Total: $35,363,399 ## Other Years # Current Computer Science Research Projects (by faculty) The funded projects listed below are active projects and the funded running total for the active projects is on the left navigational menu. SHF: Small: Towards Regulatory Compliance Software Engineering with UCONLEGAL Ana Anton ; Jon Doyle$400,000 by the National Science Foundation
08/ 1/2012 - 07/31/2014

Software engineers need improved tools and methods for translating complex, changing legal regulations into workable information technology systems. Compliance with legal requirements is an essential element in system governed by regulations. The research proposed herein advances the cutting edge for creating more accurate, efficient, and reliable Regulatory Compliance Software Engineering (RCSE), resulting in significantly more trustworthy systems. Software systems that handle sensitive information records must comply with regulations. Access control models, given their ability to represent the components that constitute the access rules in legal texts, can aid in modeling these regulations. Based on our analysis of the HIPAA Privacy Rule, we have identified the components needed to model access rules that comply with regulations. The HIPAA Privacy Rule limits access to and usage of health records. In this proposal, we propose to create a formal model for UCONLEGAL, an extension to UCONABC with components to model purposes, cross-references, exceptions, conditions, and logs for expressing the access and usage rules in HIPAA. We have identified seven types of conditions specific to HIPAA and include them in UCONLEGAL. In this project we propose to validate UCONLEGAL within the context of financial regulations, and reason about the science of ensuring regulatory compliance by developing a formal usage control model that applies for three domains: health care, finance, and homeland security ? specifically for the Information Sharing Environment. We plan to develop automated testers and verifiers to ensure the safety and reliability properties of critical systems.

REU Site: Interactive and Intelligent Media
Tiffany Barnes

$359,999 by National Science Foundation 04/ 1/2013 - 03/31/2016 The REU Site at NC State University will immerse a diverse group of undergraduates in a vibrant research community of faculty and graduate students working on cutting-edge games, intelligent tutors, and mobile applications. We will recruit students from underrepresented groups and colleges and universities with limited research opportunities through the STARS Alliance, an NSF-funded national consortium of institutions dedicated to broadening participation in computing. Using the Affinity Research Groups and STARS Training for REUs models, we will engage faculty and graduate student mentors with undergraduates to create a supportive culture of collaboration while promoting individual contributions to research through just-in-time training for both mentors and students throughout the summer. Type I: Collaborative Research: FRABJOUS CS - Framing a Rigorous Approach to Beauty and Joy for Outreach to Underrepresented Students in Computing at Scale Tiffany Barnes$352,831 by National Science Foundation
02/ 1/2013 - 08/31/2014

In this FRABJOUS CS project, we will prepare 60 high school teachers to teach the Beauty and Joy of Computing (BJC) Computer Science Principles curriculum. The BJC course is a rigorous introductory computing course that highlights the meaning and applications of computing, while introducing low-threshold programming languages Snap-Scratch, GameMaker and AppInventor. BJC is informed and inspired by the Exploring Computer Science curriculum, that was explicitly designed to channel the interests of urban HS students with ?culturally relevant and meaningful curriculum? [Goode 2011][Margolis 2008]. The BJC course uses collaborative classroom methods including pair learning, and student-selected projects are geared toward leveraging students? knowledge of social media, games, devices, and the internet. At UNC Charlotte in 2010 and 2011, PI Barnes engaged college students in supporting the BJC course, and in after-school outreach and summer camps that excite middle and high school students about this curriculum at different levels. The project engages three university faculty members and 6 college students to help the high school teachers build a Computer Science Teachers Association chapter and provide ongoing professional development and support for the BJC course. The project also engages high school teachers and an education researcher to help refine and enriches the BJC curriculum to be easier to adopt and teach in high schools.

CAREER: Educational Data Mining for Student Support in Interactive Learning Environment
Tiffany Barnes

$237,770 by UNC Charlotte/NSF 11/ 1/2013 - 06/30/2014 Creating intelligent learning technologies from data has unique potential to transform the American educational system, by building a low cost way to adapt learning environments to individual students, while informing research on human learning. This project will create the technology for a new generation of data-driven intelligent tutors, enabling the rapid creation of individualized instruction to support learning in science, technology, engineering, and mathematics (STEM) fields. This has the potential to make individualized learning support accessible for a broad audience, from children to adults, including students that are traditionally underrepresented in STEM fields. This project will (1) develop computational methods to derive cognitive models from data that can be used to support individual learners through guidance, feedback, and help; (2) develop approaches to providing student support that leverage data to provide hints and guidance based on information such as frequency of student responses, probability of future errors, and solution efficiency; (3) develop interactive visualization tools for teachers to learn from student data in real time, to allow teachers and instructional designers to tailor instruction to address actual, rather than perceived, student problem areas; and (4) conduct formal empirical evaluations of the pedagogical effectiveness of our student support. Our software will construct adaptive support for teaching and learning in logic, discrete mathematics, and other STEM domains using a data-driven approach. From the extensive but tractable student performance data in computer-aided learning environments, we will automatically construct student cognitive models. Our cognitive models will build on our prior work using Markov Decision Processes and dimensionality reduction methods that leverage past data to assess student performance, direct a studentâ€™s learning path, and provide contextualized hints. We will use machine learning techniques to expand our problem-specific models into more general cognitive models to bootstrap the construction of new tutors and learn about student learning. For teachers and learning researchers, we will build a web-based visualization and analysis tool to graphically and interactively model student solutions annotated with performance data that reflects frequency, tendency to commit future errors, and closeness to a final solution. Through our new tutors and tools we will conduct experiments to understand student learning in a variety of contexts and domains, including logic, algebra, and chemistry. We will engage a team of diverse students and colleagues to bring interdisciplinary expertise to our research and share our findings broadly. This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). DO 2 Task 3.3 - Bass John Bass$43,978 by LAS
09/13/2013 - 09/30/2014

DO 2 Task 3.3 activities

Developing a K-5 Computer Science Curriculum
Kristy Boyer

$14,038 by Wake County Public School Systems (WCPSS) 01/ 1/2014 - 05/15/2014 While great resources have been committed to developing computer science curricula at the university and high school levels, much less time has been devoted to developing curricula for younger students. The time is ripe to extend effective computer science pedagogy into the elementary realm. This project will develop and pilot a six-week elementary computer science curriculum focusing on problem solving, creativity, and computer science principles DO 2 Task 3.6 - Doyle Jon Doyle$46,904 by Laboratory for Analytic Sciences
09/13/2013 - 09/30/2014

DO 2 task 3.6 activities

NeTS: JUNO: Service Offering Model and Versatile Network Resource Grooming for Optical Packet and Circuit Integrated Networks
Rudra Dutta

$291,956 by National Science Foundation (NSF) 04/ 1/2014 - 03/31/2017 The explosive growth in bandwidth represented by advances in optical communication and networking technologies has underpinned the increasing reach and reliability of the Internet in the last two decades. However, the potential impact of increasingly sophisticated recent advances in optical technology, such as rapid switching and elastic wavelengths have not yet been realized. The main cause of this is that such technology, while possible to integrate into the data plane of planetary networking, is difficult to accommodate in the current planning, management, and control strategies. We propose in this project to work hand-in-hand with collaborating researchers from NICT, Japan, who are working to realize a novel technology of hybrid optical packet/circuit switching. Such a technology could be immensely useful to large transport network operators, but there are no existing algorithms that can easily determine how a provider can provision their resources between the circuit and packet possibilities on an ongoing dynamic basis. We envision a novel approach to this problem, where we utilize the concept of a "choice marketplace" that allows sophisticated rendezvous semantics between customer and provider, and allows them to cooperatively guide network resource provisioning to dynamically fulfill network objectives such as maximizing performance received by network traffic. Our approach also allows balancing of various objectives, such as network utilization, latency, and the increasingly important metric of energy expenditure in the network. NeTS: Large: Collaborative Research: Network Innovation Through Choice Rudra Dutta ; George Rouskas$643,917 by National Science Foundation
09/15/2011 - 08/31/2014

This project builds on the SILO project that started in 2006 to design a new architecture for the Internet. In this new project, we will collaborate with teams of researchers from the University of Kentucky, the University of Massachusetts, and RENCI, to design critical parts of a new architecture for the Internet that will support the flexible use of widely applicable information transport and transformation modules to create good solutions for specific communication applications. The key idea is to allow a network to offer information transformation services at the edge or in the core transparently to the application, and creating a framework in which application can issue a request not only for communication but for specific reusable services. We also propose research tasks that will enable network virtualization and isolation seamlessly at many levels, currently a difficult but highly relevant problem in practical networking.

