Computer Engineering Commons^™

User Modeling Via Machine Learning And Rule-Based Reasoning To Understand And Predict Errors In Survey Systems, Leonard Cleve Stuart

School of Computing: Dissertations, Theses, and Student Research

User modeling is traditionally applied to systems were users have a large degree of control over their goals, the content they view, and the manner in which they navigate through the system. These systems aim to both recommend useful goals to users and to assist them in achieving perceived goals. Systems such as online or telephone surveys are different in that users have only a singular goal of survey completion, extremely limited control over navigation, and content is restricted to prescribed set of survey tasks; changing the user modeling problem to one in which the best means of assisting users …

Decentralized Collision Avoidance, Jayasri K. Janardanan

School of Computing: Dissertations, Theses, and Student Research

Autonomous Robots must carry out their tasks as independently as possible and each robot may be assigned different tasks at different locations. As these tasks are being performed, the robots have to navigate correctly such that the assigned tasks are completed efficiently, while also avoiding each other and other obstacles. To accomplish effective navigation, we must ensure that the robots are calibrated to avoid colliding with any kind of object on its path. Each robot has to sense the obstacles on its path and take necessary corrective measure to avoid those obstacles. In a situation with multiple robots, robots may …

Improving Virtual Collaboration: Modeling For Recommendation Systems In A Classroom Wiki Environment, Derrick A. Lam

School of Computing: Dissertations, Theses, and Student Research

Collaboration is of increased importance in today’s society, with increased emphasis placed on working jointly with others, whether it is in the classroom, in the lab, in the workplace, or virtually across the world. The wiki is one particular virtual collaboration tool that is gaining particular prominence in recent years, enabling people – either in small project groups or as part of the wiki’s entire user base – to socially construct knowledge asynchronously on a wide variety of topics. However, there are few intelligent support tools for wikis available, particularly those providing recommendation-based support to users.

This thesis investigates the …

Fastlane: Flow-Based Channel Assignment In Dense Wireless Networks, Dane N. Seaberg

School of Computing: Dissertations, Theses, and Student Research

Wireless communication in dense networks is becoming more apparent and presents challenges in achieving reliable and near real-time communication. While some works have begun to address dense wireless networks, few address both reliability and latency. In this work we introduce FastLane, a method of ow-based channel assignment for dense wireless networks, which works to achieve reliable, near real-time communication in a dense environment with single-radio devices. FastLane uses an assignment mechanism that assigns channels at a ow-level granularity, rather than a tree-level or link-level granularity. Our scheme also takes into account channel quality and can adapt as the quality changes …

Energy-Efficient Failure Recovery In Hadoop Cluster, Weiyue Xu

School of Computing: Dissertations, Theses, and Student Research

Based on U.S. Environmental Protection Agency’s estimation, only in U.S., billions of dollars are spent on the electricity cost of data centers each year, and the cost is continually increasing very quickly. Energy efficiency is now used as an important metric for evaluating a computing system. However, saving energy is a big challenge due to many constraints. For example, in one of the most popular distributed processing frameworks, Hadoop, three replicas of each data block are randomly distributed in order to improve performance and fault tolerance, but such a mechanism limits the largest number of machine that can be turned …

Test Advising Framework, Yurong Wang

School of Computing: Dissertations, Theses, and Student Research

Test cases are represented in various formats depending on the process, the technique or the tool used to generate the tests. While different test case representations are necessary, this diversity challenges us in comparing test cases and leveraging strengths among them - a common test representation will help.

