Tactical Networks Research Articles

Tactical Network Bandwidth Analysis: Application of the Wearables Model‐Based Systems Engineering ‐ System Architecture (MBSE‐SA)

AbstractWarfighters are often exposed to harsh environmental conditions, and experience high rates of physical and cognitive stress, fatigue, and infections, resulting in the degradation of their health and physical performance. This degradation can have a profound effect on the readiness of military forces. Wearable sensor systems can be used to monitor warfighter physiological and cognitive data, providing insight into their health status during routine military training and deployed operations; however, to enable a real‐time, tactical health and performance monitoring capability, wearable sensor systems must integrate into existing tactical military information networks without compromising network function. We extended our existing Wearables Model‐Based System Engineering – System Architecture (MBSE‐SA) to include a bandwidth simulation to analyze the effects wearable sensor systems have on overall network function specifically for military use cases. Our Wearables MBSE‐SA enabled us to model many notional and existing architectures, which represent the wide range of wearable sensor devices, communication protocols, end user devices, and tactical network nodes typically present in operational environments. By taking advantage of the existing Wearables MBSE‐SA framework and architectures, the resulting bandwidth simulation rapidly assessed several existing military network architectures for wearable sensor system integration and identified where network changes were required. Validating the flexibility of the Wearables MBSE‐SA to incorporate new analyses was critical for the military's ability to explore wearable sensor system trades and evaluate architectures in the quickly changing wearable systems technology domain.

Framework for Federated Learning and Edge Deployment of Real-Time Reinforcement Learning Decision Engine on Software Defined Radio

Machine learning promises to empower dynamic resource allocation requirements of Next Generation (NextG) wireless networks including 6G and tactical networks. Recently, we have seen the impact machine learning can make on various aspects of wireless networks. Yet, in most cases, the progress has been limited to simulations and/or relies on large processing units to run the decision engines as opposed to deploying it on the radio at the edge. While relying on simulations for rapid and efficient training of deep reinforcement learning (DRL) may be necessary, it is key to mitigate the sim-real gap while trying to improve the generalization capability. To mitigate these challenges, we developed the Marconi-Rosenblatt Framework for Intelligent Networks (MR-iNet Gym), an open-source architecture designed for accelerating the deployment of novel DRL for NextG wireless networks. To demonstrate its impact, we tackled the problem of distributed frequency and power allocation while emphasizing the generalization capability of DRL decision engine. The end-to-end solution was implemented on the GPU-embedded software-defined radio and validated using over-the-air evaluation. To the best of our knowledge, these were the first instances that established the feasibility of deploying DRL for optimized distributed resource allocation for next-generation of GPU-embedded radios.

IDR: Intent‐driven routing strategy for reliable and cost‐effective multicasting in airborne tactical networks

AbstractTraditional multicast routing strategies can hardly meet the demanding requirements of multicasting mission assignment messages in airborne tactical networks. This letter proposes an intent‐driven routing strategy, termed as IDR, to realize reliable and efficient multicast. IDR exploits bit index explicit replication technique to encode not only the destination information but also the retransmission information into packet headers. If part of the multicast members failed to receive the packet, IDR can perceive the error and retransmit the packet to the precise set of nodes. Compared to the state‐of‐the‐art reliable multicast routing methods, IDR can enhance multicast retransmission success rate by about 10% or more and reduce retransmission overhead by around 50%.

Manifold Structure Analysis of Tactical Network Traffic Matrix Based on Maximum Variance Unfolding Algorithm

As modern weapons and equipment undergo increasing levels of informatization, intelligence, and networking, the topology and traffic characteristics of battlefield data networks built with tactical data links are becoming progressively complex. In this paper, we employ a traffic matrix to model the tactical data link network. We propose a method that utilizes the Maximum Variance Unfolding (MVU) algorithm to conduct nonlinear dimensionality reduction analysis on high-dimensional open network traffic matrix datasets. This approach introduces novel ideas and methods for future applications, including traffic prediction and anomaly analysis in real battlefield network environments.

Mobile wireless ad-hoc network routing protocols comparison for real-time military application

Mobile wireless Ad-hoc has become more popular because it forms quickly, has an easy setup, and has easy extensibility. The mobile ad-hoc wireless networks can be further classified according to their applications as follows: Regular user ad-hoc networks are commercial communication that applies to vehicles to help avoid collisions and accidents and live connections to transfer data from car to car. Another application is disaster rescue ad-hoc networking, usually used when a normal infrastructure network is destroyed by storms, earthquakes, tsunamis, etc. Nowadays, a lot of applications, particularly those related to the military and emergency situations, rely on mobile ad hoc wireless networks, where security needs are more challenging to provide than in regular networks. We present the tactical network needs for the military. This platform attempts to assess the possible advantages of mobile ad hoc networks in tactical military applications. This work proposes route discovery using reactive (on-demand) routing protocols where nodes need to just transfer data. This eliminates the requirement for each node to store and maintain any routing tables. This study presents and contrasts the benefits and drawbacks of two fundamental mobile ad hoc routing systems (AODV and DSR). Both protocols are On-Demand routing techniques, and when data needs to be sent, the discovery phase begins. The results of the simulation, the AODV routing approach outperforms the DSV routing method under identical simulated conditions.

