Research Summary
The Network Science, Wireless, and Security laboratory at Virginia Tech (NetSciWiS@VT)  is a research group focused on developing fundamental mathematical tools and principles to design, develop, and build smart, secure, and self-organizing systems, with applications to networks, wireless systems, Internet of things (IoT) systems, smart power grids, and cyber-physical systems. Our research is largely interdisciplinary and draws upon tools from optimization, game theory, machine learning, statistics, control and economics to design and build networks and cyber-physical systems.

We are currently focused on several research thrusts:
  • Wireless cellular and 5G networks.
  • Virtual reality over wireless networks.
  • Integration of millimeter wave and sub-6 GHz cellular networks.
  • Wireless communications and networking using unmanned aerial vehicles and drones.
  • The Internet of Things.
  • Smart cities and critical infrastructure.
  • Cyber-physical systems.
  • Machine learning and data analytics.
  • Cybersecurity.
Research Projects
Sponsored by: National Science Foundation (NSF)
Collaborators: Virginia Tech (Naren Ramakrishnan, Harpreet Dhillon) and University of Miami (Civil and Architectural Engineering)

The goal of this project is to transform villages, towns, and cities into smart, connected, and sustainable communities by developing the first big data-driven holistic approach to joint planning, optimization, and deployment of community infrastructure for systems of critical importance, such as communication, energy, and transportation systems. By bringing together interdisciplinary domain experts from data science, electrical engineering, and civil and architectural engineering, this research will yield several innovations that range from novel big data techniques for faithfully creating spatio-temporal models for smart communities to data-driven performance metrics to explicitly quantify the health of smart communities  and advanced analytical tools  to devise the most effective strategies for deploying, upgrading, and operating various community infrastructure nodes, given the scale, dynamics, and structure of both the data and the community.


Sponsored by: National Science Foundation (NSF)
Collaborators: Harpreet Dhillon (Virginia Tech)

The goal of this project is to develop a foundational framework for the modeling and performance analysis of the Internet of Things (IoT) that will facilitate the management of resources, such as energy and computation, jointly across its cyber and physical realms. By leveraging interdisciplinary tools from stochastic geometry, distributed optimization, and operations research, the proposed framework will yield a number of results that include new statistical models and CPS performance metrics for characterizing the cyber-physical operation of IoT as well as novel distributed optimization algorithms that will adapt the cyber-physical operational state of the IoT devices to the dynamics of the CPS environment, while being cognizant of their stringent resource constraints.


Machine-to-Machine Communications in Wireless Networks
Sponsored by: Office of Naval Research (ONR) - Young Investigator Program (YIP)

A massive deployment of machine type devices (MTDs) such as wearable sensors, surveillance apparatus, and autonomous vehicles, in wireless networks is foreseen as a major driver of future wireless networking services. Indeed, MTDs will be the cornerstone of many emerging technologes. However, reaping the benefits of MTDs is contingent on the ability of the network to sustain reliable machine-to-machine (M2M) communications. Efficiently integrating M2M communications into wireless networks warrants the introduction of MTD aware resource management mechanisms to optimally allocate scarce network resources (power, time, frequency, space) among MTDs and traditional human-type connections. The goal of this project is to address the M2M challenges in wireless networks by developing a foundational framework for optimized M2M deployment and resource management by weaving together notions from wireless communications, optimization, and network science.


Sponsored by: National Science Foundation (NSF)

Providing seamless, high quality wireless service any
time and anywhere requires substantial structural changes in today's macro-cellular networks. One such change, introducing small cell base stations, is seen as a highly promising solution. However, it requires meeting fundamental challenges: 1) nodes' self-organization, 2) network heterogeneity, and 3) high sensitivity of resource allocation to the system parameters. The proposed research addresses these challenges by exploring a dimension that has often been underexplored: the user's context. To achieve this goal, we weave together techniques from machine learning, game theory, and microeconomics to lay the foundations of context-aware wireless networks.


Sponsored by: National Science Foundation (NSF)
Collaborators: Virginia Tech (Economics, Computer Science), VTTI, Rutgers University, and FIU

Realizing the vision of truly smart cities is one of the most pressing technical challenges of the coming decade. The success of this vision requires synergistic integration of cyber-physical critical infrastructures such as smart transportation, wireless systems, water networks, and power grids into a unified smart city. Such critical infrastructures have significant resource dependence as they share energy, computation, wireless spectrum, users and personnel, and economic investments, and as such are prone to correlated failures due to day-to-day operations, natural disasters, or malicious attacks. Developing resilient processes that can control and manage these interdependent critical infrastructure resources is therefore a key towards understanding how future smart cities must be operated. The goal of this project is to lay the foundations of resilient smart cities via a coordinated and interdisciplinary approach that relies on machine learning, operations research, behavioral economics, and cognitive psychology and which takes into account both technological and human factors. 


