Network Sciences

Extramural Basic Research Network Sciences

U.S. Army Research Office
P.O. Box 12211
Research Triangle Park, N.C. 27709-2211

Commercial: (919) 549-4321
DSN: 832-4321
Fax: (919) 549-4310

Work over the past 10 years by researchers in various fields including Statistical Mechanics, Anthropology, Biology, Distributed Systems, Theoretical Computer Science, Robotics and Control theory has shown that there is a lot of commonality in the structure of networks around us, including communication among a school of fish, pack of wolves, a group of jihadists or the nodes of an ad hoc wireless network. The goal of the Network Sciences program is to make use of this commonality, in a synergistic way, to address issues of importance to the Army. Networks of sensors, communication and computation nodes, and robots are pervasive throughout the Army and especially in Command, Control, Communications, Computing, Intelligence, Surveillance, and Reconnaissance (C4ISR) systems, and these networks are impacted by and have an impact on human behavior. The Network Science program identifies and addresses the Army's critical basic research problems in C4ISR where progress has been inhibited by a lack of novel concepts or fundamental knowledge. Research in this program has application to a wide variety of developmental efforts and contributes to the solution of technology-related problems throughout the Army's Future Force operational goals. The Network Sciences program is divided into the following areas of research:

  • Communications and Human Networks addresses research for the fundamental understanding of wireless communications and human networks. In communications, the program focuses on research to further the understanding of tactical mobile wireless communication for the battlefield of the future. For human networks, identifying structure of networks from diverse data is of particular interest.
  • Intelligent Networks augment human decision makers with enhanced-embedded battlefield intelligence that will provide them with tools for creating necessary situational awareness, reconnaissance, and decision making to decisively defeat any future adversarial threats. The challenge is to find methods that facilitate the development of intelligent and autonomous systems that perceive their environment by means of sensing and through context, and use that information to generate intelligent, goal-directed desired behaviors.
  • Multi-Agent Network Control is concerned with modeling, analysis, design, and robust control of complex real-time dynamic systems, including distributed and embedded, networked autonomous and semiautonomous, nonlinear, embedded and hybrid, and decentralized systems. The program also involves innovative research on emerging areas such as net-centric control and the interaction of control with biological organisms.
  • Social and Cognitive Networks will advance the social sciences perspective on studying social networks and human behavior in the context of Network Science, by blending the methodological rigor of social sciences with computational tools from Computer Science and analytical tools from mathematical sciences. Specific topics of interest include, but are not limited to, multilevel social network analysis and diffusion and propagation of beliefs and behaviors.

Division Chief

Dr. Purush Iyer
(919) 549-4204

Communications & Human Networks

Dr. Robert Ulman
(919) 549-4330

Research in this area is concerned with the application of communications and network theory, signal processing, and mathematics to enable the fast, accurate, reliable, and efficient transmission of information for the wireless digital battlefield. Due to their low probability of interception, anti-jam, and multiple access characteristics, spread spectrum techniques are important to Army communications, intelligence, surveillance, and target acquisition systems. Methods for design and performance analysis of spread spectrum systems are being studied. The vulnerability of spread spectrum systems to jamming and interference and the use of adaptive electronic counter countermeasures (ECCM) techniques to improve network performance in the presence of jamming and interference are being investigated. Network science is being investigated to understand the fundamental limits of wireless ad hoc networks and the performance of proposed algorithms.

The digital battlefield requires a seamless, ubiquitous, survivable and highly mobile wireless communication system with a highly dynamic network topology. The information communicated ranges from voice to video and includes bursty file transfers for vehicle and aircraft radio, as well as light weight radios carried by Soldiers on foot. The channels are noisy and unreliable due to jamming, mobility, multipath, and multiuser interference. To provide the necessary capability, research is supported in spread spectrum, mobile ad hoc radio networks in the areas of multimedia network architectures, distributed routing, congestion control, and heterogeneous network integration. Research is also supported in adaptive source and channel coding, networking with adaptive antennas, adaptive routing to avoid failed nodes, and power control. Of particular interest is the science of networks as applied to the tactical wireless network problem including an understanding of its performance limits. Finally, of growing interest is the use of the concepts used in cognitive radio applied to the overall network in the emerging area of cognitive networks.

There is a natural interdependence between communications networks and human networks, as seen in the recent emergence of social media websites. Research in human networks emphasizes this interaction between the communications network and the human network. Network structure and dynamics, as well as the effects of the network on information and belief propagation, and prediction of phase changes are also of interest to this program. Mathematical techniques utilized in communications networks and other network analysis, such as network information theory, graph theory, game theory, data mining, and Markov chains, will be leveraged to analyze human networks. This subtask is closely coordinated with the Social and Cognitive Network Task.

Social and Cognitive Networks

Dr. Edward Palazzolo
(919) 549-4234

The goal of Social Cognitive Networks program is to understand human beliefs and behaviors that lead to group level phenomena particularly those relevant in military settings. Social networks are the underlying structure of interaction and exchanges between humans within both strategically designed and self-organized systems. Social networks allow collective action in which groups of people can communicate, collaborate, organize, mobilize, or attack. Social influence processes determine how ideological groups form and dissolve, information and beliefs spread and interact, and how populations reach consensus or contested states. The changing nature of DOD's doctrines and mission has greatly increased the need for models that capture the cognitive, organizational and cultural factors that drive activities of groups, teams and populations. Better understanding the human dimension of complexity will provide critical insights about emerging phenomena, social diffusion and propagation, thresholds and tipping points.

