OS and Networks Commons^™

Astrophobia: A 3d Multiplayer Space Combat Game With Linear Entity Interpolation, Luke Larson

Computer Science and Software Engineering

Astrophobia is a Descent-like 3D networked multiplayer space combat game with linear entity interpolation (client-side animation between game-state packets to give the illusion of continuous game updates) similar to entity interpolation implemented in Valve Software’s Source engine. Additionally, Astrophobia procedurally generates unique levels, has zero-gravity physics, ship and projectile wall bouncing, hit detection, OpenGL 3D graphics, Phong lighting, ship model and texture, and a simple HUD that provides visualization of health points, aiming crosshair, and player scoreboard.

A Secure And Effective Anonymous User Authentication Scheme For Roaming Service In Global Mobility Networks, Fengtong Wen, Willy Susilo, Guomin Yang

Research Collection School Of Computing and Information Systems

In global mobility networks, anonymous user authentication is an essential task for enabling roaming service. In a recent paper, Jiang et al. proposed a smart card based anonymous user authentication scheme for roaming service in global mobility networks. This scheme can protect user privacy and is believed to have many abilities to resist a range of network attacks, even if the secret information stored in the smart card is compromised. In this paper, we analyze the security of Jiang et al.’s scheme, and show that the scheme is in fact insecure against the stolen-verifier attack and replay attack. Then, we …

Coupling Alignments With Recognition For Still-To-Video Face Recognition, Zhiwu Huang, X. Zhao, S. Shan, R. Wang, X. Chen

Research Collection School Of Computing and Information Systems

The Still-to-Video (S2V) face recognition systems typically need to match faces in low-quality videos captured under unconstrained conditions against high quality still face images, which is very challenging because of noise, image blur, low face resolutions, varying head pose, complex lighting, and alignment difficulty. To address the problem, one solution is to select the frames of `best quality' from videos (hereinafter called quality alignment in this paper). Meanwhile, the faces in the selected frames should also be geometrically aligned to the still faces offline well-aligned in the gallery. In this paper, we discover that the interactions among the three tasks-quality …

Client-Based Qos Monitoring And Evaluation Architecture For Network Infrastructure And Services, Ammar Mohammed Kamel

Dissertations

Providing an efficient Quality-of-Service (QoS) measurement model is a challenging problem in today’s mobile computing and telecommunications networks. Currently, most of QoS techniques utilize service measurements that are collected by the network elements (i.e., network-side monitoring) to evaluate the network performance. However, this process does not take into account the service performance from the clients' perspective and might contradict with the Service Level Agreement (SLA). In order to overcome the limitations of service-side QoS monitoring, a number of research studies have been conducted to present alternative architectures and algorithms for client-side QoS service assessment in computer networks. The client-side QoS …

In Perfect Xen, A Performance Study Of The Emerging Xen Scheduler, Ryan Hnarakis

Master's Theses

Fifty percent of Fortune 500 companies trust Xen, an open-source bare-metal hypervisor, to virtualize their websites and mission critical services in the cloud. Providing superior fault tolerance, scalability, and migration, virtualization allows these companies to run several isolated operating systems simultaneously on the same physical server. These isolated operating systems, called virtual machines, require a virtual traffic guard to cooperate with one another. This guard known as the Credit2 scheduler along with the newest Xen hypervisor was recently developed to supersede the older schedulers. Since wasted CPU cycles can be costly, the Credit2 prototype must undergo significant performance validation before …

Automatic Domain Identification For Linked Open Data, Sarasi Lalithsena, Pascal Hitzler, Amit P. Sheth, Prateek Jain

Kno.e.sis Publications

Linked Open Data (LOD) has emerged as one of the largest collections of interlinked structured datasets on the Web. Although the adoption of such datasets for applications is increasing, identifying relevant datasets for a specific task or topic is still challenging. As an initial step to make such identification easier, we provide an approach to automatically identify the topic domains of given datasets. Our method utilizes existing knowledge sources, more specifically Freebase, and we present an evaluation which validates the topic domains we can identify with our system. Furthermore, we evaluate the effectiveness of identified topic domains for the purpose …

Semantics-Empowered Big Data Processing With Applications, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

We discuss the nature of Big Data and address the role of semantics in analyzing and processing Big Data that arises in the context of Physical-Cyber-Social Systems. We organize our research around the Five Vs of Big Data, where four of the Vs are harnessed to produce the fifth V - value. To handle the challenge of Volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision-making. To handle the challenge of Variety, we resort to the use of semantic models and annotations of data so that much of the intelligent processing …

Towards Automated Network Configuration Management, Khalid Elmansor

College of Computing and Digital Media Dissertations

Modern networks are designed to satisfy a wide variety of competing goals related to network operation requirements such as reachability, security, performance, reliability and availability. These high level goals are realized through a complex chain of low level configuration commands performed on network devices.