Optimal Placement of Things in an Adversarial Internet of Battlefield Things
Sponsored by: Army Research Laboratory (ARL)
Collaborators: Naren Ramakrishnan (Computer Science, Virginia Tech)

Military battlefields are gradually being transformed into a much anticipated Internet of Battlefield Things (IoBT) ecosystem which will synergistically combine communications, sensing, computing, and autonomy functions. The IoBT will consist of a heterogeneous mix of assets, devices, and systems which must be properly deployed, operated, and managed within a complex environment. One key research challenge facing the deployment of the IoBT is to optimally determine how, when, and where to place (and operate) a heterogeneous number of IoBT “things” that can range from sensors to wearables and autonomous vehicles within the largely adversarial IoBT environment. The goal of this project is to address this challenge by developing the first comprehensive and unified data-driven framework for optimizing the placement of “things” within an adversarial battlefield environment. 


Sponsored by: National Science Foundation (NSF)
Collaborators: Harpreet Dhillon (Virgina Tech)

Delivering pervasive access to data-intensive wireless applications is contingent upon enabling wireless cellular systems to sustain the foreseen 1000x increase in the demand for wireless capacity. One promising solution is via wireless network densification in which small base stations are deployed at possible adverse locations, such as lamp posts and the sides of the buildings, to significantly boost the wireless capacity. However, reaping the benefits of such dense cellular networks requires devising novel heterogeneous backhaul solutions that can connect the small base stations to the Internet and core network by smartly and jointly exploiting existing, wired infrastructure, as well as new wireless, possibly in-band, backhaul solutions. The key goal of this project is to introduce a fundamentally new cellular network design framework in which elaborate wireless, wired, heterogeneous, and possibly multi-hop backhaul models are tightly integrated with the access networks to facilitate joint analysis, modeling, and optimization of backhaul and radio wireless access. This proposed framework will marry together notions from stochastic geometry, microeconomics, and wireless communications to enable tomorrow's cellular systems to support bandwidth-intensive wireless applications such as mobile high-definition video streaming, thus expediting their global deployment. 


Sponsored by: National Science Foundation (NSF)
Collaborators: Tohoku University (Japan) and Florida International University

Delivering high-speed, pervasive wireless services to trillions of mobile devices requires a significant transformation to today's wireless cellular networks. Hyper-dense heterogeneous networks (HDHNs), enabled via a viral and large-scale deployment of small cell base stations and mobile devices, are seen as one of the cornerstones of this transformation. However, most existing network design and optimization techniques fall short in handling the scale, density, sustainability, and dynamics of such HDHNs.
This project contributes to the foundations of HDHNs via innovations that include novel mobility state estimation techniques, optimized cell selection and handover methods, and a new optimization framework for self-organizing resource management in energy-efficient HDHNs. The proposed approaches will be evaluated and enhanced via implementation on an experimental testbed using software radio and open source platforms. 


Sponsored by: National Science Foundation (NSF)
Collaborators: University of Nevada - Reno, University of Central Florida, and Florida International University

Next-generation public safety communication (PSC) systems must deliver high-capacity wireless services to public safety personnel and users in disaster-affected areas, with little reliance on infrastructure. Remarkably, modern-day PSC systems have yet to catch up with the past decade's wireless revolution, as they still rely on technologies of yesteryears that fall short on delivering high-speed wireless access. Indeed, coping with the foreseen stringent service requirements in future PSC systems mandates major innovations that can increase spectral efficiency. The overarching goal of this research is to initiate the much-needed leap towards a more open, highly participatory, and pervasive sharing of the wireless spectrum for communication networks, in general, and PSC, in particular. This is done by developing a new framework that tightly integrates the economic and technological challenges of PSC, using both theory and implementation.


Sponsored by: National Science Foundation (NSF)
Collaborators: Virginia Tech (Department of Geography) and University of Miami (Civil and Architectural Engineering)

Coastal cities play a critical role in the global economy. However, they are being increasingly exposed to natural hazards and disasters, such as hurricanes, and recurrent flooding due to the rise of sea-levels caused by climate change. The goal of this research is to create new paradigms for the resilient design of urban communities, and uniquely tailored toward the design of coastal cities. Results from this research will help make critical coastal infrastructures more tolerant to damage. The in turn will foster socio-economic resilience by enabling anticipatory interventions. The developed techniques and simulation models will redefine traditional urban design strategies through the integration of architecture, urban design, land-use planning, civil engineering, and advanced computational methods that explicitly consider socio-economic drivers. This project will be conducted in close collaboration with the cities of Miami and Miami Beach. 


