Rahul Simha - US grants

9505963 Mao Data traffic in networks has always been dominated by file transfers. In today's high-volume applications like the Internet bulletin boards, most files are simple text files. In the future, files are expected to consist of hypertext documents, with significant audio and video components. Already, a few seconds of low-quality audio occupy hundreds of kilobytes. These numbers are indicative of the large sizes of future multimedia files. Other applications of the future which are thought to involve large file sizes are those arising from scientific applications, large-scale databases and network-wide system backups. In this proposal the principal investigators take issue with the notion that large files should be routed as small files conventionally are -- by breaking up the file into packets and relying on packet routing algorithms. They examine and propose to study the problem of scheduling large file transfers. Past approaches traditionally avoid collecting information across networks to schedule particular files, simply because the overhead of doing so overwhelms any benefits accrued in computing optimal schedules. However, when file sizes are very large and are also known in advance of transmission, it makes eminent sense to collect information and compute good schedules, thus utilizing network resources efficiently. The researchers will formulate a file transfer scheduling problem, argue its importance, assess shortcomings in the available research on this problem and outline issues for future research. *** ******* Darleen Fisher Program Manager Networking and Communications Research Program 4201 Wilson Blvd. Room 1175 Arlington Va 22230 (703) 306-1949 (703) 306-0621 (FAX)

9712718 Simha, Rahul Leemis, Lawrence College of William & Mary CISE Educational Innovation:Undergraduate Modeling, Simulation and Analysis This CISE Educational Innovation award supports the development of a new course sequence in computational science for undergraduates. The program, entitled Undergraduate Modeling, Simulation and Analysis (USMA), enables qualified undergraduates to broaden their educational experience via small group interaction with faculty who are active researchers in modeling, simulation and analysis. The USMA program provides formal courses in these areas as preparatory work for research in computational science, encourages small-group interaction with research-active faculty via a mentored research seminar, offers an integrative interdisciplinary project based on an application from engineering or the sciences, creates a mechanism for students from Hampton University to participate in the USMA program and begins to incorporate courses in computational science at that institution, as well.

EIA-9977030
Voigt, Robert G.
Simha, Rahul
College of William & Mary

MRI: Acquisition of High Performance Clusters for Effective Parallel Computing in Computational Science Research and Education

The PIs request funding to purchase and operate a high speed network of computer systems that will complement state investment in computational science at College of William and Mary and help drive significant, related research and educational activities. The equipment will be used as the centerpiece of the common research focus: the effective use of parallel systems for scientific computation. The PIs seek hardware that balances the many needs of their activities. The selected architecture consists of three interconnected subsystems each of which is a cluster of workstations or PC's. Two of these are 16-processor and 32-procesor Pentium-based Beowulf-like systems built with different interconnection networks, and the third is a combination of four 4-processor SUN multiprocessors.

Computer Science (31)

We are creating and refining materials for a two-course undergraduate sequence in the area of e-commerce to meet two nationwide educational needs in computer science: 1) the lack of tested course materials in the area of e-commerce, and 2) the lack of significant opportunities for computer science students to pursue team work in an interdisciplinary setting.

The first course covers web technology for computer science majors and minors; the second is a unique interdisciplinary e-commer course open to students of all disciplines. In the second course, CS students have a different set of requirements than non-CS students as they provide technical expertise learned in the first course to student teams.

EIA-0216137
Rahul Simha
George Washington University

MRI: Acquisition of Research Infrastructure for Distributed Sensor Applications in the Home of the Future