CAREER: Secure OS Views for Modern Computing Platforms
William Enck

$400,000 by National Science Foundation 02/ 1/2013 - 01/31/2018 Controlling the access and use of information is a fundamental challenge of computer security. Emerging computing platforms such as Android and Windows 8 further complicate access control by relying on sharing and collaboration between applications. When more than two applications participate in a workflow, existing permission systems break down due to their boolean nature. In this proposal, we seek to provide applications with residual control of their data and its copies. To do this, we propose secure OS views, which combines a new abstraction for accessing data with whole-system information tracking. We apply secure OS views to modern operating systems (e.g., Android and Windows 8), which use database-like abstractions for sharing and accessing information. Similar to a database view, secure OS views uses runtime context to dynamically define the protection domain, allowing the return of the value, a fake value, or nonexistence of the record. TWC: Small: Collaborative: Characterizing the Security Limitations of Accessing the Mobile Web William Enck$167,000 by NSF
10/ 1/2012 - 09/30/2015

Mobile browsers are beginning to serve as critical enablers of modern computing. With a combination of rich features that rival their desktop counterparts and strong security mechanisms such as TLS/SSL, these applications are becoming the basis of many other mobile apps. Unfortunately, the security guarantees provided by mobile browsers and the risks associated with today's mobile web have not been evaluated in great detail. In the proposed work, we will investigate the security of mobile browsers and the mobile specific websites they access. Characterizing and responding to the threats in this space is critical, especially given that cellular devices are used by more than five billion people around the world

CAREER: Enable Robust Virtualized Hosting Infrastructures via Coordinated Learning, Recovery, and Diagnosis
Xiaohui (Helen) Gu

$450,000 by National Science Foundation 01/ 1/2012 - 12/31/2016 Large-scale virtualized hosting infrastructures have become the fundamental platform for many real world systems such as cloud computing, enterprise data centers, and educational computing lab. However, due to their inherent complexity and sharing nature, hosting infrastructures are prone to various runtime problems such as performance anomalies and software/hardware failures. The overarching objective of this proposal is to systematically explore innovative runtime reliability management techniques for large-scale virtualized hosting infrastructures. Our research focuses on handling performance anomalies in distributed systems that are often very difficult to reproduce offline. Our approach combines the power of online learning, knowledge-driven first-response recovery, and in-situ diagnosis to handle unexpected system anomalies more efficiently and effectively. We aim at transforming the runtime system anomaly management from a trial-and-error guessing game into an efficient knowledge-driven self-healing process. Predictive Anomaly Management For Resilient Virtualized Computing Infrastructures Xiaohui (Helen) Gu$300,000 by Army Research Office
07/ 1/2010 - 08/15/2014

Large-scale virtualized computing infrastructures have become important platforms for many real-world systems such as cloud computing, virtual computing lab, and massive information processing. However, due to its inherent complexity and sharing nature, virtualized computing infrastructures are inevitably prone to various system anomaly problems such as software/hardware failures, performance anomalies, and malicious attacks. The goal of this project is to develop a new predictive anomaly management system to enhance the resilience of virtualized computing infrastructure. The major contributions will be an integrated framework consisting of four synergistic techniques: 1) scalable runtime virtual machine monitoring; 2) self-evolving online anomaly prediction; 3) speculative anomaly diagnosis; and 4) online anomaly correction.

North Carolina Bio-Preparedness Collaboration (NCB-Prepared)
Marc Hoit ; Laurie Williams

$1,760,486 by US Dept of Homeland Security via UNC-CH 06/ 1/2010 - 09/30/2014 For this project, we will explore the potential benefits of symptomatic and syndromic surveillance using existing NCB-Prepared data sources, including EMS, ED and poison control data, to improve surveillance capacity and outbreak response relating to the area of food safety. During the initial phase, we will examine two years of NCB-Prepared national poison control data to evaluate its utility related to evaluating trends in foodborne illness. This initial phase will produce preliminary statistics by working with the SAS analytics team of NCB-Prepared to incorporate poison control data into the system. Some possible analytical techniques employed may include descriptive statistics, Fourier analysis and cluster analysis. Results from this phase will provide a baseline for identifying potential foodborne illness outbreaks in the future as part of the NCB-Prepared system. This first phase will demonstrate basic functionality of the poison control data by July 30, 2012. During the second phase, we will continue to explore relationships between the poison control, EMS and ED data in relationship to their ability to improve early detection of potential foodborne illness outbreaks. After the first phase, project will have a national poison center data set relating to food safety issues available covering at least 10 year. For example, we will select key national outbreaks and determine if the historical data provided to NCB-Prepared could have been used to provide earlier signals that an outbreak was ongoing. A preliminary result will be produced for this second phase by September 30. Additional efforts will be made to help the team explore relationships between the poison control, EMS and ED data as they pertain to foodborne illness outbreaks. Comprehension-Driven Program Analysis (CPA) for Malware Detection in Android Phones Xuxian Jiang$556,488 by Iowa State University/US Air Force-Research Laboratory
02/ 3/2012 - 08/ 2/2016

Our goal is to develop new automated program analyses capable of proving that the application programs have security properties of interest to the DoD and demonstrate those analyses in the form of tools designed specifically to keep malicious code out of DoD Android-based mobile application marketplaces.

CAREER: Towards Exterminating Stealthy Rootkits -- A Systematic Immunization Approach
Xuxian Jiang

$424,166 by the National Science Foundation 02/15/2010 - 01/31/2015 Stealthy rootkit attacks are one of the most foundational threats to cyberspace. With the capability of subverting the software root of trust of a computer system, i.e., the operating system (OS) or the hypervisor, a rootkit can instantly take over the control of the system and stealthily inhabit the victim. To effectively mitigate and defeat them, researchers have explored various solutions. Unfortunately, the state-of-the-art defense is mainly reactive and in a fundamentally disadvantageous position in the arms-race against these stealthy attacks. The proposed research aims to fundamentally change the arms-race by proposing a systematic immunization approach to proactively prevent and exterminate rootkit attacks. Inspired by our human immune system and fundamental biological design principles, the proposed approach transforms system software (i.e., the OS and the hypervisor) so that the new one will tip the balance of favor toward the rootkit defense. To accomplish that, we will investigate a suite of innovative techniques to preserve kernel/hypervisor control flow integrity and evaluate their effectiveness with real-world malware and infrastructures. The proposed education components include the creation and dissemination of unique hands-on course materials with live demos, lab sessions, and tutorials. Collaborative Research: II-NEW: OpenVMI: A Software Infrastructure for Virtual Machine Introspection Xuxian Jiang$225,000 by National Science Foundation
09/ 1/2009 - 08/31/2014

Research in virtualization technologies has gained significant momentum in recent years. One of the basic yet powerful enabling function in many virtualization research efforts is virtual machine introspection or VMI: Observing a VM's states and events from outside the VM. The goal of this project is to develop OpenVMI: a software-based research infrastructure for VMI, which is expected to enable new research and education opportunities, including, but not limited to, safe malware experiments, intelligent virtual infrastructure management etc.

A Hybrid Computing Testbed For Mobile Threat Detection and Enhanced Research and Education in Information
Xuxian Jiang ; Peng Ning

$150,000 by US ARMY - ARO 08/21/2012 - 08/20/2014 This proposal proposes to build a hybrid computing testbed for detecting emerging mobile threats and improving research and education in information security at North Carolina State University (NCSU). The proposed computing testbed will be developed on the basis of the current Virtual Computing Lab (VCL) environment to provide a prototyping environment, which will be used for rapid development and evaluation of a variety of ongoing research projects funded by DoD and other government agencies. Also, it supports research-related education components in system oriented information security courses at NCSU. Moreover, we propose to equip the hybrid testbed with various mobile devices for detecting and experimenting with emerging mobile threats (e.g., Android malware). One key use of this hybrid testbed is to detect emerging or new threats against current mobile gadgets (e.g., smart phones and tablets), which is not available or possible yet based on current computing resources. The results and experience gained from operating and managing a real computing testbed will also provide practical insights into emerging threats on mobile Internet for students and researchers. The experience in managing and operating such a hybrid computing testbed will also be valuable to identify new security and performance problems and develop their practical solutions. SCH: INT: Collaborative Research: A Self-Adaptive Personalized Behavior Change System for Adolescent Preventive Healthcare James Lester$952,818 by National Science Foundation
10/ 1/2013 - 09/30/2017

Although the majority of adolescent health problems are amenable to behavioral intervention, and most adolescents are comfortable using interactive computing technology, few health information technology interventions have been integrated into adolescent care. The objective of the proposed research is to design, implement, and investigate INSPIRE, a self-adaptive personalized behavior change system for adolescent preventive healthcare. With a focus on adolescents, INSPIRE will enable adolescents to be active participants in dynamically generated, personalized narrative experiences that operationalize theoretically grounded interventions for behavior change through interactive narratives? plot structures and virtual character interactions.