In this thesis, we define a new Test Case Language (TCL) that can be used to represent test cases that vary in structure and are generated by multiple test generation frameworks. We also present a methodology for transforming test cases of varying representations into a common format where they can be matched …

Directed Test Suite Augmentation, Zhihong Xu

School of Computing: Dissertations, Theses, and Student Research

Test suite augmentation techniques are used in regression testing to identify code elements affected by changes and to generate test cases to cover those elements. Whereas methods and techniques to find affected elements have been extensively researched in regression testing, the problem of generating new test cases to cover these elements cost-effectively has rarely been studied. We believe that reusing existing test cases will help us achieve this task. This research develops test suite augmentation techniques that reuse existing test cases to automatically generate new test cases to cost-effectively cover affected elements. We begin by using two dynamic test case …

Spatiotemporal Capacity Management For The Last Level Caches Of Chip Multiprocessors, Dongyuan Zhan

School of Computing: Dissertations, Theses, and Student Research

Judicious management of on-chip last-level caches (LLC) is critical to alleviating the memory wall of chip multiprocessors (CMP). Although there already exist many LLC management proposals, belonging to either the spatial or temporal dimension, they fail to capture and utilize the inherent interplays between the two dimensions in capacity management. Therefore, this dissertation is targeted at exploring and exploiting the spatiotemporal interactions in LLC capacity management to improve CMPs' performance. Based on this general idea, we address four specific research problems in the dissertation.

For the private LLC organization, prior-art proposals can improve the efficacy of inter-core cooperative caching at …

Modeling Of Yeast Pheromone Pathway Using Petri Nets, Abhishek Majumdar

School of Computing: Dissertations, Theses, and Student Research

Yeast (Saccharomyces cerevisiae) is one of the most widely studied single celled organisms. Mating of yeast cells occur between cells of opposite mating types a and alpha. Pheromone secretion by a cell alerts the corresponding opposite type cell about its presence and eventually facilitates the process of mating between them. The details of how pheromones affect cells can be studied from the pheromone response pathway in a yeast cell. A response pathway typically depicts the chain of interactions that happens between the different proteins in the cells in response to the pheromone. In this thesis we model the …

A Unifying Approach To Behavioral Coverage, Elena Sherman

School of Computing: Dissertations, Theses, and Student Research

Developing methods for validating that a program works as intended is one of the key research areas in software engineering. Ideally a program P must exhibit its expected be- havior, or property, φ on all of its inputs, i.e., P |= φ. The software engineering community has developed various program analysis approaches to assess whether P |= φ. In general, these approaches can be partitioned into dynamic and static program analysis. The former execute P on a particular input and checks that the execution conforms to φ. The latter in- terprets the code of P and check that on all …

Improving Performance Of Solid State Drives In Enterprise Environment, Jian Hu

School of Computing: Dissertations, Theses, and Student Research

Flash memory, in the form of Solid State Drive (SSD), is being increasingly employed in mobile and enterprise-level storage systems due to its superior features such as high energy efficiency, high random read performance and small form factor. However, SSD suffers from the erase-before-write and endurance problems, which limit the direct deployment of SSD in enterprise environment. Existing studies either develop SSD-friendly on-board buffer management algorithms, or design sophisticated Flash Translation Layers (FTL) to ease the erase-before-write problem. This dissertation addresses the two issues and consists of two parts.

The first part focuses on the white-box approaches that optimize the …

Automation Of Landmark Selection For Rodent Brain Mri-Histology Registration Using Thin-Plate Splines, Ayan Sengupta

School of Computing: Dissertations, Theses, and Student Research

Image registration is the process of aligning two different images of the same object taken at different times, at different orientations or using different instruments. This is common in medical applications since multiple modalities are used to image different parts of the body. This is an important early step in many diagnostic procedures such as change detection, monitoring tumor or quantifying spread of a disease. The widely used landmark based registration approach is tedious, time consuming, inconsistent and error prone. Furthermore, the standard schemes based on rigid and affine transformation can only describe global geometric differences between the objects of …

Simulation, Development And Deployment Of Mobile Wireless Sensor Networks For Migratory Bird Tracking, William P. Bennett Jr.