This proposal, developing an infrastructure for applications that can exploit a network of sensors and actuators in the home environment, extends work already in progress on future technologies aiming at launching a long-term research program around the Home-21 theme with a broader base of applications and a stronger research focus. Applications (with respective examples) involve:
1. Sensors distributed around the home (detecting intrusion),
2. Sensors on an occupants (helping monitor infirm or disabled occupants), and
3. Sensors on a service provider (helping a fireman navigate a burning home).
Faculty with research interests in networking, human-computer interaction, MEMS devices, sensors and biomedical engineering will collaborate on a single infrastructure to support these classes of applications. Although the theme centers on the home of the future, the infrastructure and applications apply to other living environments including, for example, hotels, dormitories, offices, ships, and assisted-living facilities. Special attention will be devoted to applications that will use sensors and actuators on occupants at multiple level of granularity, coarse-grained (location of occupant within the house) and fine-grained (movement of limbs). Such applications involve placing sensors on the occupant that are wireless connected to algorithms that track movement and can, in some cases, also send location-specific feedback (via the actuators) in accordance with the desired objective. Ancillary projects involve Safety (falls, fire, etc.), Security (intrusion monitoring), Health Monitoring Measuring (measuring telemedicine applications, monitoring and relaying vital signs), and RF monitoring (controlling harm from electromagnetic radiation). The equipment, including magnetic trackers, wireless equipment, RF analyzer and software, and support equipment, serves as a testbed for senior design students. Hence, a key component is its focus for undergraduate research and training.

ITR: A Compiler-Hardware Co-Design Approach to Software Protection

PI's: Rahul Simha, Bhagi Narahari, Alok Choudhary, Nasir Memon

Abstract:

The growing area of software protection aims to address the problems of code understanding and code tampering along with related problems such as authorization. This project will combine novel techniques in the areas of compilers, architecture, and software security to provide a new, efficient, and tunable approach to some problems in software protection. The goal is to address a broad array of research issues that will ultimately enable design tools such as compilers to assist system designers in managing the tradeoffs between security and performance.

The main idea behind the proposed approach is to hide code sequences (keys) within instructions in executables that are then interpreted by supporting FPGA (Field Programmable Gate Array) hardware to provide both a "language" (the code sequences) and a "virtual machine within a machine" (the FPGA) that will allow designers considerable flexibility in providing software protection. Thus, by using long sequences and PKI to exchange a secret key with the FPGA while also encrypting the executable with that secret key, a system can be positioned at the high-security (but low-performance) end of the spectrum. Similarly, as will be explained in the proposal, by using shorter sequences and selective encryption, one can achieve high-performance with higher security than is possible with systems that rely only on obscurity.

The Computer Science (CS) community has witnessed decades of research into security techniques for commonplace transactions such as banking or voting. Yet, powerful cryptographic techniques - such as
encrypted ballots for voting - have not made their way into the public domain. A large part of the reason is that the current standard for electronic voting is pass/fail in nature, and provides no incentive for the use of novel techniques. Further, while desired properties of voting systems (such as count integrity and ballot secrecy) are mentioned in the standard, they are not well-defined, nor is the standard centered on the properties. Instead, the standard is centered on specific designs of voting systems from over fifteen years ago. As a result, innovative systems, in addition to having their advantages obscured by a pass/fail standard, also face hurdles for not being based on the old designs.

This project is aimed at pursuing an important near-term (Spring 2005) opportunity to change the basis on which electronic voting systems are evaluated. Technical recommendations are to be made to the U.S. House of Representatives in Spring 2005 by the Senate-appointed Election Assistance Commission (EAC), under the Help America Vote Act (HAVA). This group of researchers hope to contribute the recommendations. In particular, the group is working together to rate and compare voting systems on performance with respect to well-defined properties such as: ballot secrecy, count integrity, voter and public verifiability, system transparency, reliability, usability and accessibility for the handicapped. The requirement for such a framework is urgent, as the HAVA deadline is firm and another opportunity to contribute to the conduct of mass elections in the U.S. may not appear again soon.

This project will contribute to the technical core of the recommendations to the Senate by working closely with the Technical Guidelines Development Committee (TGDC) of the EAC and the Voting Systems Standards Project of NIST. The project will develop a rating mechanism that captures the properties of the flow of information among voters, voting machines, aggregation processes, counting and auditing. The investigators hope to test a prototype against some of the key dimensions of the performance rating system developed.
The project will also develop a test suite to enable testing with respect to some of the properties for large
numbers of votes.

