Computer Sciences Commons^™

Generating Minimal T-Wise Test Suites, Luis C. Gutierrez, Carlos Nieto, Francisco Zapata, Martine Ceberio

COURI Symposium Abstracts, Summer 2012

As the use of computing devices increases every day, users rely on the adequate functioning of software. When software is not tested properly, it can yield erroneous information or a complete failure of the system. The NIST estimates that defective software cost the United States economy close to $60 billion a year. Therefore, there is a need to develop software testing techniques that are time and cost effective. Fully testing software under all possible combinations of parameters values cannot be reduced. However, testing can focus on covering all combinations of subsets of parameters and empirical data shows that doing so …

How To Divide Students Into Groups So As To Optimize Learning: Towards A Solution To A Pedagogy-Related Optimization Problem, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

To enhance learning, it is desirable to also let students learn from each other, e.g., by working in groups. It is known that such groupwork can improve learning, but the effect strongly depends on how we divide students into groups. In this paper, based on a first approximation model of student interaction, we describe how to optimally divide students into groups so as to optimize the resulting learning. We hope that, by taking into account other aspects of student interaction, it will be possible to transform our solution into truly optimal practical recommendations.

Logistics Orchestration Modeling And Evaluation For Humanitarian Relief, Hoong Chuin Lau, Zhengping Li, Xin Du, Heng Jiang, Robert De Souza

Research Collection School Of Computing and Information Systems

This paper proposes an orchestration model for post-disaster response that is aimed at automating the coordination of scarce resources that minimizes the loss of human lives. In our setting, different teams are treated as agents and their activities are "orchestrated" to optimize rescue performance. Results from simulation are analysed to evaluate the performance of the optimization model.

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 …

Performance Evaluation Of Optimal Rate Allocation Models For Wireless Networks, Ryan Michael Padilla

Theses and Dissertations

Convex programming is used in wireless networks to optimize the sending or receiving rates of links or flows in a network. This kind of optimization problem is formulated into a rate allocation problem, where each node in the network will distributively solve the convex problem and all links or flows will converge to their optimal rate. The objective function and constraints of these problems are represented in a simplified model of contention, interference, and sending or receiving rates. The Partial Interference model is an optimal rate allocation model for use in wireless mesh networks that has been shown to be …

Generating Minimal Pair-Wise Covering Test Suites, Luis C. Gutierrez ^, Martine Ceberio *

COURI Symposium Abstracts, Spring 2012

Software is ubiquitous and needs to be reliable. Software testing therefore plays an important role in software development. Proper testing a software system informs about its quality and reliability so as to prevent unexpected behavior during system execution. One of the methods to prevent failures consists in testing a system under different input values, but when all possible input values are tested, an impractical number of test cases might result. In software testing, pair-wise testing is a combinatorial technique which uses combination of pair input values to generate test cases. Using pair-wise testing dramatically reduces the number of test cases, …

A Fitness Function Elimination Theory For Blackbox Optimization And Problem Class Learning, Gautham Anil

Electronic Theses and Dissertations

The modern view of optimization is that optimization algorithms are not designed in a vacuum, but can make use of information regarding the broad class of objective functions from which a problem instance is drawn. Using this knowledge, we want to design optimization algorithms that execute quickly (efficiency), solve the objective function with minimal samples (performance), and are applicable over a wide range of problems (abstraction). However, we present a new theory for blackbox optimization from which, we conclude that of these three desired characteristics, only two can be maximized by any algorithm. We put forward an alternate view of …

Networking And Security Solutions For Vanet Initial Deployment Stage, Baber Aslam

Electronic Theses and Dissertations

Vehicular ad hoc network (VANET) is a special case of mobile networks, where vehicles equipped with computing/communicating devices (called "smart vehicles") are the mobile wireless nodes. However, the movement pattern of these mobile wireless nodes is no more random, as in case of mobile networks, rather it is restricted to roads and streets. Vehicular networks have hybrid architecture; it is a combination of both infrastructure and infrastructure-less architectures. The direct vehicle to vehicle (V2V) communication is infrastructure-less or ad hoc in nature. Here the vehicles traveling within communication range of each other form an ad hoc network. On the other …

Coevolutionary Algorithms For The Optimization Of Strategies For Red Teaming Applications, Tirtha Ranjeet

Theses: Doctorates and Masters

Red teaming (RT) is a process that assists an organization in finding vulnerabilities in a system whereby the organization itself takes on the role of an “attacker” to test the system. It is used in various domains including military operations. Traditionally, it is a manual process with some obvious weaknesses: it is expensive, time-consuming, and limited from the perspective of humans “thinking inside the box”. Automated RT is an approach that has the potential to overcome these weaknesses. In this approach both the red team (enemy forces) and blue team (friendly forces) are modelled as intelligent agents in a multi-agent …

