Research Programs from BAA - Network Sciences

1.0 Overview

Work over the past ten years by researchers in various fields including Statistical Mechanics, Anthropology, Structural 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—be it communication among a school of fish, pack of wolves, a group of jihadis, or an ad-hoc wireless network. The goal of the Network Science Division 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. The Network Science Division 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 ARO supports and advances fundamental research and knowledge that focuses on the needs of the Army's effort to be net-centric. To accomplish this objective, the Division supports extramural basic research in the four areas of Communication and Human Networks, Intelligent Networks, Multi-Agent Network Control, and Decision Sciences. The boundary between these programs is fluid; and thus, a research topic might fall in more than one area. However, a common theme of all these extramural research programs is their relevance to the Army.

1.1 Communication and Human Networks

This program is concerned primarily with establishing the fundamental understanding necessary to support the Army's future mobile, wireless tactical battlefield communications needs. These systems must support broad-based and highly mobile communications and must perform in environments of impressive diversity, from dense foliage to dense urban obstructions, and unintentional and intentional jamming. Future Army tactical communication systems for the digital battlefield will consist of many different types of networks and must be capable of communicating on the move. These systems will be highly mobile creating highly dynamic network topologies (mobile ad-hoc networks) and routing multimedia (voice, data and video) data. Also of interest is interaction between communications and human networks.

1.1.1 Wireless Network Theory

Research is required in the broad area of wireless network science including fundamental limits, performance characterization, novel architectures, and high-fidelity simulation. Metrics, fundamental limits, and performance need to be characterized for multihop wireless networks with mobility, node loss, and bursty traffic. New simulation techniques are necessary to allow for very large simulations without losing the fidelity at the physical layer that is necessary for realistic results.

1.1.2 Mobile Ad Hoc and Sensor Networks

Research is required in the area of mobile ad hoc networks, including cross-layer design, robust, survivable and cooperative networking, and physical-layer design. Low-energy consumption is of primary concern for sensor networks. In order to meet energy, throughput, and QoS requirements, cross-layer design is necessary from the physical to the admission control and transport protocols. Robust and survivable network solutions are needed to recover from network disconnects, failures, and malfunctioning nodes in order to minimize disruption to communications and services. LPI/LPD/AJ and physical-layer authentication are key design considerations.

1.1.3 Network Integration

The integrated network may be highly heterogeneous, including disadvantaged nodes with severe energy and bandwidth constraints, as well as mobile access points such as in unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and satellites. There is a need for managing the heterogeneity of networks, nodes and protocols, for resolving interoperability issues when a common platform does not exist, as well as creating network architectures that maximize performance. Research is needed in spectrum management and reuse, including wideband sensing and networking protocols, and implementing spectrum policy.

1.1.4 Human Networks

Topology, dynamics, and information flow within human networks is of interest as well as interaction of communications and human networks. In particular, this program will leverage mathematical techniques invented in the context of communication networks, such as network information theory, graph theory, and Markov chains, to analyze human networks. Interaction between human and communications networks need to be analyzed, such as the interaction of QoS communications goals with the requirements of the human network in a tactical scenario.

Technical Point of Contact: Dr. Robert Ulman, email:, +44-1895-626518

1.2 Decision & Neuro-Sciences

TThe objective of the Decision and Neurosciences Program is to develop theoretical foundations, models, and algorithms to support timely, robust, near-optimal decision making in highly complex, dynamic systems, operating in uncertain, resource-constrained environments with incomplete information against a competent thinking adversary. Although, based on operations research methodologies such as modeling, simulation and numerical optimization, this program is expected to include multidisciplinary emphasis to accommodate complex, multidimensional decision frameworks in today's asymmetric warfare. Examples of research that could contribute towards this unifying goal are the following::

  1. Modeling and simulation of contemporary environments (addressing adversarial strategies, classic terrain features, demographically informed population information, as well as dynamic temporal information) with the objective of decision support.
  2. Fundamental graph theory and network analysis in support of modeling social networks and other complex systems behaviors and processes.
  3. Numerical optimization and modeling to include capabilities for stochastic behaviors, novel approaches that address more general conditions and distributions.
  4. Bayesian and other evidential reasoning and fusion approaches to model wide ranging, perhaps real time, and incomplete information.
  5. Sequential dynamic decision making approaches.
  6. New algorithms with provable or demonstrable improved performance bounds.
  7. Game theoretical and simulation approaches applied to asymmetric warfare situations.
  8. Empirical studies into physiological, psychological and cognitive modeling of decision making.