School of Computing: Dissertations, Theses, and Student Research

This thesis presents CraneTracker, a multi-modal sensing and communication system for monitoring migratory species at the continental level. By exploiting the robust and extensive cellular infrastructure across the continent, traditional mobile wireless sensor networks can be extended to enable reliable, low-cost monitoring of migratory species. The developed multi-tier architecture yields ecologists with unconventional behavior information not furnished by alternative tracking systems at such a large scale and for a low-cost. The simulation, development and implementation of the CraneTracker software system is presented. The system is shown effective through multiple proxy deployments on wildlife and has been operational for 10 months …

Routing Over The Interplanetary Internet, Joyeeta Mukherjee

School of Computing: Dissertations, Theses, and Student Research

Future space exploration demands a Space Network that will be able to connect spacecrafts with one another and in turn with Earth's terrestrial Internet and hence efficiently transfer data back and forth. The feasibility of this technology would enable common people to directly access telemetric data from distant planets and satellites. The concept of an Interplanetary Internet (IPN) is only in its incubation stage and considerable amount of common standards and research is required before widespread deployment can occur to make IPN feasible.

We provide a comprehensive survey that presents a picture of the current space networking technologies and architectures. …

Statistical Software Properties: Definition, Inference And Monitoring, Javier A. Darsie

School of Computing: Dissertations, Theses, and Student Research

Software properties define how software systems should operate. Specifying correct properties, however, can be difficult and expensive as it requires deep knowledge of the system's expected behavior and the environment in which it operates. Automated analysis techniques to infer properties from code or code executions can mitigate that cost, but are still unable to go beyond state properties and the simplest patterns of temporal properties. This limitation renders properties that sacrifice fault detection power.

To address this problem, we introduce a new type of software properties called \textit{statistical properties}, which characterize significant statistical relationships among the values of variables across …

Data Mining Of Protein Databases, Christopher Assi

School of Computing: Dissertations, Theses, and Student Research

Data mining of protein databases poses special challenges because many protein databases are non-relational whereas most data mining and machine learning algorithms assume the input data to be a relational database. Protein databases are non-relational mainly because they often contain set data types. We developed new data mining algorithms that can restructure non-relational protein databases so that they become relational and amenable for various data mining and machine learning tools. We applied the new restructuring algorithms to a pancreatic protein database. After the restructuring, we also applied two classification methods, such as decision tree and SVM classifiers and compared their …

On Heterogeneous User Demands In Peer-To-Peer Video Streaming Systems, Zhipeng Ouyang

School of Computing: Dissertations, Theses, and Student Research

A Peer-to-Peer (P2P) video streaming system usually consists of a large number of peers, which have heterogeneous physical properties. Orthogonal to the physical heterogeneity, there is another type of heterogeneity called demand heterogeneity. Namely, peers have their own demands on the quality and type of the streaming service. The problem of demand heterogeneity has received little attention and as a result current P2P video streaming systems cannot achieve satisfactory performance due to demand heterogeneity. In this dissertation, we study how to design efficient P2P video streaming systems with heterogeneous user demands.

First, we study the problem of heterogeneous user demands …

An Enhanced Self-Adaptive Mapreduce Scheduling Algorithm, Xiaoyu Sun

School of Computing: Dissertations, Theses, and Student Research

MapReduce is a framework for processing huge amounts of data in a distributed environment and Hadoop is Apache’s open source implementation of MapReduce, which is widely used. However, Hadoop’s performance is currently limited by its default task scheduler, which assumes that cluster nodes are homogeneous when estimating the task progress and choosing slow tasks for re-execution. In practice, the homogeneity assumption does not always hold. Longest Approximate Time to End (LATE) is a scheduling algorithm that takes heterogeneity into account. It, however, still depends on a static method to estimate the task execution time. As a result, neither Hadoop default …