As networks become larger, more complex and more heterogeneous, human errors become the most significant threat to network operation and the main cause of network outage. In addition, the gap between high-level requirements and low-level configuration data is continuously increasing and difficult to close. Although many solutions have been introduced to reduce the complexity of configuration …

Understanding The Genetic Makeup Of Linux Device Drivers, Peter Senna Tschudin, Laurent Reveillere, Lingxiao Jiang, David Lo, Julia Lawall

Research Collection School Of Computing and Information Systems

No abstract provided.

City Notifications As A Data Source For Traffic Management, Pramod Anantharam, Biplav Srivastava

Kno.e.sis Publications

A common problem for cities of developing countries like India in managing traffic is the lack of basic automated instrumentation to track road conditions or vehicle locations. Still, to help their citizens make informed travel decisions based on changing city dynamics; many cities have an authorized, city-initiated, notification service in place to alert subscribing commuters about road conditions. Here, alternative means may be used to create informal textual notifications e.g., inputs from field personnel, citizen updates, and pre-authorized events from city calendar. In this paper, we show that collections of such notifications, when processed with information extraction techniques, can turn …

The Future Of Research And Collaboration – The Dedicated Science Network, Andrew Sherman, David Galassi, William Boos, Daisuke Nagai

Yale Day of Data

This poster describes the new high-speed Science Network and Science DMZ at Yale that will be used for data movement, data sharing, and scientific collaboration.

A Statistical And Schema Independent Approach To Identify Equivalent Properties On Linked Data, Kalpa Gunaratna, Krishnaprasad Thirunarayan, Prateek Jain, Amit P. Sheth, Sanjaya Wijeratne

Kno.e.sis Publications

Linked Open Data (LOD) cloud has gained significant attention in the Semantic Web community recently. Currently it consists of approximately 295 interlinked datasets with over 50 billion triples including 500 million links, and continues to expand in size. This vast source of structured information has the potential to have a significant impact on knowledge-based applications. However, a key impediment to the use of LOD cloud is limited support for data integration tasks over concepts, instances, and properties. Efforts to address this limitation over properties have focused on matching data-type properties across datasets; however, matching of object-type properties has not received …

A Robust Rgbd Slam System For 3d Environment With Planar Surfaces, Po-Chang Su, Ju Shen, Sen-Ching S. Cheung

Computer Science Faculty Publications

With the increasing popularity of RGB-depth (RGB-D) sensors such as the Microsoft Kinect, there have been much research on capturing and reconstructing 3D environments using a movable RGB-D sensor. The key process behind these kinds of simultaneous location and mapping (SLAM) systems is the iterative closest point or ICP algorithm, which is an iterative algorithm that can estimate the rigid movement of the camera based on the captured 3D point clouds. While ICP is a well-studied algorithm, it is problematic when it is used in scanning large planar regions such as wall surfaces in a room. The lack of depth …

Mining Effective Multi-Segment Sliding Window For Pathogen Incidence Rate Prediction, Lei Duan, Changjie Tang, Xiasong Li, Guozhu Dong, Xianming Wang, Jie Zuo, Min Jiang, Zhongqi Li, Yongqing Zhang

Kno.e.sis Publications

Pathogen incidence rate prediction, which can be considered as time series modeling, is an important task for infectious disease incidence rate prediction and for public health. This paper investigates the application of a genetic computation technique, namely GEP, for pathogen incidence rate prediction. To overcome the shortcomings of traditional sliding windows in GEP-based time series modeling, the paper introduces the problem of mining effective sliding window, for discovering optimal sliding windows for building accurate prediction models. To utilize the periodical characteristic of pathogen incidence rates, a multi-segment sliding window consisting of several segments from different periodical intervals is proposed and …

Types Of Property Pairs And Alignment On Linked Datasets - A Preliminary Analysis, Kalpa Gunaratna, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Dataset publication on the Web has been greatly influenced by the Linked Open Data (LOD) project. Many interlinked datasets have become freely available on the Web creating a structured and distributed knowledge representation. Analysis and aligning of concepts and instances in these interconnected datasets have received a lot of attention in the recent past compared to properties. We identify three different categories of property pairs found in the alignment process and study their relative distribution among well known LOD datasets. We also provide comparative analysis of state-of-the-art techniques with regard to different categories, highlighting their capabilities. This could lead to …