Intellectual merit: The project will help refine the debate on voting systems by defining a technical core
for ratings of performance with respect to specific properties. It will also develop a test suite and study
the scalability of a leading cryptographic technique. Outcomes of this project will include (a) the
security and privacy aspects of the technical core used to evaluate voting systems and (b) an open-source
prototype voting system.

Broader impact: The project will contribute to the process of determining a new voting standard through input to the technical recommendations of the EAC and will make available to public interest groups for analysis and education the first open-source prototype of a voting system with voter verifiability. The project will also help train graduate students in the area of security, and will help develop ties between the computer science community and public interest groups engaged in democratic processes.

Physics(13) Faculty from George Washington University's departments of physics, biology and computer science are developing a novel introductory physics course that extends the NSF-supported SCALE-UP (Student-Centered Active Learning Environment for Undergraduate Programs) curriculum to investigations of biological systems. For this calculus-based introductory mechanics course, the biological applications drive the introduction of the physics principles rather than being mere sidebars. The project is producing in-class activities, problem sets, and computation exercises using biologically-inspired alternatives. The course is using microbial motion and molecular dynamics as central motivating examples, while simultaneously introducing students to grand challenge problems. Additional important course elements include student-created videos, student self-reflections, and career planning. Materials provided by this project will enable physics departments interested in increasing enrollments to develop a new and innovative interdisciplinary course with a minimum of effort.

This project focuses on one of the most popular models of complex networks, Boolean models, and proposes a new approach based on a process-viewpoint. In contrast to the standard attractor-basin portrait of a discrete dynamical system, the process-viewpoint starts with a single sequence of states and addresses the types of networks that might produce that sequence. The sequence of states, a process, corresponds to a time-course in biological terms and is often the only dynamical data available for real systems. The types of research questions include: what networks produce a given biological process? How do those networks differ and what do they have in common? This project will also consider the space of processes and the types of questions that arise from characterizing the space: Are some processes harder to build networks for? Do some processes need different network properties than others? The approach used is based on mathematical logic and results in a single expression characterizing the space of networks for a given process.

The importance of this research project is threefold. First, the research has the potential of increasing our understanding of complex biological networks, whose functioning is the basis of living systems. Second, the approach might result in a practical algorithm for inferring network structure from the types of data available today; this is significant because the underlying network structure is very difficult to infer with current technologies. The precise network structure and dynamics is essential to understanding how particular reactions within the cell work. Finally, the project will help increase our understanding of complex systems in general. Biocomplexity is merely one type of complexity; to the extent we make headway in building computational tools to help understanding this type of complexity, similar tools are likely to help with other types of complexity. Certainly, this has proved to be the case for other complexity-tools such as small-world networks, scale-free graphs and phase transitions.

This project focuses on hardware features
to improve the security of software systems.
By refining the coarse-grained protections available in
today's architectures, the project will aim to protect
the integrity of individual software objects or components.
The hardware mechanisms force tight controls on
the execution of software components, which
programmers can define to be as large as entire
applications or as small as individual objects.
The goal is to rapidly detect and also recover from attacks that
improperly access memory or take over the CPU.
The approach also includes hardware-supervised
recovery, to enable systems to return to normal
operation after an attack and to protect the recovery
process itself from attacks.

The benefits of this project include the ability to
thwart a large class of attacks and the potential of
developing more robust software systems in the future.
Recovery, which has received somewhat less attention than
attack prevention or detection, is especially important for
embedded systems that do not have the luxury of intervention
by human operators.

The project will be used to train graduate students and to
feed material into graduate courses taught at the three
participating universities. Modules will also be developed for
use in K-12 education with the aim of drawing students into
considering careers in computer science and engineering.