Projects supported by the social-cognitive networks program will contribute methodological advancements in modeling dynamic social network structures and substantive knowledge about the cognitive and psychological factors that enable emergent behaviors and capabilities. The U.S. Army is particularly interested in research that uses defense-relevant empirical data to feed into computational models. As such, this program seeks to fund projects that are successful in blending theories and methods from the social sciences with rigorous computational methods from computer science and mathematical modeling.

Methodological research in this program will collect data, build multi-agent models and design dynamic simulations that resolve issues around (a) scalability of networks, (b) multilevel (nested) systems, and (b) imputing network links and identifying meaningful subgroups. These projects could include research that examines small group dynamics within big data sets; multilevel models that account for nested cognitive, social, cultural, physical dimensions of systems; link and subgroup estimation algorithms to deal with incomplete data and clandestine activities.

Topical research areas in this program include (a) diffusion /propagation dynamics and (b) collaborative networks. Diffusion dynamics research will focus on formation and dissolution of civic-minded and violent networks, mobilization of benign to hostile political movements; propagation of and enduring changes in attitudes; and network-based interventions. Organizational network research will investigate network models of collaborative communication as they relate to information spread, information fidelity and organization performance through different structural/topological classifications of networks.

Intelligent Networks

Dr. Purush Iyer
(919) 549-4204

Augment human decision makers with enhanced-embedded battlefield intelligence that will provide them with tools for creating necessary situational awareness, reconnaissance, and decision making to decisively defeat any future adversarial threats. The challenge is to find methods that facilitate the development of intelligent and autonomous systems that perceive their environment by means of sensing and through context, and use that information to generate intelligent, goal-directed desired behaviors. This area of research poses unique challenges for the Army as it involves developing autonomous capability for mixed teams of air and ground vehicles that acts to complement a Soldier's capabilities.

The focus is on developing a formalized mathematical, algorithmic, and practical understanding of designing and building autonomous systems to aid Soldiers and decision makers in discovering relevant knowledge for situational awareness. Research is sought in:

  • Mathematical Reasoning of Groups and Societies, bringing together elements of game theory, knowledge representation, network science and social sciences, to understand adversaries and to use wisdom of crowds in solving decision-theoretic problems.
  • Robust Reasoning Under Uncertainty, where the ability to adapt or compensate, in reasoning, for the uncertainty inherent in real systems related to modeling error, sensing errors and noise, system failures, and changing dynamic environments, are important. In particular, mathematical limits on what is efficiently and effectively computable, based on observations of networks, are as relevant to the program as trade-offs between efficiency and accuracy of inferences drawn about the observed networks.
  • Integrated Intelligence, where subcomponents for vision, knowledge representation, reasoning, and planning are integrated in a synergistic fashion to yield a sum that is more than its parts
  • Knowledge Discovery in Large Graphs, including new paradigms for carrying out scalable searches and foundational work on limits of what can be searched for (within laws, such as privacy and secrecy laws, of a society).

Multi-Agent Network Control

Dr. Alfredo Garcia
(919) 549-4282

The Multi-Agent Network Control program is concerned with the problem of inducing desirable outcomes (i.e. control) in systems composed of multiple heterogeneous agents which may interact locally or through aggregate statistics of the relevant features of the system. The program seeks to fund contributions to the modeling, analysis, design and control of complex real-time physical and information-based systems; including distributed and embedded, networked autonomous and semi-autonomous, nonlinear, smart structures, and decentralized systems. Specifically, the program invests in research in:

  1. Distributed and/or decentralized control and optimization mechanisms governing the interaction of heterogeneous multi-agent teams in order to induce desired outcomes. Research in this area should contribute to a better understanding of the tradeoffs between what can be achieved by a multi-agent system (e.g. controllability) versus (i) information processing requirements, network topology and computational overhead (ii) individual-agent control actuation capabilities, (ii) degrees of autonomy and cognitive-behavioral issues arising from human-system interaction.
  2. The study of mechanisms under which the heterogeneous components of interconnected dynamical systems may self-organize to achieve desirable global performance. Theories that provide an endogenous description of a multi-agent system heterogeneity and network structure are of special interest.
  3. Fundamental systems and control theory and relevant areas of control science (e.g. multivariable control, nonlinear control, stochastic and probabilistic control) as they inform and/or support (1) and/or (2).
  4. Game theoretic approaches for distributed control that take into account the effects resulting from the networked interaction between technology, information and humans to induce desired emergent behaviors. Mechanism design for networked agents with and/or without transfers.
  5. Mathematical techniques for analyzing stochastic dynamical systems arising from models of interacting agents taking into account heterogeneity and asymmetry with a special emphasis on characterizations of convergence to equilibria.

Additional Information


Last Update / Reviewed: July 26, 2016