Optimization Of Pilot Tones Using Differential Evolution Algorithm In Mimo-Ofdm Systems, Muhammet Nuri̇ Seyman, Necmi̇ Taşpinar

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a differential evolution (DE) algorithm for optimizing the placement and power of the pilot tones that are utilized by a least square (LS) algorithm for channel estimation in multiple-input and multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. Computer simulations demonstrated that the performance of the LS algorithm was increased by optimizing the pilot tones with the DE algorithm instead of locating them orthogonally. We used the upper bound of the mean square error (MSE) as a fitness function of the DE algorithm for optimization tasks. With the use of an upper bound, it is not necessary …

Cross-Layer Throughput Optimization With Power Control In Sensor Networks, Maggie Xiaoyan Cheng, Xuan Gong, Lin Cai, Xiaohua Jia

Computer Science Faculty Research & Creative Works

In wireless sensor networks, transmission power has a significant impact on network throughput as wireless interference increases with transmission power, and interference negatively impacts the network throughput. in this paper, we try to improve the network throughput through cross-layer optimization. We first present two algorithms to compute the transmission power of each node with the objectives of minimizing the total transmission power and minimizing the total interference, respectively, from which we can obtain a network topology that ensures a connected path from each source to the sink; then, we compute the maximum achievable throughput from the obtained topology by using …

Modeling Wireless Networks For Rate Control, David C. Ripplinger

Theses and Dissertations

Congestion control algorithms for wireless networks are often designed based on a model of the wireless network and its corresponding network utility maximization (NUM) problem. The NUM problem is important to researchers and industry because the wireless medium is a scarce resource, and currently operating protocols such as 802.11 often result in extremely unfair allocation of data rates. The NUM approach offers a systematic framework to build rate control protocols that guarantee fair, optimal rates. However, classical models used with the NUM approach do not incorporate partial carrier sensing and interference, which can lead to significantly suboptimal performance when actually …

A Study On Facility Planning Using Discrete Event Simulation: Case Study Of A Grain Delivery Terminal, Sarah M. Asio

Department of Industrial and Management Systems Engineering: Dissertations, Theses, and Student Research

The application of traditional approaches to the design of efficient facilities can be tedious and time consuming when uncertainty and a number of constraints exist. Queuing models and mathematical programming techniques are not able to capture the complex interaction between resources, the environment and space constraints for dynamic stochastic processes. In the following study discrete event simulation is applied to the facility planning process for a grain delivery terminal. The discrete event simulation approach has been applied to studies such as capacity planning and facility layout for a gasoline station and evaluating the resource requirements for a manufacturing facility. To …

Automated, Parallel Optimization Algorithms For Stochastic Functions, Dheeraj Chahal

All Dissertations

The optimization algorithms for stochastic functions are desired specifically for real-world and simulation applications where results are obtained from sampling, and contain experimental error or random noise. We have developed a series of stochastic optimization algorithms based on the well-known classical down hill simplex algorithm. Our parallel implementation of these optimization algorithms, using a framework called MW, is based on a master-worker architecture where each worker runs a massively parallel program. This parallel implementation allows the sampling to proceed independently on many processors as demonstrated by scaling up to more than 100 vertices and 300 cores.
This framework is highly …

Multi-Channel Peer-To-Peer Streaming Systems As Resource Allocation Problems, Miao Wang

School of Computing: Dissertations, Theses, and Student Research

In the past few years, the Internet has witnessed the success of Peer-to-Peer (P2P) streaming technology, which has attracted millions of users. More recently, commercial P2P streaming systems have begun to support multiple channels and a user in such systems is allowed to watch more than one channel at a time. We refer to such systems as multi-channel P2P streaming systems. In this dissertation, we focus on designing multi-channel P2P streaming systems with the goal of providing optimal streaming quality for all channels, termed as system-wide optimal streaming quality. Specifically, we design the systems from the perspective of how to …

A Two-View Learning Approach For Image Tag Ranking, Jinfeng Zhuang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Tags of social images play a central role for text-based social image retrieval and browsing tasks. However, the original tags annotated by web users could be noisy, irrelevant, and often incomplete for describing the image contents, which may severely deteriorate the performance of text-based image retrieval models. In this paper, we aim to overcome the challenge of social tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view learning approach. It can effectively exploit both textual and visual contents of social images to discover the complicated relationship between tags and images. Unlike the …

