Anurag Ganguli

Mobility Aware Routing for the Airborne Network backbone

The airborne network (AN) will form an essential part of the global information grid in the future, thus providing information and decision superiority to US armed forces. AN is an enabling technology for network centric warfare. AN is different from the terrestrial mobile ad-hoc networks (MANETs) and the wire-line internet, both in terms of network capability and underlying assumptions. The backbone nodes of the AN are envisioned to fly in pre-planned orbits whose knowledge can be exploited for efficient routing. In this paper we propose a dynamic adaptive routing protocol that uses known trajectories of the AN nodes to enhance performance. Our routing protocol has two components: (1) a Mobility Aware Routing Protocol (MARP), that routes traffic based on the knowledge of network topology with respect to time and makes preemptive decisions to minimize packet losses due to link failure and discover better routes, and (2) a Mobility Dissemination protocol (MDP) that informs all network nodes of any deviation from the preplanned behavior. We analyze MARP/MDP protocol suite using the QualNet network simulator for representative AN deployment scenarios and compare performance with proactive and reactive MANET routing protocols. We use packet delivery ratio, end-to-end latency and control overhead as performance metrics. We also analyze the performance of the MARP/MDP routing protocol for varying degrees of prediction accuracy. This work is part of an ongoing Phase II Small Business Innovation Research program administered by the Air Force Research Laboratory/Information Directorate in Rome, New York.

Geo-based inter-domain routing (GIDR) protocol for MANETs

Inter-domain routing for MANETs (Mobile Ad Hoc Networks) draws increasing attention because of military and vehicular applications. The existing Border Gateway Protocol (BGP) is the de facto inter-domain routing protocol for the Internet. But BGP is not applicable to MANETs because the BGP design is based on a static Internet which does not support dynamic discovery of members, and cannot scale to mobile, dynamic topology environments.

Towards a mission planning toolbox for the Airborne Network: Optimizing ground coverage under connectivity constraints

The airborne network (AN) is a constellation of networked aircrafts flying in periodic orbits. AN is an enabling technology for network centric warfare for the military, autonomous air traffic control for commercial aviation and for providing Internet access over a broad urban area. AN is a highly dynamic environment and presents challenges that have not been addressed in traditional wire-line or wireless MANET research. Wireless links in AN are quasi-persistent and break due to platform banking and antenna shadowing. In this paper, the objective is to deploy airborne nodes so that they provide ground nodes with high data upload capacity while making sure that a minimal topology within the backbone airborne network is always maintained. For the sake of simplicity of presentation we make a few assumptions on the trajectories of the airborne nodes. We verify our assumptions against a well studied airborne network deployment scenario. Using tools from convex optimization we determine optimal locations of airborne nodes for three different scenarios. We present our results graphically and illustrate them using examples.

Topology control for future Airborne Networks

Active topology management in the future Airborne Networks (AN) can provide improved overall network throughput, efficiency, and scalability and is critical due to the high degree of platform dynamics involved. The RF links that form an airborne network must be established and reconfigured rapidly in response to aircraft joining and leaving the network, aircraft changing flight paths, and to changes in mission information flows, among other things. Additional technical challenges stem from the fact that the airborne nodes will use multiple directional and omni-directional antennas with differing antenna patterns. In this paper we present a Mobility Aware Topology Control (MAToC) solution for the Airborne Network. MAToC is comprised of deliberative and reactive topology planning components. MAToC utilizes a distributed protocol for airborne nodes for ad-hoc exchange of respective flight plan. Deliberative mode planning uses the collected flight plan information to assign optimal power, channel and boresight direction to the airborne antennas. Deliberative MAToC uses graph coloring algorithms for channel and timeslot assignment and uses geometric optimization methodology to assign antenna powers to maximize Signal to Interference and Noise Ratio (SINR). In the reactive mode, MAToC is responsible for link monitoring and link repair for fault-tolerance.

Hierarchical multiple sensor fusion using structurally learned Bayesian network

Multiple sensor fusion is very important for wireless health monitoring since a single type of sensor usually can only provide limited aspects of the health condition while multiple sensors of different types hopefully can complement each other and yield more comprehensive aspects of the health condition. Many existing sensor fusion approaches are based on a flat structure, where multiple sensor features are treated as in the same layer and are fused by the feature-level fusion. In this paper we present a systematic approach using a structurally learned Bayesian Network (BN) for sensor fusion. The BN serves as a powerful framework that can integrate multiple sensor features in a hierarchy that is automatically learned via supervised learning. We present a hybrid structure learning approach that includes four steps and consists of both systematic global and local structure learning, as well as random perturbation for structure learning. Subsequent to the feature selection, we first learn an Augmented Bayesian Classifier (ABC) and it is followed by an extended K2 structure learning to search for a better structure in another structure subspace. Random structure learning is then performed to perturb the structure learning so as to avoid getting stuck in a local optimum. Finally, we perform local structure learning with hill-climbing by reversing or removing each link between features. The proposed hierarchical sensor fusion solution outperformed some conventional approaches such as Naïve Bayesian Classifier and Support Vector Machine classifier that integrate multiple sensor features by a flat feature-level fusion.