LAS DO 2 task 3.3 - Lester-Taylor-Mott-Rowe
James Lester

$54,488 by Lab for Analytic Sciences/NSA 09/13/2013 - 09/30/2014 DO 2 task 3.3 activities (no other abstract available) DO 2 Task 3.8 Lester-Mott-Rowe James Lester$45,614 by Lab for Analytic Science/NSA
09/13/2013 - 09/30/2014

DO 2 Task 3.8 activities (no abstract available)

DO 2 Task 3.5 Lester
James Lester

$37,577 by Lab for Analytic Sciences/NSA 09/13/2013 - 09/30/2014 DO 2 Task 3.5 activities (no abstract available) Type I: ENGAGE: Immersive Game-Based Learning for Middle Grade Computational Fluency James Lester ; Kristy Boyer ; Bradford Mott ; Eric Wiebe$999,996 by National Science Foundation
01/ 1/2012 - 12/31/2014

The goal of the ENGAGE project is to develop a game-based learning environment that will support middle grade computer fluency education. It will be conducted by an interdisciplinary research team drawn from computer science, computer science education, and education. In collaboration with North Carolina middle schools, the research team will design, develop, deploy, and evaluate a game-based learning environment that enables middle school students to acquire computer fluency knowledge and skills. The ENGAGE project will be evaluated in middle grade classrooms with respect to both learning effectiveness and engagement.

Type I: ENGAGE: Immersive Game-Based Learning for Middle Grade Computational Fluency
James Lester ; Kristy Boyer ; Bradford Mott ; Eric Wiebe

$16,000 by NSF (Supplement) 01/ 1/2012 - 12/31/2014 The goal of the ENGAGE project is to develop a game-based learning environment that will support middle grade computer fluency education. It will be conducted by an interdisciplinary research team drawn from computer science, computer science education, and education. In collaboration with North Carolina middle schools, the research team will design, develop, deploy, and evaluate a game-based learning environment that enables middle school students to acquire computer fluency knowledge and skills. The ENGAGE project will be evaluated in middle grade classrooms with respect to both learning effectiveness and engagement. Detection and Transition Analysis of Engagement and Affect in a Simulation-Based Combat Medic Training Environment James Lester ; Bradford Mott$478,592 by Columbia University/US Army Research Laboratory
12/19/2012 - 12/18/2015

The project will develop automated detectors that can infer the engagement and affect of trainees learning through the vMedic training system. This project will combine interaction-based methods for detecting these constructs (e.g., models making inference solely from the trainee?s performance history) with scalable sensor-based methods for detecting these constructs, towards developing models that can leverage sensor information when it is available, but which can still assess trainee engagement and affect effectively even when sensors are not available. The automated detectors will be developed, integrated together, and validated for accuracy when applied to new trainees.

The Leonardo Project: An Intelligent Cyberlearning System for Interactive Scientific Modeling in Elementary Science Education
James Lester ; Bradford Mott ; Michael Carter ; Eric Weibe

$3,499,409 by National Science Foundation 08/15/2010 - 07/31/2014 The goal of the Leonardo project is to develop an intelligent cyberlearning system for interactive scientific modeling. Students will use Leonardo's intelligent virtual science notebooks to create and experiment with interactive models of physical phenomena. As students design and test their models, Leonardo's intelligent virtual tutors will engage them in problem-solving exchanges in which they will interactively annotate their models as they devise explanations and make predictions. During the project, the Leonardo virtual science notebook system will be rolled out to 60 classrooms in North Carolina, Texas, and California. CSR: Small: Collaborative Research: Enabling Cost-effective Cloud HPC Xiaosong Ma$311,998 by the National Science Foundation
10/ 1/2013 - 09/30/2016

The proposed work examines novel services built on top of public cloud infrastructure to enable cost-effective high-performance computing. We will explore the on-demand, elastic, and configurable features of cloud computing to complement the traditional supercomputer/cluster platforms. If successful, this research will result in tools that adaptively aggregate, configure, and re-configure cloud resources for different HPC needs, with the purpose of offering low-cost R&D environments for scalable parallel applications.

Collaborative Research: Automatic Extraction of Parallel I/O Benchmarks From HEC Applications
Xiaosong Ma ; Frank Mueller (co-PI)

$499,999 by National Science Foundation 09/15/2009 - 08/31/2014 Parallel I/O benchmarks are crucial for application developers, I/O software/hardware designers, and center administrators. However, currently there lack portable and comprehensive I/O benchmarks for high-end storage systems. We address this gap by proposing automatic generation of parallel I/O benchmarks. More specifically, we target the automated creation of application I/O benchmarks. Co-Design of Hardware / Software for Predicting MAV Aerodynamics Frank Mueller$799,999 by Virginia Polytechnic Institute and State University (US Air Force)
09/ 1/2012 - 10/31/2017

This proposal provides subcontractor support to Virginia Tech for a proposal submitted under the Air Force's Basic Research Initiative. The proposal will focus on development of reconfigurable mapping strategies for porting multi-block structured and unstructured-mesh CFD codes to computing clusters containing CPU/GPU processing units.

Hobbes: OS and Runtime Support for Application Composition
Frank Mueller

$300,000 by Sandia National Laboratories via US Dept of Energy 10/24/2013 - 10/23/2016 This project intends to deliver an operating system and runtime system (OS/R) environment for extreme-scale scientific computing. We will develop the necessary OS/R interfaces and lowlevel system services to support isolation and sharing functionality for designing and implementing applications as well as performance and correctness tools. We propose a lightweight OS/R system with the flexibility to custom build runtimes for any particular purpose. Each component executes in its own "enclave" with a specialized runtime and isolation properties. A global runtime system provides the software required to compose applications out of a collection of enclaves, join them through secure and low-latency communication, and schedule them to avoid contention and maximize resource utilization. The primary deliverable of this project is a full OS/R stack based on the Kitten operating system and Palacios virtual machine monitor that can be delivered to vendors for further enhancement and optimization. CPS: Breakthrough: Collaborative Research: Bringing the Multicore Revolution to Safety-Critical Cyber-Physical Systems Frank Mueller$225,000 by National Science Foundation
02/ 1/2013 - 01/31/2016

Multicore platforms have the potential of revolutionizing the capabilities of embedded cyber-physical systems but lack predictability in execution time due to shared resources. Safety-critical systems require such predictability for certification. This research aims at resolving this multicore predictability problem.'' It will develop methods that enable to share hardware resources to be allocated and provide predictability, including support for real-time operating systems, middleware, and associated analysis tools. The devised methods will be evaluated through experimental research involving synthetic micro-benchmarks and code for unmanned air vehicles re-thinking'' their adapting to changing environmental conditions within Cyber-Physical Systems.

Resilience for Global Address Spaces
Frank Mueller

$153,934 by Lawrence Berkeley National Laboratory via US Dept of Energy 09/24/2013 - 08/15/2015 he objective of this work is to provide functionality for the BLCR Linux module under a PGAS runtime system (within the DEGAS software stack) to support advanced fault-tolerant capabilities, which are of specific value in the context of large-scale computational science codes running on high-end clusters and, ultimately, exascale facilities. Our proposal is to develop and integrate into DEGAS a set of advanced techniques to reduce the checkpoint/restart (C/R)overhead. SHF: Small: Scalable Trace-Based Tools for In-Situ Data Analysis of HPC Applications (ScalaJack) Frank Mueller$457,395 by National Science Foundation
06/ 1/2012 - 05/31/2015

This decade is projected to usher in the period of exascale computing with the advent of systems with more than 500 million concurrent tasks. Harnessing such hardware with coordinated computing in software poses significant challenges. Production codes tend to face scalability problems, but current performance analysis tools seldom operate effectively beyond 10,000 cores. We propose to combine trace analysis and in-situ data analysis techniques at runtime. Application developers thus create ultra low-overhead measurement and analysis facilities on-the-fly, customized for the performance problems of particular application. We propose an analysis generator called ScalaJack for this purpose. Results of this work will be contributed as open-source code to the research community and beyond as done in past projects. Pluggable, customization analysis not only allows other groups to build tools on top of our approach but to also contribute components to our framework that will be shared in a repository hosted by us.