Probabilistic Qos Analysis In Wireless Sensor Networks, Yunbo Wang

School of Computing: Dissertations, Theses, and Student Research

Emerging applications of wireless sensor networks (WSNs) require real-time quality of service (QoS) guarantees to be provided by the network. Traditional analysis work only focuses on the first-order statistics, such as the mean and the variance of the QoS performance. However, due to unique characteristics of WSNs, a cross-layer probabilistic analysis of QoS performance is essential. In this dissertation, a comprehensive cross-layer probabilistic analysis framework is developed to investigate the probabilistic evaluation and optimization of QoS performance provided by WSNs. In this framework, the distributions of QoS performance metrics are derived, which are natural tools to discover the probabilities to …

Cogtool-Helper: Leveraging Gui Functional Testing Tools To Generate Predictive Human Performance Models, Amanda Swearngin

School of Computing: Dissertations, Theses, and Student Research

Numerous tools and techniques for human performance modeling have been introduced in the field of human-computer interaction. With such tools comes the ability to model legacy applications. Models can be used to compare design ideas to existing applications, or to evaluate products against those of competitors. One such mod- eling tool, CogTool, allows user interface designers and analysts to mock up design ideas, demonstrate tasks, and obtain human performance predictions for those tasks. This is one step towards a simple and complete analysis process, but it still requires a large amount of manual work. Graphical user interface (GUI) testing tools …

Supporting Developer-Onboarding With Enhanced Resource Finding And Visual Exploration, Jianguo Wang

School of Computing: Dissertations, Theses, and Student Research

Understanding the basic structure of a code base and a development team are essential to get new developers up to speed in a software development project. Developers do so through the process of early experimentation with code and the creation of mental models of technical and social structures in a project. However, getting up-to-speed in a new project can be challenging due to difficulties in: finding the right place to begin explorations, expanding the focus to determine relevant resources for tasks, and identifying dependencies across project elements to gain a high-level overview of project structures. In this thesis, I first …

Improving Backup And Restore Performance For Deduplication-Based Cloud Backup Services, Stephen Mkandawire

School of Computing: Dissertations, Theses, and Student Research

The benefits provided by cloud computing and the space savings offered by data deduplication make it attractive to host data storage services like backup in the cloud. Data deduplication relies on comparing fingerprints of data chunks, and store them in the chunk index, to identify and remove redundant data, with an ultimate goal of saving storage space and network bandwidth.

However, the chunk index presents a bottleneck to the throughput of the backup operation. While several solutions to address deduplication throughput have been proposed, the chunk index is still a centralized resource and limits the scalability of both storage capacity …

Relational Neighborhood Inverse Consistency For Constraint Satisfaction: A Structure-Based Approach For Adjusting Consistency And Managing Propagation, Robert J. Woodward

School of Computing: Dissertations, Theses, and Student Research

Freuder and Elfe [1996] introduced Neighborhood Inverse Consistency (NIC) as a local consistency property defined on the values in the variables' domains of a Constraint Satisfaction Problem (CSP). Debruyne and Bessiere [2011] showed that enforcing NIC on binary CSPs is ineffective on sparse graph and too costly on dense graphs. In this thesis, we propose Relational Neighborhood Inverse Consistency (RNIC), an extension of NIC defined as a local consistency property on the tuples of the relations of a CSP. We characterize RNIC for both binary and non-binary CSPs, and propose an algorithm for enforcing it whose complexity is bounded by …

Location Cheating: A Security Challenge To Location-Based Social Network Services, Mai Ren

School of Computing: Dissertations, Theses, and Student Research

Location-based mobile social network services such as Foursquare and Gowalla have grown exponentially over the past several years. These location-based services utilize the geographical position to enrich user experiences in a variety of contexts, including location-based searching and location-based mobile advertising. To attract more users, the location-based mobile social network services provide real-world rewards to the user, when a user checks in at a certain venue or location. This gives incentives for users to cheat on their locations.

