This funding establishes a new CISE Research Experiences for Undergraduates (REU) Site at Montana State University focused on networking and networks with applications for sustainability. Each summer a cohort of undergraduate students will participate in a ten-week summer research program at the host institution. The project includes mentoring by the experienced computer science faculty members, technical seminars and workshops, student presentations, and field trips and other professional development opportunities. The REU Site program will target high-quality undergraduate American Indian students, students from tribal colleges, and students from small colleges with limited resources. Recruitment efforts will focus on computer science and engineering students as well as students from environmental science and other related disciplines. This site is co-funded by the Experimental Program to Stimulate Competitive Research (EPSCoR).
The intellectual merit of this project lies in strong research basis and the expertise of the faculty. The projects are in research areas that are current and address national priorities such as networking and sensor networks. The students participate in a full range of research activities from preparing research literature reviews to production and dissemination of research results. The project has the potential to add to the research base of networking systems.
The broader impacts of the project include providing a quality research experience to undergraduate students, particularly students from underrepresented groups. The project team is committed to including under-represented minority students in their research. Thus this project has the potential to produce new computer science graduate students and faculty members and to advance discovery and understanding while promoting learning.
Montana State University’s Computer Science Department has hosted a NSF REU site for ten undergraduate participants during the summers of 2012-2014 in a ten-week residential program. The objectives of our REU site were: 1) to expose undergraduate students to real-world, innovative and interdisciplinary research focused on networks research and network modeling with application to sustainability; 2) to encourage more undergraduates to continue their academic careers and seek graduate degrees in computer science, engineering, and environmental science; 3) to develop research skills and improve communication and collaboration skills of the participants. Our REU program has heightened undergraduate student interest and participation in computer science related research on a variety of topics. Students have acquired general research skills, helped design algorithms and developed and used tools to tackle complex interdisciplinary problems. The following projects were conducted in the 2014 program: A Step Towards Handling Large Ecological Data in R: LabDSV is an R package that is used by many ecologists and student communities. LabDSV is one of many R extensions that can experience memory limitations when users try to analyze big data, a term commonly used to describe large data sets. This project added functionality to LabDSV in order to address memory problems associated with big data. Load Scheduling to Match Wind Generation Using Particle Swarm Optimization: In order for the power grid to function, the generated supply must match the demand. In this project a particle swarm optimization approach is used to schedule loads to match wind generation. IP2DC: Latency Estimation Using CDN Servers: Web applications today often deploy replica servers to deliver service or use host clustering as part of their application. This project investigated a new latency estimation system for arbitrary hosts using host-to-CDN latency measurements. Compared to existing latency estimation tools, our technique offers superior coverage and latency estimation accuracy. Relaxing Consensus in Distributed Optimization of NK-Landscape Models: Overlapping population-based optimization models have proven fast and efficient, often outperforming established methods using single populations. This project developed an experimental framework for applying and testing the OPO model in distributed and non-distributed settings, with abstractions allowing for various optimization algorithms, sub-population architectures, and levels of communication between subpopulations. Understanding Trustworthiness in the Advogato Online Community: Methods of establishing trustworthiness in an online environment are often severely restricted without the possibility of face-to-face interaction. This project examined three-valued subjective logic as a means to evaluate trustworthiness within a network by performing several analyses using the online community Advogato. Our REU site has helped address the nation’s need for a diverse group of innovative computer science and engineering researchers and professionals capable of using a variety of technologies to address networking and environmental problems in a sustainable way. Participants were encouraged to take a systems-level perspective in solving problems from an ever-growing number of diverse commercial, educational and national defense domains. The program has also helped increase student awareness of cultural diversity and has bolstered the academic confidence and interest among underrepresented groups in the field.