Foundations of Social Network-Aware Cellular Communications
Sponsored by: National Science Foundation (NSF)
Collaborators: University of Florida and University of Houston

Providing ubiquitous access to the rapidly expanding suite of mobile social applications has strained modern-day wireless networks, motivating the need for new technologies to optimize the usage of the scarce radio resources. Device-to-device (D2D) communications between mobile devices over the reliable and pervasive cellular network infrastructure constitutes one of the most promising technologies for further accelerating the penetration of mobile social services. As compared to conventional D2D over short-range and limited-capacity technologies such as Bluetooth, D2D over cellular provides longer transmission ranges, improved spectrum sharing, higher capacities, guaranteed quality-of-service, and a broader range of applications and services. Owing to its promising potential, D2D is now viewed by both academia and standardization bodies as a cornerstone technology in emerging 5th generation (5G) wireless systems.

Leveraging cellular D2D for mobile social applications requires addressing a variety of technical challenges that are characterized by a strong interplay between social factors such as content correlation, and wireless features such as network-controlled resource allocation and interference management. The goal of this project is to address these challenges by introducing a novel network optimization framework, cognizant of both social and wireless realms, suitable for ensuring the delivery of high-speed, high-quality social networking services over cellular D2D communications. 


Sponsored by: National Science Foundation (NSF)
Collaborators: Temple University and Florida International University

The goal of this project is to develop novel mathematical principles to design secure and robust networked cyber-physical systems (NCPS) with applications to multiple CPS domains such as power systems and transportation systems. Our goal is to better understand the security of networked cyber-physical systems and more importantly recognize the role of humans, their interaction and decisions, on the security of NCPS. In this regard, a key component of our work is to apply novel stochastic game-theoretic models and control systems theory to better integrate the cyber and physical layers of networked systems while focusing on the role of humans and the effect of their behavior and interaction on the security of the joint CPS. 


Sponsored by: National Science Foundation (NSF)
Collaborators: Sanjay Raman (VT) and IoT-DC Consortium

This project will develop a novel machine learning framework that enables the Internet of Things (IoT) to dynamically identify, classify, and authenticate devices based on their cyber-physical environment and with limited available prior data. This will result in the creation of environment-based IoT device credentials that can serve as a means of attestation, not only on the legitimacy of a device's identity, but also on the validity of the physical environment it claims to monitor and the actions it claims to be performing over time. 


Sponsored by: National Science Foundation (NSF)
Collaborators: Allen MacKenzie (VT), Trinity College Dublin (Ireland), and Queen's University (Belfast, Northern Ireland)

The demand for wireless services continues to increase rapidly, and society has come to rely on the availability of wireless services everywhere and at all times. Conventional wireless services rely on communications at radio frequencies below 5 GHz. These frequency bands are heavily used, and future systems will not be able to meet all demands if operated only with these existing technologies. Recent work has created electronic devices able to generate communications signals at higher frequencies, from 30-300 GHz, which is known as the 'millimeter wave' band. Communications links in these bands have the promise of delivering enormous wireless capacity, but these links behave somewhat more like beams of light than conventional radio communications they can be directional and are easily blocked by objects and by people's bodies. The goal of this project is to provide a holistic analysis of mmWave communications  with a focus on improving services in population-dense environments like stadiums, theaters, and transportation hubs.


Sponsored by: National Science Foundation (NSF)
Collaborators: Rutgers University and Princeton University

The realization of the vision of a smart power grid in which a significant portion of energy stems from renewable sources and other prosumer-owned devices (a “prosumer” is a consumer who can take the dual role of seller and a buyer of electricity) is contingent on large-scale, active prosumer participation in energy management. However, just because such participation can yield significant technological and societal benefits, it cannot be assumed that prosumers will actually become fully involved in the smart grid. Empirical data shows that, despite its exciting prospects, the widespread adoption of the smart grid has been hindered by modest user participation. Motivated by emerging grid scenarios, this project will advance the mathematical framework of prospect theory, a seminal contribution to behavioral economics that won the Nobel Prize, to study grid energy management, as well as to understand and overcome barriers to active user participation in grid energy management.