Operating System Mechanisms for Many-Core Systems-Phase II (PICASO II) Pico-kernel Adaptive and Scalable Operating Systems Phase II
Frank Mueller

$225,000 by Securboration via US Air Force Research Laboratory 06/ 1/2013 - 05/31/2015 The objective of this work is to design and evaluate novel system and program abstractions for combined performance and scalability paving the path into a future of operating system supporting a massive number of cores on a single chip. SHF: Small: RESYST: Resilience via Synergistic Redundancy and Fault Tolerance for High-End Computing Frank Mueller$376,219 by National Science Foundation
10/ 1/2010 - 09/30/2014

In High-End Computing (HEC), faults have become the norm rather than the exception for parallel computation on clusters with 10s/100s of thousands of cores. As the core count increases, so does the overhead for fault-tolerant techniques that rely on checkpoint/restart (C/R) mechanisms. At 50% overheads, redundancy is a viable alternative to fault recovery and actually scales, which makes the approach attractive for HEC. The objective of this work to the develop a synergistic approach by combining C/R-based fault tolerance with redundancy in computer to achieve high levels of resilience. This work alleviates scalability limitations of current fault tolerant practices. It contributes to fault modeling as well as fault detection and recovery in significantly advancing existing techniques by controlling levels of redundancy and checkpointing intervals in the presence of faults. It is transformative in providing a model where users select a target failure probability at the price of using additional resources.

CSR: Medium: Collaborative Research: Providing Predictable Timing for Task Migration in Embedded Multi-Core Environments (TiME-ME)
Frank Mueller

$390,000 by National Science Foundation 09/ 1/2009 - 08/31/2014 Assuring deadlines of embedded tasks for contemporary multicore architectures is becoming increasingly difficult. Real-time scheduling relies on task migration to exploit multicores, yet migration actually reduces timing predictability due to cache warm-up overheads and increased interconnect traffic. We propose a fundamentally new approach to increase the timing predictability of multicore architectures aimed at task migration in embedded environments making three major contributions. 1. We develop novel strategies to guide migration based on cost/benefit tradeoffs exploiting both static and dynamic analyses. 2. We devise mechanisms to increase timing predictability under task migration providing explicit support for proactive and reactive real-time data movement across cores and their caches. 3. We propose rate- and bandwidth-adaptive mechanisms as well as monitoring capabilities to increase predictability under task migration. Our work aims at initiating a novel research direction investigating the benefits of interactions between hardware and software for embedded multicores with respect to timing predictability. CAREER:Expanding Developers' Usage of Software Tools by Enabling Social Learning Emerson Murphy-Hill$495,721 by National Science Foundation
08/ 1/2013 - 07/31/2018

Tools can help software developers alleviate the challenge of creating and maintaining software. Unfortunately, developers only use a small subset of the available tools. The proposed research investigates how social learning, an effective mechanism for discovering new tools, can help software developers to discover relevant tools. In doing so, developers will be able to increase software quality while decreasing development time.

TWC: Small: Collaborative: Discovering Software Vulnerabilities Through Interactive Static Analysis
Emerson Murphy-Hill

$249,854 by National Science Foundation 10/ 1/2013 - 09/30/2016 Software vulnerabilities originating from insecure code are one of the leading causes of security problems people face today. Current tool support for secure programming focuses on catching security errors after the program is written. We propose a new approach, interactive static analysis, to improve upon static analysis techniques by introducing a new mixed-initiative paradigm for interacting with developers to aid in the detection and prevention of security vulnerabilities. DO 2 Task 3.7 - Murphy Hill Emerson Murphy-Hill$49,486 by Laboratory for Analytic Sciences
09/13/2013 - 09/30/2014

DO 2 Task 3.7 activities

SHF: Small: Expressive and Scalable Notifications from Program Analysis Tools
Emerson Murphy-Hill ; Sarah Heckman

$250,000 by National Science Foundation 10/ 1/2012 - 09/30/2014 A wide variety of program analysis tools have been created to help software developers do their jobs, yet the output of these tools are often difficult to understand and vary significantly from tool to tool. As a result, software developers may waste time trying to interpret the output of these tools, instead of making their software more capable and reliable. This proposal suggests a broad investigation of several types of program analysis tools, with the end goal being an improved understanding of how program analysis tools can inform developers in the most expressive and uniform way possible. Once this goal is reached, we can create program analysis tools that enable developers to make tremendous strides towards more correct, more reliable, and more on-time software systems. TWC: Frontier: Collaborative: Rethinking Security in the Era of Cloud Computing Peng Ning$749,996 by National Science Foundation
09/ 1/2013 - 08/31/2018

Increased use of cloud computing services is becoming a reality in today's IT management. The security risks of this move are active research topics, yielding cautionary examples of attacks enabled by the co-location of competing tenants. In this project, we propose to mitigate such risks through a new approach to cloud architecture defined by leveraging cloud providers as trusted (but auditable) security enablers. We will exploit cooperation between cloud providers and tenants in preventing attacks as a means to tackle long-standing open security problems, including protection of tenants against outsider attacks, improved intrusion detection and security diagnosis, and security-monitoring inlays.

NeTS: Small: Collaborative Research: Enabling Robust Communication in Cognitive Radio Networks with Multiple Lines of Defense
Peng Ning

$249,901 by National Science Foundation 10/ 1/2013 - 09/30/2016 Cognitive radio is an emerging advanced radio technology in wireless access, with many promising benefits including dynamic spectrum sharing, robust cross-layer adaptation, and collaborative networking. Opportunistic spectrum access (OSA) is at the core of cognitive radio technologies, which has received great attention recently, focusing on improving spectrum utilization efficiency and reliability. However, the state-of-the-art still suffers from one severe security vulnerability, which has been largely overlooked by the research community so far. That is, a malicious jammer can always disrupt the legitimate network communication by leveraging the public-available channel statistic information to effectively jam the channels and thus lead to serious spectrum underutilization. In this proposal, we propose to address the challenge of effective anti-jamming communication in cognitive radio networks (CRNs). We propose a multiple lines of defense approach, which considers and integrates defense technologies from different dimensions, including frequency hopping, power control, cooperative communication, and signal processing. The proposed defense approach enables both reactive and proactive protection, from evading jammers to competing against jammers, and to expelling jamming signals, and thus guarantees effective anti-jamming communication under a variety of network environments. CISCO-NCSU Internship Program Peng Ning$32,000 by Cisco Systems, Inc.(Supplement)
07/12/2011 - 07/11/2016

This is a pilot internship program between NCSU and Cisco for 4 undergraduate students to learn through working part-time on real life problems for Cisco with the hope that this pilot program can grow and develop into a long term working relationship. Specifically, NCSU students will participate in Cisco Software Application Support plus Upgrades (SASU) projects and/or conduct research for SASU. This will be done with an understanding that the interns are students, and as such are learning and being trained with the training coming from both the Cisco (for SASU-specific skills), and NCSU (through the undergraduate program they are enrolled in) in general relevant skills.

CISCO-NCSU Internship Program
Peng Ning

$32,000 by Cisco Systems, Inc. 07/12/2011 - 07/11/2016 This is a pilot internship program between NCSU and Cisco for 4 undergraduate students to learn through working part-time on real life problems for Cisco with the hope that this pilot program can grow and develop into a long term working relationship. Specifically, NCSU students will participate in Cisco Software Application Support plus Upgrades (SASU) projects and/or conduct research for SASU. This will be done with an understanding that the interns are students, and as such are learning and being trained with the training coming from both the Cisco (for SASU-specific skills), and NCSU (through the undergraduate program they are enrolled in) in general relevant skills. TC: Small: Defending against Insider Jammers in DSSS- and FH-Based Wireless Communication Systems Peng Ning ; Huaiyu Dai, ECE ; Mladen Vouk$499,064 by National Science Foundation
09/ 1/2010 - 08/31/2014

Jamming resistance is crucial for applications where reliable wireless communication is required, such as rescue missions and military applications. Spread spectrum techniques such as Frequency Hopping (FH) and Direct Sequence Spread Spectrum (DSSS) have been used as countermeasures against jamming attacks. However, these anti-jamming techniques require that senders and receivers share a secret key to communicate with each other, and thus are vulnerable to insider attacks where the adversary has access to the secret key. The objective of this project is to develop a suite of techniques to defend against insider jammers in DSSS and FH based wireless communication systems. We will develop novel and efficient insider-jamming-resistant techniques for both DSSS- and FH-based wireless communication systems. Our proposed research consists of two thrusts. The first thrust is to develop novel spreading/despreading techniques, called DSD-DSSS (which stands for DSSS based on Delayed Seed Disclosure), to enhance DSSS-based wireless communication to defend against insider jamming threats, while the second thrust is to develop a new approach, called USD-FH (which stands for FH based on Uncoordinated Seed Disclosure), to enable sender and receivers using FH to communicate without pre-establishing any common secret hopping pattern. A key property of our new approaches is that they do not depend on any secret shared by the sender and receivers. Our solution has the potential to significantly enhance the anti-jamming capability of today?s wireless communication systems.