On the Limits of Collision Detection Performance of a Sense- and-Avoid System for Non-Cooperative Air Traffic

Unmanned Aircraft Systems (UAS) face limitations on their utilization in civil airspace because they do not have the ability to Sense and Avoid (SAA) other air traffic. In recent years, there has been growing interest to provide an effective SAA solution for UAS operations. An effective SAA solution must address both cooperative as well as non-cooperative air traffic. A number of different sensor solutions are being evaluated for SAA pertaining to non-cooperative traffic. Examples of such sensors include electro-optical (EO), on-board radar, passive acoustics, laser radar and ground radar. Using one or more such sensing modalities, it is possible to track a non-cooperative aircraft in the vicinity of the own aircraft otherwise known as an intruder. However, an intruder’s future trajectory is never perfectly known and a SAA system’s performance will always be limited by these uncertainties. One of the components of an SAA system is the logic to decide whether a certain aircraft is on a collision course with the own craft. It, therefore, follows that the performance of this collision detection component will also be limited by the uncertainties in the future trajectory of the intruder. In this paper, we investigate the problem of what is the best that a SAA collision detection system can perform in spite of the future uncertainties in the intruder trajectory.

Feasibility of communication planning in Airborne Networks using mission information

The Department of Defense (DoD) is making strides toward Network Centric Warfare. In modern warfare, information superiority and situational awareness is vital to superiority on the battlefield. That is, whoever can pass relevant information between war fighters in a more timely and efficient manner is more likely to succeed. Therefore, the concept of communication planning for DoD missions should become as critical as mission planning itself. Over the years there has been significant research in many areas of mission planning, and most DoD missions are executed in a planned manner. The authors of this paper have in the past independently argued that the availability of mission plans can greatly improve communication planning. For this paper, we team up and closely examine how mission plans can be made available for efficient communication planning from a logistics point of view. In particular, we use the domain of the military Airborne Network (AN) as an example. We consider various degrees of mission information available in different AN missions and present case studies using simulation on the kind of communication planning possible with the given information.

Performance characterization of ad hoc routing protocols with mobility awareness

In modern warfare, informational and situational awareness is vital to superiority on the battle field. In our previous work, we have shown that communication planning based on mission plans can greatly improve the performance of the tactical communication networks. In the Mobility Aware Routing Protocol (MARP) /Mobility Dissemination Protocol (MDP), this mission information is utilized to route traffic based on the knowledge of the Airborne Network topology with respect to time and make preemptive decisions to minimize packet losses due to link failures. However, it is always difficult for the wide body aircrafts to follow the prescribed trajectories accurately, leading to imperfections in the predicted topologies. In this paper, we extend the idea of mobility aware routing for situations where the mission information is inaccurate. We simulate different scenarios to introduce these imperfections and through stress tests and simulation studies, we have compared the performance of MARP/MDP with other standard Proactive Ad Hoc routing protocol like OLSR. Based on the scenarios of study, we have empirically observed that MARP/MDP always performs better than OLSR. In this paper, we also discuss and report performance parameters collected from an emulated Linux based testbed. We developed MARP/MDP routers using Zebra/Quagga routing protocol suite and used a real time Network Emulator to set up the experiments.

Delay tolerant Mobility Aware Routing/Mobility Dissemination Protocol for the airborne network

Despite “airborne network (AN) topology design” and careful planning of AN trajectories, unexpected disruptions (from hardware failures to changes in mission requirements and hostile attacks) may cause nodes not to connect to one another directly or indirectly either because they are out of one anothers range or because nodes do not meet one another according to their preplanned trajectories. Since an end-to-end path within the AN is not always guaranteed, packets have to be delivered in a delay-tolerant fashion, namely, some intermediate nodes will need to buffer packets during times of disconnectivity. In our earlier work we developed Mobility Aware Routing Protocol and Mobility Dissemination Protocol (MARP/MDP) that used preplanned trajectories of airborne nodes to make intelligent routing decisions preemptively. In this paper we present a delay-tolerant strategy (MARP/MDP+DTN) to predict the minimum end-to-end delay and obtain the corresponding path. In addition, MARP/MDP+DTN accounts for local queueing (MARP/MDP+DTN+QC) to minimize congestion and further improves end-to-end delay with the positive side effect of load-balancing. Simulation results have shown an improvement of 52% in packet delivery ratio in MARP/MDP+DTN. MARP/MDP+DTN+QC also exhibits extremely short latency, about 90% reduction from MARP/MDP+DTN in highly congested network. Moreover, MARP+DTN+QC balances local traffic 67% better than MARP+DTN in high traffic load scenarios.

Multiple intruder tracking using a laser enhanced EO/IR Sense and Avoid system

Remotely Piloted Aircraft (RPA), otherwise known as Unmanned Aircraft Systems (UAS), need access to the National Airspace (NAS). For this to happen, a robust and reliable Sense and Avoid (SAA) technology that can simultaneously detect and track cooperative as well as non-cooperative intruders encountered in the NAS is required. To detect non-cooperative intruders, passive electro-optical (EO) and infra-red (IR) sensors are attractive from the size, weight and power (SWAP) considerations. As such they can be used even on small UAS. However, EO/IR sensors do not provide reliable range measurements. Another drawback of current EO/IR technology for detection of other air traffic is the unacceptable rate of false alarms generated due to clutter in images and small specks of clouds. The performance of the EO/IR sensors can be enhanced through the addition of laser ranging technology. A laser system can be cued by the EO/IR sensors to point towards the bearing of a suspected intruder. The laser returns can then be used to confirm the presence of the intruder and provide range information as well. In scenarios involving multiple intruders, gimbals/scanners may be employed to slew the laser from one intruder to another. This can take time and potentially limit the number of intruders that can be tracked. Intelligent sensor management and tracking algorithms can alleviate these problems to a good degree. In this paper, we address the problem of multiple-intruder tracking using a gimbaled laser system in conjunction with a passive EO/IR system. The main focus of the paper is on designing intelligent, effective and computationally efficient gimbal tasking algorithms. For realistic evaluation of system performance, we design and develop a software model of a generic EO-plus-laser system. We evaluate the performance of the system using Monte Carlo simulations based on encounters generated using the MIT Lincoln Laboratory encounter model of the National Airspace.