In this thesis, we investigate the threat of location cheating attacks, find the root cause of the vulnerability, and outline the possible …

Efficient Traffic Crash And Snow Complaint Gis System, Anthony B. Ngo

School of Computing: Dissertations, Theses, and Student Research

We describe the design and implementation of a traffic crash and snow complaint GIS system developed for the Lincoln Public Works department. We also describe a novel geocoding algorithm that was used to move data from the older Criminal Justice Information System, which is a relational database, to the new GIS system. In addition, we describe the implementation of several indexing algorithms that enable the system to efficiently answer rectangular range queries and queries about the relative locations of moving objects. Finally, in many applications (on-line analysis or mobile GIS), we need to execute spatial query efficiently (fast and small), …

Classification For Mass Spectra And Comprehensive Two-Dimensional Chromatograms, Xue Tian

School of Computing: Dissertations, Theses, and Student Research

Mass spectra contain characteristic information regarding the molecular structure and properties of compounds. The mass spectra of compounds from the same chemically related group are similar. Classification is one of the fundamental methodologies for analyzing mass spectral data. The primary goals of classification are to automatically group compounds based on their mass spectra, to find correlation between the properties of compounds and their mass spectra, and to provide a positive identification of unknown compounds.

This dissertation presents a new algorithm for the classification of mass spectra, the most similar neighbor with a probability-based spectrum similarity measure (MSN-PSSM). Experimental results demonstrate …

Molecular Dynamics Simulation Based On Hadoop Mapreduce, Chen He

School of Computing: Dissertations, Theses, and Student Research

Molecular Dynamics (MD) simulation is a computationally intensive application used in multiple fields. It can exploit a distributed environment due to inherent computational parallelism. However, most of the existing implementations focus on performance enhancement. They may not provide fault-tolerance for every time-step.

MapReduce is a framework first proposed by Google for processing huge amounts of data in a distributed environment. The simplicity of the programming model and fault- tolerance for node failure during run-time make it very popular not only for commercial applications but also in scientific computing.

In this thesis, we develop a novel communication-free and each time-step fault- …

Real-Time Divisible Load Scheduling For Cluster Computing, Anwar Mamat

School of Computing: Dissertations, Theses, and Student Research

Cluster computing has become an important paradigm for solving large-scale problems. However, as the size of a cluster increases, so does the complexity of resource management and maintenance. Therefore, automated performance control and re- source management are expected to play critical roles in sustaining the evolution of cluster computing. The current cluster scheduling practice is similar in sophistication to early supercomputer batch scheduling algorithms, and no consideration is given to desired quality-of-service (QoS) attributes. To fully avail the power of computational clusters, new scheduling algorithms that provides high performance, QoS assurance, fault-tolerance, energy savings and streamlined management of the cluster …

A Reservation-Based Smart Parking System, Hongwei Wang

School of Computing: Dissertations, Theses, and Student Research

In metropolitan areas, parking management influences drivers search time and cost for parking spaces, parking revenue, and traffic congestion. The wide deployment of wireless parking meters with sensing and communications capabilities allows the parking authority to monitor the state of each parking space in real time and optimize the parking management.

In this thesis, we study state-of-the-art parking policies in smart parking systems, and show that the smart parking system needs to be "smarter". Our design goals of the smart parking systems include: (1) simplify the operations of parking systems, (2) improve drivers' satisfaction, (3) increase parking revenue, and (4) …

Campus Grids: A Framework To Facilitate Resource Sharing, Derek J. Weitzel

School of Computing: Dissertations, Theses, and Student Research

It is common at research institutions to maintain multiple clusters. These might fulfill different needs and policies, or represent different owners or generations of hard- ware. Many of these clusters are under utilized while researchers at other departments may require these resources. This may be solved by linking clusters with grid mid- dleware. This thesis describes a distributed high throughput computing framework to link clusters without changing security or execution environments. The framework initially keeps jobs local to the submitter, overflowing if necessary to the campus, and regional grid. The framework is implemented spanning two campuses at the Holland Computing …