CISCO-NCSU Internship Program (Supplement IV)
Peng Ning ; Rouskas George

$32,000 by Cisco Systems, Inc 07/12/2011 - 07/11/2016 This is a pilot internship program between NCSU and Cisco for 4 undergraduate or graduate students to learn through working part-time on real life problems for Cisco with the hope that this pilot program can grow and develop into a long term working relationship. Specifically, NCSU students will participate in Cisco Software Application Support plus Upgrades (SASU) projects and/or conduct research for SASU. This will be done with an understanding that the interns are students, and as such are learning and being trained with the training coming from both the Cisco (for SASU-specific skills), and NCSU (through the undergraduate/graduate program they are enrolled in) in general relevant skills CISCO-NCSU Internship Program(Supplement III) Peng Ning ; George Rouskas ; Mladen Vouk$32,000 by Cisco Systems, Inc
07/12/2011 - 07/11/2016

This is a pilot internship program between NCSU and Cisco for 4 undergraduate or graduate students to learn through working part-time on real life problems for Cisco with the hope that this pilot program can grow and develop into a long term working relationship. Specifically, NCSU students will participate in Cisco Software Application Support plus Upgrades (SASU) projects and/or conduct research for SASU. This will be done with an understanding that the interns are students, and as such are learning and being trained with the training coming from both the Cisco (for SASU-specific skills), and NCSU (through the undergraduate/graduate program they are enrolled in) in general relevant skills

Is Wireless Channel Dependable for Security Provisioning?
Peng Ning (co-PI)

$350,000 by the National Science Foundation 08/12/2013 - 07/31/2016 Wireless security is receiving increasing attention as wireless systems become a key component in our daily life as well as critical cyber-physical systems. Recent progress in this area exploits physical layer characteristics to offer enhanced and sometimes the only available security mechanisms. The success of such security mechanisms depends crucially on the correct modeling of underlying wireless propagation. It is widely accepted that wireless channels decorrelate fast over space, and half a wavelength is the key distance metric used in existing wireless physical layer security mechanisms for security assurance. We believe that this channel correlation model is incorrect in general: it leads to wrong hypothesis about the inference capability of a passive adversary and results in false sense of security, which will expose the legitimate systems to severe threats with little awareness. In this project, we seek to understand the fundamental limits in passive inference of wireless channel characteristics, and further advance our knowledge and practice in wireless security. III: Small: Optimization Techniques for Scalable Semantic Web Data Processing in the Cloud Kemafor Ogan$446,942 by National Science Foundation
09/ 1/2012 - 08/31/2015

Achieving scalable processing of the increasing amount of publicly-available Semantic Web data will hinge on parallelization. The Map-Reduce programming paradigm recently emerged as a de-facto parallel data processing standard and has demonstrated effectiveness with respect to structured and unstructured data. However, Semantic Web data presents challenges not adequately addressed by existing techniques due to its flexible, fine-grained data model and the need to reason beyond explicitly represented data. This project will investigate optimization techniques that address these unique challenges based on rethinking Semantic Web data processing on Map-Reduce platforms from the ground, up - from query algebra to query execution.

Computer-aided Human Centric Cyber Situation Awareness
Doug Reeves ; Chris Healey

$979,463 by Pennsylvania State University 09/17/2009 - 09/16/2014 The NCSU participants will focus on the development of multi-level information fusion in the cyber world, VM-based automated vulnerability diagnosis of unknown cyber vulnerabilities, and application of video game technology to bridge the gap between the cyber and the human worlds. Runtime Enforcement of Security Policies Douglas Reeves$29,780 by US Army - Army Research Office
03/ 5/2014 - 12/ 4/2014

Android smartphones have grown in market share and have penetrated all corners of the market, including US Government and, in particular, DoD. The ecosystem of the Android App marketplace while encouraging creativity also has lax standards. Recent work by Aiken's group shows that it is possible to use static analysis techniques to identify vulnerabilities due to abuse of {\em permissions} afforded to the software app, by the user, but with potential for false positives and attendant necessity for manual analysis. In this preliminary investigation, we propose to investigate a run time monitor that could be used in combination with static analysis to enforce strict permission policies. The particular research questions we will consider are: x Design of a language for expressing positive (shall) and negative (should not) permission x Algorithms for instrumenting application code that would be used to maintain invariants implied by the permission policies set by the user x Algorithms for instrumenting application code to collect trace data that could be mined later for surreptitious violations of security policies, and algorithms for deleting applications automatically when policies are violated. The three parts of the research proposal, when taken together, correspond to traditional law enforcement strategies -- setting of the law, monitoring for compliance, and imposition of penalty when laws are broken. While the ultimate goal is to validate the proposed work in the context of the Android market place, the proposed preliminary investigation will be theoretical in nature.

Graduate Industrial Traineeship for Savera Tanwir
Douglas Reeves

$51,058 by SAS Institute, Inc 08/21/2013 - 08/20/2014 NCSU through the SAS GA will provide research and analysis to SAS as set forth in this Agreement. Such research and analysis shall include, but is not limited to, research, generation, testing, and documentation of operations research software. SAS GA will provide such services for SAS' offices in Cary, North Carolina, at such times as have been mutually agreed upon by the parties. Graduate Industrial Traineeship for Chris Barile Douglas Reeves$44,535 by SAS Institute, Inc.
06/ 8/2013 - 06/ 7/2014

NCSU through the SAS GA will provide research and analysis to SAS as set forth in this Agreement. Such research and analysis shall include, but is not limited to, research, generation, testing, and documentation of operations research software. SAS GA will provide such services for SAS' offices in Cary, North Carolina, at such times as have been mutually agreed upon by the parties.

Graduate Industrial Traineeship for Sagar Jauhari
Douglas Reeves

$69,026 by SAS Institute, Inc. 01/ 7/2013 - 05/31/2014 "NC State University (NCSU), through the graduate industrial traineeship (GIT) student, will provide research and analysis to SAS. Such research and analysis shall include, but is not limited to, research, generation, testing and documentation of operation research software. GIT student will provide such services for SAS' offices in Cary, North Carolina, at such times as have been mutually agreed upon by the parties. GIT student agrees to abide by SAS' policies and procedures regarding security of SAS' facilities and computing resources." Graduate Industrial Traineeship for Namita Shubhy Douglas Reeves$15,569 by SAS Institute, INC
01/27/2014 - 05/30/2014

NCSU through the SAS GA will provide research and analysis to SAS as set forth in this Agreement. Such research and analysis shall include, but is not limited to, research, generation, testing, and documentation of operations research software. SAS GA will provide such services for SAS' offices in Cary, North Carolina, at such times as have been mutually agreed upon by the parties.

Graduate Industrial Traineeship for Ameeta Muralidharan
Douglas Reeves

$15,569 by SAS Institute, INC 01/27/2014 - 05/30/2014 NCSU through the SAS GA will provide research and analysis to SAS as set forth in this Agreement. Such research and analysis shall include, but is not limited to, research, generation, testing, and documentation of operations research software. SAS GA will provide such services for SAS' offices in Cary, North Carolina, at such times as have been mutually agreed upon by the parties. Graduate Industrial Traineeship for Da Young Lee Douglas Reeves$50,604 by SAS Institute, Inc
05/13/2013 - 05/12/2014

NC State University (NCSU), through the graduate industrial traineeship (GIT) student, will provide research and analysis to SAS. Such research and analysis shall include, but is not limited to, research, generation, testing and documentation of operation research software. GIT student will provide such services for SAS' offices in Cary, North Carolina, at such times as have been mutually agreed upon by the parties. GIT student agrees to abide by SAS' policies and procedures regarding security of SAS' facilities and computing resources.

