Research Projects

Project Title: CAREER: Leveraging Wireless Virtualization for Enhancing Network Capacity, Coverage, Energy Efficiency and Security

Project Period: 06/30/2016 - 07/1/2021

Amount: $400,001.00

Funding Agency: National Science Foundation (NSF)

PI:  Danda B. Rawat

Website: http://wivi.info/

Project Description: This CAREER project focuses on the design, analysis and evaluation of a Wireless Virtualization (Wi-Vi) framework by combining different wireless resources and infrastructures, beyond spectrum sharing with licensed users, to be used as on-demand service over the network, with the goal of enhancing network capacity, coverage, energy efficiency and security. The PI will develop Wi-Vi architecture using systematic approaches to improve overall network performance. Specifically, the significance of the proposed research includes: 1) development of a generalized wireless virtualization framework that will help meet dynamic demands of wireless users by expanding or shrinking wireless resources of the virtual wireless operators; 2) study and implementation of optimal wireless resource sharing among coverage- and capacity-driven Mobile Virtual Network Operators (MVNOs); 3) development of systematic approaches for base station-level, MVNO-level and user level optimizations and Quality-of-Service (QoS) provisioning; 4) application of wireless virtualization in network security through dynamic network segmentation; and 5) validation and evaluation of the proposed novel techniques through extensive simulations and experiments in NSF-funded cloud testbeds such as ROAR, Chameleon, etc. The CAREER award will have a broad societal impact as wireless networks touch every aspect of our society, and will support enhancement of our national wireless capacity and cybersecurity. This project will impact many emerging areas in which wireless communication has applications - such as smart grid, eHealth, vehicular networks, next generation cellular networks, Internet-of-things, cyber-physical systems and secure cyberspace. The PI will train undergraduate and graduate students by disseminating knowledge to students through new courses and modules on wireless virtualization and next generation wireless networks. Overall, the PI will establish an integrated research and educational program to train future scientists and engineers in the area of next generation wireless networks and to inspire young people's interest (including K-12 students) in science and engineering fields at the early stage of their learning career.

Project Title: Security Engineering for Resilient Networked Critical Infrastructure

Project Period: 08/09/2017 - 07/31/2022

Amount: $1,198,627.00

Funding Agency: US Department of Homeland Security (DHS)

PI: Danda B Rawat

Website: https://sites.google.com/view/criticalinfrastructuresec

Project description: The Security Engineering project integrates education and research that may result in practical security and resilience for the Internet of Things (IoT) and cyber-physical systems (CPS) that comprise network-connected critical infrastructure. Embedded and cyber-physical systems are increasingly vulnerable to attack especially because of ubiquitous network access—the Internet of Things (IoT) refers to the proliferation of such systems. Device heterogeneity and emerging communication protocols make it difficult to understand the scope of an IoT application’s attack surface, much less secure it. This project explores the security of IoT devices through an IoT Security Testbed that will enable further research exploration in the area of IoT Security and resilience.

Project Title: Collaborative Research: Transforming Data Science Education through a Portable and Sustainable Anthropocentric Data Analytics for Community Enrichment Program 

Project Period: 08/09/2019 - 09/31/2021

Amount: $449,955.00

PIs: Jiang Li (EECS), Danda Rawat (EECS), Yayin Fang (Medicine), Shaolei Teng (Biology) Jae Eun Chung (Communication)  

Project description:  This project will focus on human-centric analytics, or anthropocentric data analytics, to provide a common ground for beginning studies in data science and to prepare students to address interdisciplinary problems. As one of the most promising subareas of data science, human-centric data analytics either considers humans as the research object or involves humans as the executors over all stages of data analytics. The proposed Anthropocentric Data Analytics for Community Enrichment (ADACE) project will form a three-institution partnership, with University of Tennessee at Chattanooga (UTC) as the coordinating organization, and UTC, Chattanooga State Community College and Howard University as implementing organizations. Together they will address the challenge of developing a large, high-quality workforce skilled in data-related disciplines. This is essential for the United States to maintain its competitiveness in the 21st century. The project aims to establish an interdisciplinary platform with a curriculum that integrates real-world community research projects. In today's increasingly globalized world, data science occupations are essential for sustained social and economic development. Most U.S. colleges and universities are witnessing an increased interest from students in these programs offered by computer science and other related departments. However, a lack of training programs and community engagement through real-life projects makes it difficult to keep students engaged and interested. Limited access to internships can also reduce students' success in data science and may even direct them away from these fields. This project addresses the critical need to attract higher numbers of talented students, to better stimulate students' interest, to increase the retention rates, and to eventually meet the rising workforce demand.

Project Title: Security Engineering with Distributed Machine Learning for Adversarial Resiliency

Project Period: 08/09/2018 - 09/31/2019

Amount: $160000.00

Funding Agency: Intel

PI: Danda B Rawat

Website: https://sites.google.com/site/secureadversarialml/

Project description: This project integrates education and research that may result in practical security and resilience for distributed machine learning and  adversarial machine learning.