Reaper – Toward Automating Mobile Cloud Communication, Daniel R. Ward

LSU New Orleans Theses and Dissertations

Mobile devices connected to cloud based services are becoming a mainstream method of delivery up-to-date and context aware information to users. Connecting mobile applications to cloud service require significant developer effort. Yet this communication code usually follows certain patterns, varying accordingly to the specific type of data sent and received from the server. By analyzing the causes of theses variations, we can create a system that can automate the code creation for communication from a mobile device to a cloud server. To automate code creation, a general pattern must extracted. This general solution can then be applied to any database …

On Fuzzy Soft Matrix Based On Reference Function, Florentin Smarandache, Said Broumi, Mamoni Dhar

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we study fuzzy soft matrix based on reference function. Firstly, we define some new operations such as fuzzy soft complement matrix and trace of fuzzy soft matrix based on reference function. Then, we introduced some related properties, and some examples are given. Lastly, we define a new fuzzy soft matrix decision method based on reference function.

An Agent-Based Network Analytic Perspective On The Evolution Of Complex Adaptive Supply Chain Networks, Loganathan Ponnanbalam, A. Tan, Xiuju Fu, Xiaofeng Yin, Zhaoxia Wang, Rick S. M. Goh

Research Collection School Of Computing and Information Systems

Supply chain networks of modern era are complex adaptive systems that are dynamic and highly interdependent in nature. Business continuity of these complex systems depend vastly on understanding as to how the supply chain network evolves over time (based on the policies it adapts), and identifying the susceptibility of the evolved networks to external disruptions. The objective of this article is to illustrate as to how an agent-based network analytic perspective can aid this understanding on the network-evolution dynamics, and identification of disruption effects on the evolved networks. To this end, we developed a 4-tier agent based supply chain model …

An Agent-Based Network Analytic Perspective On The Evolution Of Complex Adaptive Supply Chain Networks, L. Ponnambalam, A. Tan, X. Fu, X. F. Yin, Zhaoxia Wang, R. S. Goh

Research Collection School Of Computing and Information Systems

Supply chain networks of modern era are complex adaptive systems that are dynamic and highly interdependent in nature. Business continuity of these complex systems depend vastly on understanding as to how the supply chain network evolves over time (based on the policies it adapts), and identifying the susceptibility of the evolved networks to external disruptions. The objective of this article is to illustrate as to how an agent-based network analytic perspective can aid this understanding on the network-evolution dynamics, and identification of disruption effects on the evolved networks. To this end, we developed a 4-tier agent based supply chain model …

From Questions To Effective Answers: On The Utility Of Knowledge-Driven Querying Systems For Life Sciences Data, Amir H. Asiaee, Prashant Doshi, Todd Minning, Satya S. Sahoo, Priti Parikh, Amit P. Sheth, Rick L. Tarleton

Kno.e.sis Publications

We compare two distinct approaches for querying data in the context of the life sciences. The first approach utilizes conventional databases to store the data and provides intuitive form-based interfaces to facilitate querying of the data, commonly used by the life science researchers that we study. The second approach utilizes a large OWL ontology and the same datasets associated as RDF instances of the ontology. Both approaches are being used in parallel by a team of cell biologists in their daily research activities, with the objective of gradually replacing the conventional approach with the knowledge-driven one. We describe several benefits …

Crisis Response Coordination In Online Communities, Hemant Purohit

Kno.e.sis Publications

During recent crises, citizens (sensors) are increasingly using social media to share variety of information- situation on the ground, emerging needs, donation offers, damage, etc. In such an evolving ad-hoc community, how can we extract actionable nuggets from the social media streams to aid relief efforts? This doctoral consortium presentation summarizes a framework to analyze social data and manage information to assist coordination by focusing on three important questions to answer: Whom to coordinate with, Why to coordinate and How to coordinate, with exemplary insights for needs and availability from the recent disaster events.

Demo: Approximate Semantic Matching In The Collider Event Processing Engine, Souleiman Hasan, Kalpa Gunaratna, Yongrui Qin, Edward Curry

Kno.e.sis Publications

This demo presents a use case from the energy management domain. It builds upon previous work on approximate semantic matching of heterogeneous events and compares two semantic matching scenarios: exact and approximate. It illustrates how a large number of exact matching event subscriptions are needed to match heterogeneous power consumption events. It then demonstrates how a small number of approximate semantic matching subscriptions are needed but possibly with a lower true positives/negatives performance. The demo is delivered via the COLLIDER approximate event processing engine currently under development in DERI.

Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni

Research Collection School Of Computing and Information Systems

The Last Mile Problem (LMP) refers to the provision of travel service from thenearest public transportation node to a home or office. We study the supply side of thisproblem in a stochastic setting, with batch demands resulting from the arrival of groupsof passengers at rail stations or bus stops who request last-mile service. Closed-formbounds and approximations are derived for the performance of Last Mile TransportationsSystems as a function of the fundamental design parameters of such systems. An initialset of results is obtained for the case in which a fleet of vehicles of unit capacity providesthe Last Mile service and each …

Spring­11: Pdc In Cs1/2 And A Mobile/Cloud Intermediate Mobile/Cloud Intermediate Software Design Course, Joseph P. Kaylor, Konstantin Läufer, Chandra N. Sekharan, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Recent changes in the environment of Loyola University Chicago’s Department of Computer Science include a better differentiation of our four undergraduate majors, growing interest in computing among science majors, and an increased demand for graduates with mobile and cloud skills. In our continued effort to incorporate parallel and distributed computing topics into the undergraduate curriculum, we are focusing on these three existing courses:

CS1: In response to a request from the physics department, we started to offer a CS1 section aimed at majors in physics and other hard sciences this spring semester. This section includes some material on numerical methods …

Building Capable, Energy-Efficient, Flexible Visualization And Sensing Clusters From Commodity Tablets, Thomas Delgado Dias, Xian Yan, Konstantin Läufer, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

We explore the application of clusters of commodity tablet devices to problems spanning a “trilogy” of concerns: visualization, sensing, and computation. We conjecture that such clusters provide a low-cost, energy-efficient, flexible, and ultimately effective platform to tackle a wide range of problems within this trilogy. This is a work in progress, and we now elaborate our position and give a preliminary status report.

A wide range of Android tablet devices are available in terms of price and capabilities. “You get what you pay for” w.r.t. display resolution, sensors, and chipset---corresponding to the trilogy. $200 gets one a 1280x800-pixel touch display, …

Network Technologies Used To Aggregate Environmental Data, Paul Stasiuk, Konstantin Läufer, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

The goal of the Loyola Weather Service (lws) project is to design and build a system of functioning environmental monitoring widgets that can intelligently and autonomously control the environment around them based on set thresholds and triggers. The widgets will also have the ability to aggregate their data and easily display this data in various ways: through a user interface in the room that the widget is placed, via a web application, and programmatically via a RESTful web service.

Behind The Magical Numbers: Hierarchical Chunking And The Human Working Memory Capacity, Guoqi Li, Ning Ning, Kiruthika Ramanathan, Wei He, Li Pan, Luping Shi

Research Collection School Of Computing and Information Systems

To explore the influence of chunking on the capacity limits of working memory, a model for chunking in sequential working memory is proposed, using hierarchical bidirectional inhibition-connected neural networks with winnerless competition. With the assumption of the existence of an upper bound to the inhibitory weights in neurobiological networks, it is shown that chunking increases the number of memorized items in working memory from the "magical number 7" to 16 items. The optimal number of chunks and the number of the memorized items in each chunk are the "magical number 4".

An Online Algorithm For The 2-Server Problem On The Line With Improved Competitiveness, Lucas Adam Bang

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this thesis we present a randomized online algorithm for the 2-server problem on the line, named R-LINE (for Randomized Line). This algorithm achieves the lowest competitive ratio of any known randomized algorithm for the 2-server problem on the line.

The competitiveness of R-LINE is less than 1.901. This result provides a significant improvement over the previous known competitiveness of 155/78 (approximately 1.987), by Bartal, Chrobak, and Larmore, which was the first randomized algorithm for the 2-server problem one the line with competitiveness less than 2. Taking inspiration from this algorithm,we improve this result by utilizing ideas from T-theory, game …

A Semantic Situation Awareness Framework For Indoor Cyber-Physical Systems, Pratikkumar Desai

Kno.e.sis Publications

Recently, the domain of cyber-physical systems (CPSs) has emerged as a successor to the traditional embedded systems and the wireless sensor networks. The relatively new cyber-physical domain offers tight integration of control, communication and computation components to develop advanced web based application in various heterogeneous domains such as health care, disaster management, automation and environment monitoring. The applications of indoor CPSs include remote patient monitoring, smart home, etc. with focus on situation awareness via event identification from context information. The principal challenges associated with the development of situation awareness applications include uncertainty in contextual data, incomplete domain knowledge, interoperability between …

Operating System Scheduling: Linux Preemptive Scheduling Algorithms, Andrew Brand

Honors Capstones

Capstone submitted as a graduation requirement for the BSU Honors Program.