top-down, bottom-up, and auction-based allocation, and how each kind of allocation will maximize the revenue of both the backbone network as well as the mobile subscribers while maintaining a minimum Quality of Service (or fairness). Each of these approaches has merit in different hybrid wireless systems, and I will summarize the benefits of each in a study of a network system with a combination of the elements discussed in the previous chapters.
Dynamic Algorithms for Sensor Scheduling and Adversary Path Prediction
(North Dakota State University, 2010) Pandey, Shivendushital Pyarelal
In this thesis we describe three new dynamic, real time and robust sensor scheduling algorithms for intruder tracking and sensor scheduling. We call them Tactic Association Based Algorithm (TABA), Tactic Case Based Algorithm (TCBA) and Tactic Weight Based Algorithm (TWBA). The algorithms are encoded, illustrated visually, validated, and tested. The aim of the algorithms is to efficiently track an intruder or multiple intruders while minimizing energy usage in the sensor network by using real time event driven sensor scheduling. What makes these intrusion detection schemes different from other intrusion detection schemes in the literature is the use of historical data in path prediction and sensor scheduling. The TABA uses sequence pattern mining to generate confidences of movement of an intruder from one location to another location in the sensor network. TCBA uses the Case-based reasoning approach to schedule sensors and track intruders in the wireless sensor network. TWBA uses weighted hexagonal representation of the sensor network to schedule sensors and track intruders. In this research we also introduce a novel approach to generate probable intruder paths which are strong representatives of the paths intruders would take when moving through the sensor network.
A Closed Form Optimization Model for The Conflict Neutralization Problem
(North Dakota State University, 2010) Wang, Yan
In this study, we proposed a novel closed form optimization model for the Conflict Neutralization Problem (CKP) and implemented an efficient algorithm for solving the problem. A novel tableau representation of the CNP model was presented and described in detail. We implemented a special structured branch and bound algorithm to solve the problem. Key components of the implementation were described. To test the computation performance of our algorithm, we designed and conducted three sets of experiments. The experiment results were reported and analyzed in this report. The test results showed the efficiency of the algorithm for solving the Conflict Neutralization Problem.
An Architecture for the Implementation and Distribution of Multiuser Virtual Environments.
(North Dakota State University, 2010) Dischinger, Benjamin James
JavaMOO is an architecture for creating multiuser virtual environments focusing on domain-specific design and rapid development. JavaMOO components use best practices and extensible design for system configuration, client-server communication, event handling, object persistence, content delivery, and agent control. Application dependencies such as database and web servers are embedded, promoting wide dissemination by decreasing management overhead. The focus of this thesis is the design and implementation of the JavaMOO architecture and how it helps improve the state of multiuser virtual environments.
Post-Deployment Key Management in Heterogeneous Wireless Sensor Networks
(North Dakota State University, 2010) Loree, Paul Edward
Many wireless sensor network applications require secure communication between nodes in the network. However, establishing pair-wise keys between nodes to provide security is challenging due to the limited resources in sensor nodes and the hostile environments in which they are deployed. Many key establishment schemes have been previously proposed for wireless sensor networks. However, most of these schemes were designed to work in a homogeneous network environment in which the nodes all have similar capabilities. Our work establishes that better performance can be achieved in a heterogeneous sensor network environment. We present a key management scheme for establishing pair-wise keys after deployment in a heterogeneous wireless sensor network. We take advantage of the more powerful nodes present in a heterogeneous network to reduce the communication overhead and ultimately the power consumption necessary to perform these services to the network. Additionally, by taking advantage of these nodes we are able to increase the overall network connectivity and resiliency against node capture attacks.
Anonymity and Hostile Node Identification in Wireless Sensor Networks
(North Dakota State University, 2010) Reindl, Phillip Steven
In many secure wireless network attack scenarios, the source of a data packet is as sensitive as the data it contains. Existing work to provide source anonymity in wireless sensor networks (WSN) are not frugal in terms of transmission overhead. We present a set of schemes to provide secure source anonymity. As the state of the art in WSN advances, researchers increasingly look to heterogeneous network topologies. We leverage high powered cluster head nodes to further reduce transmission overhead and provide excellent scalability. A significant threat to WSN is the insider attack due to the ease of tampering with low-cost sensors. Should a node become compromised and start making malicious collisions, it is desirable to identify the corrupt node and revoke its keys. We present schemes to identify the source of an arbitrary transmission in a reliable and distributed fashion.
Data Replication Strategies in Cloud Computing
(North Dakota State University, 2011) Liu, Yang
Data replication is a widely used technique in various systems. For example, it can be employed in large-scale distributed file systems to increase data availability and system reliability, or it can be used in many network models (e.g. data grid, Amazon CloudFront) to reduce access latency and network bandwidth consumption, etc. I study a series of problems that related to the data replication method in Hadoop Distributed File System (HDFS) and in Amazon CloudFront service. Data failure, which is caused by hardware failure or malfunction, software error, human error, is the greatest threat to the file storage system. I present a set of schemes to enhance the efficiency of the current data replication strategy in HDFS thereby improving system reliability and performance. I also study the application replication placement problem based on an Original-Front sever model, and I propose a novel strategy which intends to maximize the profit of the application providers.