NeTS: Small: Investigation of Human Mobility: Measurement, Modeling,Analysis, Applications and Protocols
Injong Rhee

$298,356 by National Science Foundation 08/ 1/2010 - 07/31/2014 Simulating realistic mobility patterns of mobile devices is important for the performance study of mobile networks because deploying a real testbed of mobile networks is extremely difficult, and furthermore, even with such a testbed, constructing repeatable performance experiments using mobile devices is not trivial. Humans are a big factor in simulating mobile networks as most mobile nodes or devices (cell phones, PDAs and cars) are attached to or driven by humans. Emulating the realistic mobility patterns of humans can enhance the realism of simulation-based performance evaluation of human-driven mobile networks. Our NSF-funded research that ends this year has studied the patterns of human mobility using GPS traces of over 100 volunteers from five different sites including university campuses, New York City, Disney World, and State Fair. This research has revealed many important fundamental statistical properties of human mobility, namely heavy-tail flight distributions, self-similar dispersion of visit points, and least-action principle for trip planning. Most of all, it finds that people tend to optimize their trips in a way to minimize their discomfort or cost of trips (e.g., distance). No existing mobility models explicitly represent all of these properties. Our results are very encouraging and the proposed research will extend the work well beyond what has been accomplished so far. . We will perform a measurement study tracking the mobility of 100 or 200 students in a campus simultaneously, and analyze the mobility patterns associated with geo-physical and social contexts of participants including social networks, interactions, spatio-temporal correlations, and meetings. . We will cast the problem of mobility modeling as an optimization problem borrowing techniques from AI and Robotics which will make it easy to incorporate the statistical properties of mobility patterns commonly arising from group mobility traces. The realism of our models in expressing human mobility will surpass any existing human mobility models. . We will develop new routing protocols leveraging the researched statistical properties found in real traces to optimize delivery performance. The end products of the proposed research is (a) a new human mobility model that is capable of realistically expressing mobility patterns arising from reaction to social and geo-physical contexts, (b) their implementation in network simulators such as NS-2/3 and GloMoSim, (c) mobility traces that contain both trajectories of people in a university campus and contact times, (d) new efficient routing protocols for mobile networks NetSE: Large: Collaborative Research: Platys: From Position to Place in Next Generation Networks Injong Rhee ; Munindar Singh$706,167 by National Science Foundation
09/ 1/2009 - 08/31/2014

This project develops a high-level notion of context that exploits the capabilities of next genera-tion networks to enable applications that deliver better user experiences. In particular, it exploits mobile devices always with a user to capture key elements of context: the user's location and, through localization, characteristics of the user's environment.

RI: Small: Collaborative Research: Speeding Up Learning through Modeling the Pragmatics of Training
David Roberts

$156,203 by National Science Foundation 10/ 1/2013 - 09/30/2015 We propose to develop techniques that will enable humans to train computers efficiently and intuitively. In this proposed work, we draw inspiration from the ways that human trainers teach dogs complex behaviors to develop novel machine learning paradigms that will enable intelligent agents to learn from human trainers quickly, and in a way that humans can intuitively take advantage of. This research aims to return to the basics of programming---it seeks to develop novel methods that allow humans to tell computers what to do. More specifically, this research will develop learning techniques that explicitly model and leverage the implicit communication channel that humans use while training, a process akin to interpreting the pragmatic implicature of a natural language communication. We will develop algorithms that view the training process as an intentional communicative act, and can vastly outperform standard reward-seeking algorithms in terms of the speed and accuracy with which human trainers can generate desired behavior. CPS: Synergy: Integrated Sensing and Control Algorithms for Computer-Assisted Training (Computer Assisted Training Systems (CATS) for Dogs) David Roberts ; Alper Bozkurt ECE ; Barbara Sherman CVM$999,103 by National Science Foundation
11/30/-1 - 09/30/2016

We propose to develop tools and techniques that will enable more effective two-way communication between dogs and handlers. We will work to create non-invasive physiological and inertial measuring devices that will transmit real-time information wirelessly to a computer. We will also develop technologies that will enable the computer to train desired behaviors using positive reinforcement without the direct input from humans. We will work to validate our approach using laboratory animals in the CVM as well as with a local assistance dog training organization working as a consultant.

NeTS:Small: Computationally Scalable Optical Network Design
George Rouskas

$429,995 by NSF 08/ 1/2011 - 07/31/2014 Optical networking forms the foundation of the global network infrastructure, hence the planning and design of optical networks is crucial to the operation and economics of the Internet and its ability to support critical and reliable communication services. With this research project we aim to make contributions that will lead to a quantum leap in the ability to solve optimally a range of optical design problems. In particular, we will develop compact formulations and solution approaches that can be applied efficiently to instances encountered in Internet-scale environments. Our goal is to lower the barrier to entry in fully exploring the solution space and in implementing and deploying innovative designs. The solutions we will develop are "future-proof" with respect to advances in DWDM transmission technology, as the size of the corresponding problem formulations is independent of the number of wavelengths. Scalable and Power Efficient Data Analytics for Hybrid Exascale Systems Nagiza Samatova$364,944 by Oak Ridge National Laboratories/ US Dept. of Energy
01/31/2011 - 12/31/2014

The specific objectives of the proposal are as follows: 1. Design and develop data mining kernels and algorithms for acceleration on hybrid architectures which include many-core systems, GPUs, and other accelerators. 2. Design and develop approximate scalable algorithms for data mining and analysis kernels enabling faster exploration, more efficient resource usage, reduced memory footprint, and more power efficient computations. 3. Design and develop index-based data analysis and mining kernels and algorithms for performance and power optimizations including index-based perturbation analysis kernels for noisy and uncertain data. 4. Demonstrate the results of our project by enabling analytics at scale for selected applications on large-scale HPC systems.

Runtime System for I/O Staging in Support of In-Situ Processing of Extreme Scale Data
Nagiza Samatova

$286,140 by Oak Ridge National Loboratory/Dept. of Energy 01/31/2011 - 08/31/2014 Accelerating the rate of insight and scientific productivity demands new solutions to managing the avalanche of data expected in extreme-scale. Our approach is to use tools that can reduce, analyze, and index the data while it is still in memory (referred to as "in-situ" processing of data). ). In order to deal with the large amount of data generated by the simulations, our team has partnered with many application teams to deliver proven technology that can accelerate their knowledge discovery process. These technologies include ADIOS, FastBit, and Parallel R. In this proposal we wish to integrate these technologies together, and create a runtime system that will allow scientist to create an easy-to-use scientific workflow system, that will run in situ, in extra nodes on the system, which is used to not only accelerate their I/O speeds, but also to pre-analyze, index, visualize, and reduce the overall amount of information from these solutions. Joint Faculty Agreement For Nagiza Samatova Nagiza Samatova$507,294 by Oak Ridge National Laboratories - UT Battelle, LLC
08/ 9/2007 - 08/ 8/2014

Dr. Nagiza Samatova's joint work with NC State University and Oak Ridge National Laboratory (ORNL) will provide the interface between the two organizations aiming to collaboratively address computational challenges in the Scientific Data Management, Data-Intensive Computing for Understanding Complex Biologicial Systems, Knowledge Integration for the Shewanella Federation, and the Large-Scale Analysis of Biologicial Networks with Applications to Bioenergy Production.

Analytics-driven Efficient Indexing and Query Processing of Extreme Scale AMR Data
Nagiza Samatova

$149,999 by National Science Foundation 05/ 1/2012 - 04/30/2014 One of the most significant advances for large-scale scientific simulations has been the advent of Adaptive Mesh Refinement, or AMR. By using dynamic gridding, AMR can achieve substantial savings in memory, computation, and disk resources while maintaining or even increasing simulation accuracy, relative to static, uniform gridding. However, the resultant non-uniform structure of the simulation mesh produced by AMR methods cause inefficient post-simulation access patterns during AMR data analytics that is becoming a substantial bottleneck given the exponential increase in simulation output. Toward bridging this gap in efficient analytics support for AMR data, we propose an integrated, three-prong approach that aims: (a) To devise an AMR query model; (b) To explore effective indexing methods for AMR data analytics; and (c) To investigate data storage layout strategies for AMR data retrieval optimized for analytics-induced heterogeneous data access patterns. Scalable Data Management, Analysis, and Visualization (SDAV) Institute Nagiza Samatova ; Anatoli Melechko$750,000 by US Department of Energy
02/15/2012 - 02/14/2017

The SDAV is a unique and comprehensive combination of scientific data management, analysis, and visualization expertise and technologies aimed at enabling scientific knowledge discovery for applications running on state-of-the-art computational platforms located at DOE's primary computing facilities. This integrated institute focuses on tackling key challenges facing applications in our three focus areas through a well-coordinated team and management organization that can respond to changing technical and programmatic objectives. The proposed work portfolio is a blend of applied research and development, aimed at having key software services operate effectively on large distributed memory multi-core, and many-core platforms and especially DOE's open high performance computing facilities. Our goal is to create an integrated, open source, sustainable framework and software tools for the science community.

Scalable Statistical Computing For Physical Science Applications
Nagiza Samatova ; Anatoli Melechko

$354,646 by US Department of Energy (DOE) 12/ 2/2011 - 06/30/2014 Physical science applications such as nanoscience, fusion science, climate and biology generate large-scale data sets from their simulations and high throughput technologies. This necessitates scalable technologies for processing and analyzing this data. We plan to research and develop advanced data mining algorithms for knowledge discovery from this complex, high-dimensional, and noisy data. We will apply these technologies to DOE-mission scientific applications related to fusion energy, bioenergy, understanding the impacts of climate extremes, and insider threat detection and mitigation. Ultrascale Computational Modeling of Phenotype-Specific Metabolic Processes in Microbial Communities Nagiza Samatova ; Anatoli Melechko$454,311 by Oak National Laboratories - UT Battelle (DOE)
01/15/2010 - 05/31/2014

Ultrascale computational modeling methods will be developed for revealing phenotype-specific metabolic processes and their cross-talks and applied to the critical DOE problem of acid mine drainage (AMD). The apex of the project will be a systematic and iterative computational procedure for: (1) identification and expression-level characterization of phenotype-related genes; (2) reconstruction of phenotype-specific metabolic pathways enriched by these genes; (3) elucidation of the symbiotic and/or competing interplay between these pathways across species; and (4) characterization of evolutionary and environmental adaptation of the community.