Algorithms For Training Large-Scale Linear Programming Support Vector Regression And Classification, Pablo Rivas Perea

Open Access Theses & Dissertations

The main contribution of this dissertation is the development of a method to train a Support Vector Regression (SVR) model for the large-scale case where the number of training samples supersedes the computational resources. The proposed scheme consists of posing the SVR problem entirely as a Linear Programming (LP) problem and on the development of a sequential optimization method based on variables decomposition, constraints decomposition, and the use of primal-dual interior point methods. Experimental results demonstrate that the proposed approach has comparable performance with other SV-based classifiers. Particularly, experiments demonstrate that as the problem size increases, the sparser the solution …

Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a novel method for unsupervised change detection in multi-temporal satellite images by using multiobjective cost function optimization via genetic algorithm (GA). The spatial image grid of the input multi-temporal satellite images is divided into two distinct regions, representing ``changed'' and ``unchanged'' regions between input images, via the intermediate change detection mask produced by the GA. The dissimilarity of pixels of ``changed'' regions and similarity of pixels of ``unchanged'' regions between input multi-temporal images are measured using image quality metrics which consider correlation, spectral distortion, radiometric distortion, and contrast distortion. The contextual information of each pixel …

Packing Virtual Machines Onto Servers, David Luke Wilcox

Theses and Dissertations

Data centers consume a significant amount of energy. This problem is aggravated by the fact that most servers and desktops are underutilized when powered on, and still consume a majority of the energy of a fully utilized computer even when idle This problem would be much worse were it not for the growing use of virtual machines. Virtual machines allow system administrators to more fully utilize hardware capabilities by putting more than one virtual system on the same physical server. Many times, virtual machines are placed onto physical servers inefficiently. To address this inefficiency, I developed a new family of …

A Species-Conserving Genetic Algorithm For Multimodal Optimization, Michael Scott Brown

CCAC Theses and Dissertations

The problem of multimodal functional optimization has been addressed by much research producing many different search techniques. Niche Genetic Algorithms is one area that has attempted to solve this problem. Many Niche Genetic Algorithms use some type of radius. When multiple optima occur within the radius, these algorithms have a difficult time locating them. Problems that have arbitrarily close optima create a greater problem. This paper presents a new Niche Genetic Algorithm framework called Dynamic-radius Species-conserving Genetic Algorithm. This new framework extends existing Genetic Algorithm research.

This new framework enhances an existing Niche Genetic Algorithm in two ways. As the …

The Impact Of Overfitting And Overgeneralization On The Classification Accuracy In Data Mining, Huy Nguyen Anh Pham

LSU Doctoral Dissertations

Current classification approaches usually do not try to achieve a balance between fitting and generalization when they infer models from training data. Such approaches ignore the possibility of different penalty costs for the false-positive, false-negative, and unclassifiable types. Thus, their performances may not be optimal or may even be coincidental. This dissertation analyzes the above issues in depth. It also proposes two new approaches called the Homogeneity-Based Algorithm (HBA) and the Convexity-Based Algorithm (CBA) to address these issues. These new approaches aim at optimally balancing the data fitting and generalization behaviors of models when some traditional classification approaches are used. …

An Approach Based On Particle Swarm Computation To Study The Nanoscale Dg Mosfet-Based Circuits, Fayacl Djeffal, Toufik Bendib, Redha Benzid, Abdelhamid Benhaya

Turkish Journal of Electrical Engineering and Computer Sciences

The analytical modeling of nanoscale Double-Gate MOSFETs (DG) requires generally several necessary simplifying assumptions to lead to compact expressions of current-voltage characteristics for nanoscale CMOS circuits design. Further, progress in the development, design and optimization of nanoscale devices necessarily require new theory and modeling tools in order to improve the accuracy and the computational time of circuits' simulators. In this paper, we propose a new particle swarm strategy to study the nanoscale CMOS circuits. The latter is based on the 2-D numerical Non-Equilibrium Green's Function (NEGF) simulation and a new extended long channel DG MOSFET compact model. Good agreement between …

Stochastic Optimization For Learning-Based Super-Resolution: Algorithms And Applications, Jun Zheng

Open Access Theses & Dissertations

Human beings get much of their information visually and depend on perception of images for many critical tasks, such as object identification, medical image analysis, photography, etc. In many visual-based applications, higher resolution images are required for perceiving and receiving critical information. A high resolution image can contribute to a better identification of a suspect's face, or a more accurate localization of a tumor in a mammogram, or a more pleasing view in high definition television, and so on. However, it is hard to obtain the high resolution images needed for some applications, for example, the cost of sensors increases …

Redtnet: A Network Model For Strategy Games, Philip Hingston, Mike Preuss, Daniel Spierling

Research outputs pre 2011

In this work, we develop a simple, graph-based framework, RedTNet, for computational modeling of strategy games and simulations. The framework applies the concept of red teaming as a means by which to explore alternative strategies. We show how the model supports computer-based red teaming in several applications: realtime strategy games and critical infrastructure protection, using an evolutionary algorithm to automatically detect good and often surprising strategies.