POMDP Planning in Service Composition
(North Dakota State University, 2011) Min, Chen
Automated vVeb service composition is becoming an increasingly important research topic. It describes the automatic process of composing atomic services into a chain of services that provide a specific functionality that could not be achieved by atomic services alone. A service-oriented environment is dynamic in nature, meaning that services come online and go offiine, services change their functionality, etc. Current classical AI planning techniques suffer from the assumption of deterministic behavior of \Veb services and require execution monitoring for service failures. To address this concern, Partially Observable Markov Decision Processes (POMDP) in workflow composition has been used. POMDPs provide a powerful mathematical framework for planning and decision making in noisy and/ or dynamic environments. PO:\1DPs have been widely used to model many real-world problems. This thesis develops, implements and analyzes the suitability of the POMDP approach to the Web service composition problem. iii
Uses and Gratifications of Amputees' Online Social Networks
(2011) Frohlich, Dennis Owen
The following thesis examined amputee support groups on Facebook. Having an 111 amputation can be a life-changing experience. and social support may be necessary to understand one's amputation. Hundreds of amputee groups exist on Face book, and many of them foster active onlinc communities. This study sought to accomplish two goals: describe how amputees use these groups, and uncover the predictors that lead to engagement in socially supportive behaviors, particularly providing informational support and emotional support. While not all groups are active, this study found that amputees do connect with others through Facebook, sometimes quite frequently. Posting on group walls significantly predicted use of informational support behaviors, and age, overall heal th condition, and posting on group walls significantly predicted use of emotional support behaviors.
Frequent Substring-Based Sequence Classification Using Reduced Alphabets
(North Dakota State University, 2011) Chitraranjan, Charith Devinda
In recent years, various disciplines have generated large quantities of sequence data which has necessitated automated techniques for classifying these sequences into different categories of interest. Especially with the rapid rate at which biological sequence data has been emerging out of high throughput sequencing efforts, the need to interpret these large quantities of raw sequence data and gain deeper insights into them has become an essential part of modern biological research. Understanding the functions, localization and structure of newly identified protein sequences in particular has become a major challenge and is seeking the aid of computational techniques to keep up with the pace. In this thesis, we1 evaluate frequent pattern-based algorithms for predicting aforementioned attributes of proteins from their primary structure ( amino acid sequence). \Ve also apply our algorithms to datasets containing wheat Expressed Sequence Tags (ESTs) as an attempt to predict ESTs that are likely to be located near the centromere of their respective chromosomes. \Ve use frequent substrings mined from the training sequences as features to train a classifier. Our evaluation includes SVM and association rule-based classifiers. Some amino acids have similar properties and may substitute one another without altering the topology or function of a protein. Therefore, we use a combination of reduced amino acid alphabets in an attempt to capture patterns that may contain such substitutions. Frequent substrings mined from different alphabets are treated as features resulting from multiple sources and we evaluate both feature fusion and classifier fusion approaches towards multiple source prediction. 'We compare the performance of the different approaches using protein sub-cellular location, protein function and EST chromosomal location datasets. Pair-wise sequence-alignment-based Nearest Neighbor and basic SVM k-gram classifiers are also included as baseline algorithms in the comparison. Results show that frequent pattern-based SVM classifiers demonstrate better performance compared to other classifiers on the sub-cellular location datasets and they perform competitively with the nearest neighbor classifier on the protein function datasets. Our results also show that the use of reduced alphabets provides statistically significant performance improvements for the SVM-based classifier fusion algorithm, for half of the classes studied.
Distance-Aware Relay Placement and Scheduling in Wireless Networks.
(North Dakota State University, 2011) Bai, Shi
The WiMAX technology and cognitive radio have been active topics in wireless networks. A WiMAX mesh network is able to provide larger wireless coverage, higher network capacity and Non-Line-Of-Sight (NLOS) communications. Cognitive radios enable dynamic spectrum access over a large frequency range. These characteristics make WiMAX mesh networks and cognitive radio networks able to provide users with low-cost, high-speed and long-range wireless communications, as well as better Quality of Service. However, there are still several challenges and problems to be solved in this area, such as relay station placement problems and scheduling problems. In this thesis, I studied a distance-aware relay placement problem and max-min fair scheduling problem in WiMAX mesh networks. To solve these problems, approximation algorithms and heuristic algorithms are proposed. Theoretical analysis and simulation results are provided to evaluate the solutions. I also studied a scheduling problem adopting the idea of cognitive radio technique in wireless networks over water. Two heuristics are presented to solve this unique problem. I provide the numerical results to justify the performance and efficiency of our proposed scheduling algorithms.