Collaborative Research: Understanding Climate Change: A Data Driven Approach
Nagiza Samatova ; Frederick Semazzi

$1,815,739 by National Science Foundation 09/ 1/2010 - 08/31/2015 The goal is to provide a computational capability for effective and efficient exploration of high-resolution climate networks derived from multivariate, uncertain, noisy and spatio-temporal climate data. We plan to increase the efficiency and climatologically relevancy of the network patterns identification through integrated research activities focused on: (a) supporting comparative analysis of multiple climate networks; (b) constraining the search space via exploiting the inherent structure (e.g., multi-partite) of climate networks; (c) establishing the foundation to efficiently update solutions for perturbed (changing) graphs; and (d) designing and implementing parallel algorithms scalable to thousands of processors on multi-node multi-core supercomputer architectures. Lecture Hall Polytopes, Inversion Sequences, and Eulerian Polynomials Carla Savage$30,000 by Simons Foundation
09/ 1/2012 - 08/31/2017

Over the past ten years, lecture hall partitions have emerged as fundamental structures in combinatorics and number theory, leading to new generalizations and new interpretations of several classical theorems. This project takes a geometric view of lecture hall partitions and uses polyhedral geometry to investigate their remarkable properties.

Policy-Based Governance for the OOI Cyberinfrastructure
Munindar Singh

$134,688 by the University of California-San Diego 09/30/2009 - 02/25/2015 This project will develop policy-based service governance modules for the Oceanographic Observatories Initiative (OOI) Cyberinfrastructure. The main objectives of the proposed project include (1) formulating the key conceptual model underlying the patterns of governance; (2) formalizing "best practices" patterns familiar to the scientific community and seeding the cyberinfrastructure with them; (3) understanding user requirements for tools that support creating and editing patterns of governance. Policy-Based Governance for the OOI Cyberinfrastructure Munindar Singh$124,688 by Univ of Calif-San Diego/NSF
09/ 1/2009 - 02/25/2015

This project will develop policy-based service governance modules for the Oceanographic Observatories Initiative (OOI) Cyberinfrastructure. The main objectives of the proposed project include (1) formulating the key conceptual model underlying the patterns of governance; (2) formalizing "best practices" patterns familiar to the scientific community and seeding the cyberinfrastructure with them; (3) understanding user requirements for tools that support creating and editing patterns of governance

Policy-Based Governance for the OOI Cyberinfrastructure
Munindar Singh

$10,000 by University of California - San Diego / National Science Foundation (This is a supplement) 09/ 1/2009 - 02/25/2015 This project will develop policy-based service governance modules for the Oceanographic Observatories Initiative (OOI) Cyberinfrastructure. The main objectives of the proposed project include (1) formulating the key conceptual model underlying the patterns of governance; (2) formalizing "best practices" patterns familiar to the scientific community and seeding the cyberinfrastructure with them; (3) understanding user requirements for tools that support creating and editing patterns of governance Student Support for Participation in the Symposium and Bootcamp on the Science of Security (HotSoS) Munindar Singh$5,000 by National Science Foundation (NSF)
01/ 1/2014 - 12/31/2014

This project will support travel by US student researchers to the Symposium and Bootcamp on the Science of Security (HotSoS), which will be held in April 2014 in Raleigh, North Carolina. Travel support will be critical in encouraging participation, which is especially important since HotSoS 2014 will be one of the first peer-reviewed events on the Science of Security.

DO 2 Task 3.7 - Singh
Munindar Singh

$43,889 by Laboratory for Analytic Sciences 09/13/2013 - 09/30/2014 DO 2 Task 3.7 activities Quality of Information-Aware Networks for Tactical Applications (QUANTA) Munindar Singh$669,028 by Penn State University (Army Research Laboratory
09/28/2009 - 09/27/2014

This project will develop a computational approach to trust geared toward enhancing the quality of information in tactical networks. In particular, this project will develop a trust model that takes into account various objective and subjective qualities of service as well as the social relationships among the parties involved in a network who originate, propagate, or consume information. The proposed approach will build an ontology for quality of information and its constituent qualities, and will expand existing probabilistic techniques to multivalued settings. The project will develop a prototype software module that realize the techniques for producing trust assessments regarding the information exchanged.

DO 2 Task 3.8 - St. Amant
Robert St. Amant

$49,493 by Laboratory for Analytic Sciences 09/13/2013 - 09/30/2014 DO 2 Task 3.8 activities DO 2 Task 3.2 - Streck John Streck$935,302 by NSA
09/13/2013 - 09/30/2014

DO 2 Task 3.2 activities

NCDS Data Science Faculty Fellow-Tracking Community Evolution in Dynamic Graph Data Using Tree-Like Structure
Vida Sullivan

$30,000 by National Consortium for Data Science (UNC-UNC Chapel Hill) 01/ 1/2014 - 12/31/2014 "Big Data" sources for many real-world applications pose numerous challenges to understanding the complex and possibly hidden relationships between components of a complex network. Furthermore, these networks often consist of heterogeneous entities and types of relationships, and many existing algorithms for computing network features and similarity are not directly applicable. In order to draw actionable insights, analysis need to identify events of interest, place them in context, and understand their impact. Existing approaches which emphasize visualization (at the expense of analytics), struggle to coherently present networks with hundreds of entities, whereas practical applications require hundreds of thousands (or more). We propose to develop methods which integrate ideas from graph theory with multi-scale modeling (since events of interest may occur at different levels of granularity/contexts within the data) to improve comprehension of such relational data and form a foundation for novel methods of visualization and interaction. Joint Faculty Appointment For Vida Blair Sullivan Vida Sullivan$75,200 by Oak Ridge National Laboratories - UT-Battelle LLC
09/13/2013 - 08/15/2014

The PI's unique combination of expertise in structural graph theory and scalable graph algorithms/big data is necessary to ensure the success of ORNL-based projects using applied discrete mathematics to enable advances in graph generation and HPC benchmarking, social network analysis, and multi-scale graph decompositions for the Department of Energy and Department of Defense. The PI will direct and conduct fundamental research, collaborate with ORNL staff, write up research results for peer-reviewed publication, give presentations, and mentor students and postdoctoral staff as appropriate.

Collaborative Research: CPATH II: Incorporating Communication Outcomes into the Computer Science Curriculum
Mladen Vouk ; Michael Carter (co-PI). Grad

$369,881 by National Science Foundation 10/ 1/2009 - 03/31/2015 In partnership with industry and faculty from across the country, this project will develop a transformative approach to developing the communication abilities (writing, speaking, teaming, and reading) of Computer Science and Software Engineering students. We will integrate communication instruction and activities throughout the curriculum in ways that enhance rather than replace their learning technical content and that supports development of computational thinking abilities of the students. We will implement the approach at two institutions. By creating concepts and resources that can be adapted by all CS and SE programs, this project also has the potential to increase higher education's ability nationwide to meet industry need for CS and SE graduates with much better communication abilities than, on average, is the case today. In addition, by using the concepts and resources developed in this project, CS and SE programs will be able to increase their graduates' mastery of technical content and computational thinking. Investigation of a Novel Indoor Localization (Navigation) Technique For Smartphones Mladen Vouk ; Kyunghan Lee$75,000 by Samsung Telecommunications America, LLC - TX
01/ 2/2012 - 12/31/2014

In this project, we aim at developing a new indoor localization technique relying on low-frequency radio that can penetrate indoor obstacles (or detour obstacles by diffraction in the shortest path) by its long wave characteristics. The smartphone running this system would be able to identify its position by measuring straight-line distances from a few radio transmission towers deployed in a city scale (or in a district scale). Straight-line distances that have not been affected by indoor obstacles would be able to provide a three-dimensional position including floor information and position information in the floor (e.g., store information in a shopping complex).