Joint Routing And Link Rate Allocation Under Bandwidth And Energy Constraints In Sensor Networks, Maggie Cheng, Xuan Gong, Lin Cai

Computer Science Faculty Research & Creative Works

In sensor networks, both energy and bandwidth are scarce resources. in the past, many energies efficient routing algorithms have been devised in order to maximize network lifetime, in which wireless link bandwidth has been optimistically assumed to be sufficient. This article shows that ignoring the bandwidth constraint can lead to infeasible routing solutions. as energy constraint affects how data should be routed, link bandwidth also affects not only the routing topology but also the allowed data rate on each link. in this paper, we discuss the sufficient condition on link bandwidth that makes a routing solution feasible, then provide mathematical …

An Optimization Approach For The Cascade Vulnerability Problem, Christian Servin

Open Access Theses & Dissertations

In inter-connected systems, where several computers share information with each other, problems may arise when inappropriate information starts to flow through. For example, let us consider a simple scenario of a university composed of three departments: payroll, financial aid, and academic services. We know that the payroll department deals with sensitive information, such as social security numbers, dates of birth, amounts of wages, etc. The financial aid department may use information that payroll owns. Similarly, the academic department communicates with the financial aid department. An intruder can take advantage of this network connectivity and create an inappropriate flow of information …

Softcomputing Identification Techniques Of Asynchronous Machine Parameters: Evolutionary Strategy And Chemotaxis Algorithm, Nouri Benaïdja

Turkish Journal of Electrical Engineering and Computer Sciences

Softcomputing techniques are receiving attention as optimisation techniques for many industrial applications. Although these techniques eliminate the need for derivatives computation, they require much work to adjust their parameters at the stage of research and development. Issues such as speed, stability, and parameters convergence remain much to be investigated. This paper discusses the application of the method of reference model to determine parameters of asynchronous machines using two optimisation techniques. Softcomputing techniques used in this paper are evolutionary strategy and the chemotaxis algorithm. Identification results using the two techniques are presented and compared with respect to the conventional simplex technique …

Parameter Identification Of A Separately Excited Dc Motor Via Inverse Problem Methodology, Mounir Hadef, Mohamed Rachid Mekideche

Turkish Journal of Electrical Engineering and Computer Sciences

Identification is considered to be among the main applications of inverse theory and its objective for a given physical system is to use data which is easily observable, to infer some of the geometric parameters which are not directly observable. In this paper, a parameter identification method using inverse problem methodology is proposed. The minimisation of the objective function with respect to the desired vector of design parameters is the most important procedure in solving the inverse problem. The conjugate gradient method is used to determine the unknown parameters, and Tikhonov's regularization method is then used to replace the original …

Optimizing Product Line Designs: Efficient Methods And Comparisons, Alexandre Belloni, Robert Freund, Matthew Selove, Duncan Simester

Business Faculty Articles and Research

We take advantage of recent advances in optimization methods and computer hardware to identify globally optimal solutions of product line design problems that are too large for complete enumeration. We then use this guarantee of global optimality to benchmark the performance of more practical heuristic methods. We use two sources of data: (1) a conjoint study previously conducted for a real product line design problem, and (2) simulated problems of various sizes. For both data sources, several of the heuristic methods consistently find optimal or near-optimal solutions, including simulated annealing, divide-and-conquer, product-swapping, and genetic algorithms.

Utility-Based Adaptation In Mission-Oriented Wireless Sensor Networks, Sharanya Eswaran, Archan Misra, Thomas La Porta

Research Collection School Of Computing and Information Systems

This paper extends the distributed network utility maximization (NUM) framework to consider the case of resource sharing by multiple competing missions in a military-centric wireless sensor network (WSN) environment. Prior work on NUM-based optimization has considered unicast flows with sender-based utilities in either wireline or wireless networks. We extend the NUM framework to consider three key new features observed in mission-centric WSN environments: i) the definition of an individual mission's utility as a joint function of data from multiple sensor sources ii) the consumption of each senders (sensor) data by multiple receivers (missions) and iii) the multicast-tree based dissemination of …