This new program, just initiated in FY09, advances work in developing improved and robust models and algorithms taking into account multiple complex factors, including highly stochastic and dynamic behaviors.

1.2.1 Stochastic Optimization

Research into numerical methods to improve current optimization algorithms should address more general conditions: nonlinearity, generalized differentials, stochastic properties (constraints and objective function), mixed integer constraints, as well as highly complex and dynamic properties. Both mathematically convergent and heuristic methods are to be considered. Specific efforts to improve and extend network and graph theory-based methods that take into account social and cultural properties are important.

1.2.2 Improved Inference Models

Research into numerical methods to improve inference models to address fusion of complex information across multiple levels of uncertainty and probability distribution properties should be addressed. Effort in developing improved mathematically based inference models that fuse highly dynamic, uncertain, incomplete information will be considered. Study of human and other biological systems decision dynamics in experimental settings is an important focus to identify decision processes and to possibly inspire new numerical approaches.

1.2.3 Modeling and Simulation of Complex Networks

Development of fundamental modeling and simulation of complex networks that do not adhere to simplifying assumptions related to linear, ergodic and equilibrium behaviors—conditions present in contemporary environments. Studies and developments that uncover adaptive and self-organizing behaviors to explain and improve operational decision making are important.

Technical Point of Contact: Dr. Purush Iyer, email:, (919) 549-4204

1.3 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. 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 perception, control and learning to facilitate the development of intelligent and autonomous systems. The Intelligence Networks Program aims to be the glue that supports fundamental work in "intelligence," which is utilized in several other programs in Computing Science and Network Science divisions.

1.3.1 Integrated Intelligence

Topics of interest are subcomponents for vision, knowledge representation, reasoning, and planning that can be integrated in a synergistic fashion to yield a sum that is more than its parts.

1.3.2 Robust Reasoning Under Uncertainty

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.

1.3.3 Socio-Cultural Computing

Research on the mathematical tools to model and reason about societies and cultures is needed that brings together tools from Game Theory, Social Sciences and Knowledge Representation.

Technical Point of Contact: Dr. Purush Iyer, email: email:, (919) 549-4204

1.4 Multi-Agent Network Control

The Multi-Agent Network Control Research Program is concerned with developing the theory and tools, through appropriate application and creation of the relevant mathematics, 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. The program invests in fundamental systems and control theory and relevant mathematical foundations for areas of control science with two major thrusts: Intelligent Control and Multi-Agent Systems.

1.4.1 Intelligent Control

The advancements in ubiquitous computation, communications, sensing, biological systems, cognitive sciences, etc., provide a new horizon for control paradigm advancements. Topics of interest in this thrust include multivariate, adaptive, nonlinear, optimal, stochastic, embedded, and hybrid control, learning systems, swarming behaviors, nonconventional game theory, and intelligent decision making. Control theoretic framework, accurate, efficient, demonstrable computational procedures, analytical solutions of intelligent control of time-sensitive applications in severe environments, using noisy sensors are of special interest.

1.4.2 Multi-Agent Systems

he anticipated dynamics of the future battle space will require a greatly increased level of automation to enable the necessary mobility, sensor coverage, information flow, and responsiveness to support the military goals of information superiority, dominant maneuver, and precision engagement. Intelligent collaborative networks of software and physical agents will allow the Army to satisfy this increased tempo within the constraints of reduced manpower and casualties. Topics of interest in this thrust include integrated agent-based decision and control architectures, dynamic resource management, and fault-tolerant operation, especially under network delay, bandwidth communication and computational constraints. This thrust is also interested in establishing mathematical foundations related to distributed system theory; metrics for system complexity, information content, flow, structure, swarming phenomena, design of emergent behavior for heterogeneous multi-agent systems; and information processing and data fusion for decision-making, distributed multi-agent theory with applications to heterogeneous teams of robotic, UAVs, biological entities, and/or software.

Technical Point of Contact: Technical Point of Contact: Dr. Samuel Stanton, e-mail:, (410) 278-7777 or Dr. Randy Zachery, e-mail:, (919) 549-4368


Last Update / Reviewed: March 14, 2016