Improving Energy Efficiency of Smartphones Through Elimination of Unnecessary WiFi Scans Using Cellular Signal Information
Mladen Vouk ; Kyunghan Lee

$75,000 by Samsung Electronics Co, Ltd. - Korea 12/ 1/2011 - 05/31/2014 In this project, a system providing intelligence to WiFi AP scan operations will be studied and developed for Android-operated smart devices, to reduce energy consumption in using WiFi chipsets. We ultimately aim at eliminating WiFi scans when users are mainly moving around their living boundaries by predicting which WiFi AP to connect without scanning. The prediction will be performed based on matching algorithms that find the similarity between a short term observation of cellular signal information measured in a smart device and a database of WiFi APs containing cellular base station IDs and their signal strength information per WiFi AP accumulated whenever the device is connected to a specific WiFi AP. Given our small scale measurement of energy consumption showing that WiFi scan operations drain about 10~15% of battery capacity of smartphones in their daily usages, our proposed algorithm is expected to be able to save substantial amount of energy in smart devices. Improving Energy and Data Communication Efficiencies of Smartphones through a Receiver-based TCP Control Mechanism for Cellular Networks Mladen Vouk ; Kyunghan Lee$75,000 by Samsung Electronics Co., Ltd - Korea
12/ 1/2011 - 05/31/2014

As smart devices like smartphones and tablet computers become prevalent, TCP performance over cellular networks is of growing importance. However, various measurement studies reveal that TCP suffers from excessively long delay as well as throughput degradation in cellular networks. In this project we will conduct extensive experiments over the 3G/4G networks of various cellular network carriers and investigate several under-developed issues: the current 3G/4G networks are over-buffered (termed as bufferbloat) and the excessive buffers void TCP congestion control who relies on packet loss to detect network congestion. Since all the overshot packets are absorbed by the buffers, no packet is lost and TCP will keep increasing its congestion window even if it is already much larger than the underlying bandwidth-delay product. To mitigate such problems, smartphones set the maximum receive buffer size to a relatively small value. Although this simple provisional scheme alleviates the aforementioned problem, it is losing performance in a number of scenarios due to its static nature. Through this project, we aim at proposing an adaptive receive window adjustment algorithm that requires changes only in receiver-side and implement it in Android phones and tablets.

EDU: Motivating and Reaching Students and Professionals with Software Security Education
Laurie Williams ; Emerson Murphy-Hill ; Kevin Oliver (Education)

$300,000 by National Science Foundation 09/ 1/2013 - 08/31/2015 According to a 2010 report that was based on the interviews from 2,800 Information Technology professionals worldwide, the gap between hacker threats and suitable security defenses is widening, and the types and numbers of threats are changing faster than ever before . In 2010, Jim Gosler, a fellow at the Sandia National Laboratory who works on countering attacks on U.S. networks, claimed that there are approximately 1,000 people in the country with the skills needed for cyber defense. Gosler went on to say that 20 to 30 times that many are needed. Additionally, the Chief Executive Officer (CEO) of the Mykonos Software security firm indicated that today's graduates in software engineering are unprepared to enter the workforce because they lack a solid understanding of how to make their applications secure. Particularly due to this shortage of security expertise, education of students and professionals already in the workforce is paramount. In this grant we provide a plan for motivating and providing software security education to students and professionals. Science of Security Laurie Williams ; Michael Rappa (joint coll)$211,774 by US Army - Army Research Office (National Security Agency)
06/25/2013 - 06/24/2018

Critical cyber systems must inspire trust and confidence, protect the privacy and integrity of data resources, and perform reliably. Therefore, a more scientific basis for the design and analysis of trusted systems is needed. In this proposal, we aim to progress the Science of Security. The Science of Security entails the development of a body of knowledge containing laws, axioms and provable theories relating to some aspect of system security. Security science should give us an understanding of the limits of what is possible in some security domain, by providing objective and quantifiable descriptions of security properties and behaviors. The notions embodied in security science should have broad applicability - transcending specific systems, attacks, and defensive mechanisms. A major goal is the creation of a unified body of knowledge that can serve as the basis of a trust engineering discipline, curriculum, and rigorous design methodologies. As such, we provide eight hard problems in the science of security. We also present representative projects which we feel will make progress in the discipline of the science of security.

Differential Analysis on Changes in Medical Device Software
Tao Xie

$60,000 by NSF 10/ 1/2012 - 09/30/2014 As medical device technology evolves, so too does the software upon which the technology often relies. Changes in device software, after it has been approved or cleared, may compromise the safety of that device. Assessing the safety of such changes presents special challenges to regulators at the FDA. This project explores differential analysis techniques to assess the effects of software changes on device safety. SHF:Small:Collaborative Research: Constraint-Based Generation of Database States for Testing Database Applications Tao Xie$265,880 by National Science Foundation
09/ 1/2009 - 08/31/2014

Testing is essential for database applications to function correctly and with acceptable performance when deployed. In practice, it is often necessary for a database software vendor to test their software completely before selling or integrating their package to the database owner. In this proposal, we focus on two bottlenecks in database application testing: functional testing, which is to test whether the applications can perform a set of predefined functions correctly, and performance testing, which is to test whether the applications can function with acceptable performance when deployed.

CAREER: Cooperative Developer Testing with Test Intentions
Tao Xie

$525,727 by the National Science Foundation 08/ 1/2009 - 07/31/2014 Developer testing has been widely recognized as an important, valuable means of improving software reliability. However, manual developer testing is often tedious and not sufficient. Automated testing tools can be used to reduce manual testing efforts. This project develops a systematic framework for cooperative developer testing to enable effective, synergetic cooperation between developers and testing tools. This framework centers around test intentions (i.e., what testing goals to satisfy) and consists of four components: intention specification, test generation, test abstraction, and intention inference. The project also includes integrated research and educational plans. Collaborative Research: II-EN: Infrastructure Support for Software Testing Research Tao Xie$279,000 by the National Science Foundation
06/ 1/2010 - 05/31/2014

The objective of this project is to enhance the Software-artifact Infrastructure Repository in order to enable the evaluation of various new research projects on software testing such as unit test generation.

HCC:Small:Collaborative Research:Integrating Cognitive and Computational Models of Narrative for Cinematic Generation
R. Michael Young

$352,696 by the National Science Foundation 08/ 1/2013 - 07/31/2016 Virtual cinematography, the use of a virtual camera within a three dimensional virtual world, is being used increasingly to communicate both in entertainment contexts as well as serious ones (e.g., training, education, news reporting). While many aspects of the use of virtual cameras are currently automated, the control of the camera is currently determined using either a pre-programmed script or a human operator controlling the camera at the time of filming. This project seeks to develop a model of virtual cinematography that is both computational -- providing a software system capable of generating camera control directives automatically -- and cognitive -- capable of modeling a viewer's understanding of an unfolding cinematic. ALICE: A Model for Sustaining Technology-Rich Adaptive Learning Spaces and Interactive Content Environments R. Michael Young$285,321 by Institute of Museum & Library Services
11/ 1/2013 - 10/31/2014

This proposal would fund the research and design phase of building the ALICE engine. The project will focus on creating a conceptual model for how to build an adaptive learning space; an architecture for the Artificial Intelligence (AI) engine and technology core; a series of "proof of concept" functional prototypes for collecting data and creating content; and a continuous assessment model for measuring the success of the AI as far as the quality of its engagement with the community and the success of the engine at enhancing a given technology-rich research and learning space.

DO 2 Task 3.4 -Young and Roberts
R. Michael Young

$1,017,700 by LAS/NSA 09/13/2013 - 09/30/2014 DO 2 Task 3.4 Activities TWC SBE: Medium: Collaborative: User-Centric Risk Communication and Control on Mobile Devices Ting Yu$267,096 by the National Science Foundation
09/ 1/2013 - 08/31/2016

Human-system interactions is an integral part of any system. Because the vast majority of ordinary users have limited technical knowledge and can easily be confused and/or worn out by repeated security notifications/questions, the quality of users? decisions tends to be very low. On the other hand, any system targeting end-users must have the flexibility to accommodate a wide spectrum of different users, and therefore needs to get the full range of users involved in the decision making loop. This dilemma between fallible human nature and inevitable human decision making is one main challenge to the goal of improving security. In this project, we aim at developing principles and mechanisms for usable risk communication and control. The major technical innovations include (1) multi-granularity risk communications; (2) relative risk information in the context of comparison with alternatives; (3) Discover and integrate risk information from multiple sources; (4) Expand opportunities for risk communication and control.

CAREER: Trust and Privacy Management for Online Social Networks
Ting Yu

\$450,000 by the National Science Foundation
08/ 1/2008 - 07/31/2014

Online social networks not only greatly expand the scale of people's social connections, but also have the potential to become an open computing platform, where new types of services can be quickly offered and propagated through existing social structures. Mechanisms for trust management of privacy protection are integral to the future success of online social networks. In this project, we develop theoretical and practical techniques for the management of trust and privacy for social networks. Some of the innovative expected results include a formal trust model and trust policy languages for social networks, privacy preserving feedback management, and graph anonymization techniques for the sharing of social network data.