This WIDER planning project is addressing the challenges of student learning, diversity, and retention in STEM by promoting evidenced-based pedagogies with proven organizational change frameworks. The project is being implemented by a team of faculty with a depth and breadth of accumulated expertise in transforming faculty educational practices. The team is working work with colleagues in ten STEM departments to develop a framework in which to pilot the use of four effective pedagogies, as a prelude to a larger implementation phase. The four pedagogies are: (1) Peer-instruction; (2) SCALE-UP; (3) Blended learning and flipped classrooms; and (4) Online customized tutoring in mathematics to accompany mathematics and statistics coursework. To achieve the transformation, the project will focus on core faculty beliefs about student learning as a means for identifying opportunities for transformation. The project will also rely both on proven transformative processes at GW, such as faculty learning communities, as well as organizational change approaches recommended in the education community, such as the Concerns Based Adoption Model (CBAM). The project will forge the collaborations among faculty needed to adopt future developments in STEM pedagogy, and to form an agent of transformative change on campus.

This project will also seek to understand the core issues in recruiting and retaining students from non-dominant and underrepresented groups, as well as impact student learning in non-major STEM courses through the use of evidence-based pedagogies. The change processes and materials developed in this project can serve as a model at other universities.

The George Washington University Mathematics and Statistics Training, Education, and Research (MASTER) program is designed to excite students about the mathematical questions and techniques underlying the computational challenges of analyzing large-scale data. The program will be run by the Departments of Mathematics and Statistics, with support from faculty in Computer Science. Computational and Data-enabled Science and Engineering (CDS&E) has now emerged as a distinct intellectual and technological discipline lying at the intersection of applied mathematics, statistics, computer science, core science and engineering disciplines. The program will help educate mathematics and statistics undergraduate students who are prepared to confront new challenges in CDS&E. Training students to think mathematically while working with big data will prove useful for students' successful careers in many application areas.

The project will feature curricular enhancements, research mentoring, and faculty development. The curricular enhancements will add new courses centered about the theme of CDS&E; the undergraduate research mentoring program will provide research experience for talented undergraduates majors in mathematics or statistics. The research projects will themselves involve CDS&E research questions arising from network dynamics, biological data analysis, clustering, topology of large data sets, and compressive sensing. Among the new courses to be offered are mathematics of networks, the statistics of data exploration, and CDS&E mathematical modeling; the courses will be focused on the variety of topics, including network data analysis, biological network data, graphical techniques for data exploration, statistical computing, dimension analysis, and modeling of large data sets. Summer workshops for faculty will enhance the skills of college faculty in CDS&E.

This project aims to serve the national interest by improving the supply of well-prepared computer science professionals capable of addressing the needs of American employers in the public and private sectors. This project intends to build a national partnership between employers and academia to help identify and mitigate gaps between the competencies of computing graduates and the expectations of potential employers. The project will survey computer science educators and practitioners to develop a model that defines the competencies expected by potential employers. The project team then plans to test the model at three institutions of higher education in Alabama – the University of Alabama, Tuscaloosa, Tuskegee University, and Shelton State Community College. Finally, the project team intends to develop tools and methods for institutions to identify and implement competency-based educational approaches for computer science across the nation.

The project plans to use three interconnected strands of evidence-based activities to institute transformational change in the involved communities. First, a national strand will engage U.S. faculty in developing competency-based curricula informed by industry practitioner feedback. Second, a local pilot strand intends to create transformative curricular change based on student competencies using an evidence-based change model in the three Alabama institutions. Sociologists and computing faculty on the team will help to understand, predict, and reduce barriers to competency-based employment of computing graduates from marginalized communities in the heart of the impoverished Alabama Black Belt. The unique perspective relative to diversity, equity, and inclusion needs should serve as a model for other computing departments. The third strand will develop competency-based surveys for practitioners and academics to identify and refine specific competencies that are hoped to drive continual curricular change. Outcomes, including the change process, national workshops, and experiences from the local process will help with transferability in the computing education community. In addition to informing curricula, the project will provide valuable data for educational researchers to help close the gap between employers and higher education. Finally, as the competency approach to curricular design is relatively new in computing and engineering disciplines, lessons from this project will have the potential to transform curricular review and design in other STEM disciplines. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Institutional and Community Transformation track, the program supports efforts to transform and improve STEM education across institutions of higher education and disciplinary communities.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.