A wormhole attack detection method for tactical wireless sensor networks.

Wireless sensor networks (WSNs) are networks formed by organizing and combining tens of thousands of sensor nodes freely through wireless communication technology. WSNs are commonly affected by various attacks, such as identity theft, black holes, wormholes, protocol spoofing, etc. As one of the more severe threats, wormholes create passive attacks that are hard to detect and eliminate. Since WSN is often used in the tactical network field, a planned secure network is essential for military applications with high security. Guard nodes are traffic monitoring nodes used to supervise neighbors' data communication around the tactical networks. Therefore, this work proposes a Quality of Service (QoS) security mechanism to select multiple dual-layer guard nodes at different paths of the WSN based on the path qualities to detect wormholes. The entire network's links are categorized into high, normal, and low priority levels. As such, this study aimed to confirm the security of high priority nodes and links in the tactical network, avoid excessive overhead, and provide random security facilities to all nodes. The proposed measures of the QoS-based security provision, including link cluster formation, guard node selection, authenticated guard node identification, and intrusion detection, ensure economic and efficient network communication with different quality levels.

Avoiding Detection by Hostile Nodes in Airborne Tactical Networks

Contemporary airborne radio networks are usually implemented using omnidirectional antennas. Unfortunately, such networks suffer from disadvantages such as easy detection by hostile aircraft and potential information leakage. In this paper, we present a novel mobile ad hoc network (MANET) routing protocol based on directional antennas and situation awareness data that utilizes adaptive multihop routing to avoid sending information in directions where hostile nodes are present. Our protocol is implemented in the OMNEST simulator and evaluated using two realistic flight scenarios involving 8 and 24 aircraft, respectively. The results show that our protocol has significantly fewer leaked packets than comparative protocols, but at a slightly higher cost in terms of longer packet lifetime.

An Efficient Bio-inspired Routing Scheme for Tactical Ad hoc Networks

Ad hoc networks are temporary networks, created mainly for applications that are infrastructure-less. Such networks and network nodes demand special characteristics like mobile nodes having dynamic topology, wireless medium, heterogeneous deployment environment, and reactive or proactive routing depending on the nature of the network which includes network parameters such as node placement, mobility model, number of participants in the network, patterns of mobility, etc. Due to these characteristics and the mobility of network nodes, the process of routing is quite challenging in the ad hoc environment, especially when the node mobility is high. Bio-inspired routing can be an effective solution to meet all the design requirements and deal with the issues of tactical ad hoc networks. Different types of nature-inspired routing mechanisms are possible to use for tactical networks. This paper proposes the design of a novel Ant Colony Optimization-based routing strategy for ad hoc networks. Ant-based algorithms are dynamic and have adaptive behavior. Hence, they are competent for routing in ad hoc networks. Our proposed routing scheme is evaluated based on the network’s performance by varying different parameters. The performance of our proposed ACO-based routing approach is also compared to some existing ad hoc routing mechanisms. Different metrics in different deployment scenarios that can affect the efficiency of our proposed protocol are taken into consideration to evaluate the performance.

동적 전술 네트워크 환경에서 자율 무인체계를 위한 상호인증 기법

미래 전장환경의 주요 구성요소인 자율 무인체계들은 군집화되어 팀 단위로 활동하고 작전 목적 및 작전 상황에 따라 팀 구성은 매우 유동적일 것이다. 즉, 독립된 작전에 투입되어 운영되던 무인체계 팀들이 하나의 팀으로 통합되거나 하나의 무인체계 팀이 두 개 이상의 팀으로 분할될 수 있다. 새로운 팀으로 재편될 때마다 안전한 인증절차가 필요하다. 무인체계는 인간 전투원과 달리 종합적인 상황판단을 통한 인증이 제한되기 때문에 적 무인체계에 의한 기만적 활동에 취약할 수 있다. 본 논문은 미래 전장에서 안전한 무인체계 활용을 위한 경량화된 인증 기법을 제안한다. 제안하는 기법에서 무인체계는 개별 고유식별번호와 CRT(Chinese Remainder Theorem)를 통해 같은 팀에 소속된 무인체계들은 동일한 정수를 추출하고, 추출한 정수만큼 해시 연산을 반복하여 암호키를 개별적으로 생성한다. 그리고 수신된 암호화 메시지를 복호화함으로써 수신 메시지가 아군으로부터 수신된 것임을 인증한다. 제안하는 기법의 성능분석을 통해 제안하는 기법이 메시지 재전송 공격, 위장 공격, 메시지 변형 공격 등에 안전하고 기존 유사 기법에 비해 적은 연산량이 요구됨을 확인하였다.