Efficient Publish/Subscribe System over Mobile Ad-Hoc Network
(North Dakota State University, 2012) Liu, Chao
Information dissemination is an important issue for mobile ad-hoc communities. This issue is very challenging due to the dynamic and fragile nature of the mobile ad-hoc networks, in which participants have limited computing resources and battery, intermittent network connections, and mobile tasks. To address the aforementioned issue, this thesis proposes an efficient semantics-based publish/subscribe strategy. In our proposed publish/subscribe system, distributed mobile participants are organized into clusters based on their location proximity. A compact semantics-based indexing scheme is provided to guide information flow. Intra- and inter- cluster routings are proposed to assist efficient propagation of event notifications. A comprehensive set of simulation experiments prove the effectiveness of the proposed scheme.
Adaptive Regression Testing Strategy: An Empirical Study
(North Dakota State University, 2012) Arafeen, Md. Junaid
When software systems evolve, different amounts of code modifications can be involved in different versions. These factors can affect the costs and benefits of regression testing techniques, and thus, there may be no single regression testing technique that is the most cost-effective technique to use on every version. To date, many regression testing techniques have been proposed, but no research has been done on the problem of helping practitioners systematically choose appropriate techniques on new versions as systems evolve. To address this problem, we propose adaptive regression testing (ART) strategies that attempt to identify the regression testing techniques that will be the most cost-effective for each regression testing session considering organization’s situations and testing environment. To assess our approach, we conducted an experiment focusing on test case prioritization techniques. Our results show that prioritization techniques selected by our approach can be more cost-effective than those used by the control approaches.
An Investigation of Integration and Performance Issues Related to the Use of Extended Page Sizes in Computationally Intensive Applications
(North Dakota State University, 2012) Piehl, Matthew James
The combination of increasing fabrication density and corresponding decrease in price has resulted in the ability of commodity platforms to support large memory capacities. Processor designers have introduced support for extended hardware page sizes to assist operating systems with efficiently scaling to these memory capacities. This paper will explore integration strategies the designers of the Linux operating system have used to access this hardware support and the practical performance impact of using this support. This paper also provides a review of common strategies for adding support for this functionality at the application level. These strategies are applied to a sampling representative of common scientific applications to support a practical evaluation of the expected performance impact of extended page size support. An analysis of these results support a finding that a 5% performance improvement can be expected by adding support for extended page sizes to memory intensive scientific applications.
A Distributed Power Market for the Smart Grid
(North Dakota State University, 2012) McCulloch, Ryan James
To address the challenges of resource allocation in the Smart Electrical Grid a new power market is proposed. A distributed and autonomous contract net based market system in which participants, represented by the agents, engage in two distinct yet interconnected markets in order to determine resource allocation. Key to this proposed design is the 2 market structure which separates negotiations between consumers and reliable generation from negotiations between consumers and intermittent energy resources. The first or primary market operates as a first price sealed bid reverse auction while the second or secondary market utilizes a uniform price auction. In order to evaluate this new market a simulator is developed and the market is modeled and tested within it. The results of these tests indicate that the proposed design is an effective method of allocating electrical grid resources amongst consumers, generators, and intermittent energy resources with some feasibility and scalability limitations.
Evaluating the Gap Between the Skills and Abilities of Senior Undergraduate Computer Science Students and the Expectations of Industry
(North Dakota State University, 2012) Radermacher, Alex
A large emphasis is placed on improving student education. Every year researchers propose new teaching methods and suggest improvements to existing methods. However, recent computer science and software engineering graduates continue to face difficulties when beginning their professional careers. This thesis reports the results of a systematic literature review that examined the knowledge deficiency among graduating students beginning work in the software industry. Following the literature review, interviews with industry managers and surveys of graduating students were undertaken to examine additional knowledge deficiencies among graduating students. The results from the literature review and the additional studies show that students lack proficiency with software development tools, knowledge of software testing, and teamwork and communication skills. The results of this research can be used by both educators and industry managers to identify potential areas of improvement for students and new hires.
Investigation of the Effect of the Number of Inspectors on the Software Defect Estimates
(North Dakota State University, 2012) Saxena, Kaustubh
Capture-recapture models help software managers by providing post-inspection defect estimate remaining in a software artifact to determine if a re-inspection in necessary. These estimates are calculated using the number of unique faults per inspector and the overlap of faults found by inspectors during an inspection cycle. A common belief is that the accuracy of the capture-recapture estimates improves with the inspection team size. This however, has not been empirically studied. This paper empirically investigates the effect of the number of inspectors on the estimates produced by capture-recapture models, by using inspection data with varying number and types of inspectors. The results show that the SC (Sample Coverage) estimators are best suited to software inspections and need least number of inspectors to achieve accurate and precise estimates. Our results also provide a detailed analysis of the number of inspectors necessary to obtain estimates within 5-20% of the actual defect count.

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