LoRaWAN & The Helium Blockchain: A Study on Military IoT Deployment

Technology is evolving at a rapid pace, and the demand for a reliable, far-reaching Internet of Things (IoT) network has never been higher. Low Power Wide Area Network (LPWAN) offers an energy-efficient, low-cost, long-range wireless communication protocol catered to IoT devices. A subset of LPWAN, Long Range Wireless Access Network (LoRaWAN), is being rapidly adopted due to its effortless integration into existing system architectures and real-world success. The Helium Network cryptocurrency blockchain’s financial incentives have been used to speed up the LoRaWAN adoption and deployment in urban and rural areas by financially incentivizing gateway owners to establish a redundant network based out of their homes and businesses. In addition to ease of deployment, the Helium Network allows for enhanced security by utilizing a public blockchain ledger to verify the identities of both sender and recipient to combat packet replay and man-in-the-middle attacks. This research argues for the effectiveness of LoRaWAN and Helium Network technology fusion based on real-world examples of a robust and dependable worldwide network. Further, this research advocates for adoption and modification of this technology by the Department of Defense (DoD), to enhance environmental sensing, establish real-time tactical networks, and critical infrastructure and logistics monitoring. If the DoD chooses to integrate these two technologies with its existing IoT infrastructure; it can reliably, securely, and anonymously use LoRaWAN nodes and routers as both a long-range and backup encrypted communication network capable of supporting end-to-end encryption up to AES-128 (DoD SECRET-classification standard). The DoD could capitalize on these successes to advance information dominance in both domestic and international environments. The demonstrated performance and low adoption cost of LoRaWAN and Helium Network technologies could greatly enhance the DoD’s mission of maintaining its lethality and dominance in information warfare.

Deep Reinforcement Learning in Competing Cognitive Tactical Networks

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Blind Vector Parameter Estimation for Burst Type CPM Transmissions

Short burst continuous phase modulation transmission is of practical relevance in e.g. frequency hopping systems applied in sensor or tactical networks. The channel conditions can be seen as mutually uncorrelated for each burst due to spectral and or temporal separation of those. Because of this time variant nature, a recurring acquisition of the impairment parameters is required for each burst. In this work, a blind joint estimation of several parameters in a flat fading environment for continuous phase modulation bursts is realized by the expectation maximization algorithm. The main contributions are first the formulation of the expectation and maximization steps to enable the joint computation of the maximum likelihood parameter estimates and second the analysis of the likelihood functions to obtain an optimized initialization for the algorithm. It is shown, that the joint estimator produces unbiased estimates and its performance in terms of the mean squared estimation error achieves the theoretical limits, i.e. the modified Cramér-Rao-Vector-Bound and slightly outperforms a state of the art pilot based estimator. Furthermore, the effective throughput is discussed and bit and frame error rates are compared to each other and to the perfectly synchronized estimator. Its computational complexity is analyzed and efficient computation steps and further approaches are outlined to decrease it.

A Game Theoretic Framework for Distributed Mission Slice Allocation and Management for Tactical Networks

A Game Theoretic Framework for Distributed Mission Slice Allocation and Management for Tactical Networks

Interoperable, adaptable, information exchange in NATO coalition operations

Abstract This paper summarises our work on policy-enabled inter-network routing for mobile networks and adapting information services to available networking resources in tactical networks. The work shows promise; both the policy routing and adaptive service infrastructure were part of successful interoperability trials in the Coalition Warrior Interoperability eXercise (CWIX) in 2021. This paper highlights our findings, how our work can support interoperability in NATO, and represents an enabler for future coalition operations. Although promising, the work involves research and concept development, and so, we anticipate its timeframe for seeing actual operational use as likely 3–5 years from now, typically targeting future developments within Federated Mission Networking (FMN). In our work, we have shown that we can build a federated mobile network by using a reactive routing protocol that supports policy routing in a network overlay for use in a coalition. Further, we have shown that we can leverage network-level information at the application level, through a so-called cross-layer optimization (CLO) approach. The CLO approach leverages a well-defined format, and we found that this format promotes interoperability and can be used in a multi-national setting. Since our work is experimental, we have also identified some shortcomings for future work.

Dynamic Reliability-Aware Virtual Network Embedding for Airborne Tactical Networks

Airborne tactical networks (ATNs) built on network virtualization (NV) can enable efficient information sharing for network-centric warfare by breaking the tight coupling between applications and network infrastructure and thus solving the network ossification problem. With dynamic changes during military missions, the application of virtualization is challenged by the changing demands on network resources when instantiating multiple virtual networks (VNs) on a shared substrate network (SN), known as virtual network embedding (VNE). However, existing dynamic VNE algorithms, mostly designed for wired networks, focus on the dynamic changes of single VN and do not consider the dynamic changes of different VNs. The proper processing of changes of different VNs is beneficial to improve the embedding profits of VNs. On these backgrounds, we investigate the dynamic wireless VNE that processes the dynamic changes of different VNs in the wireless environment of ATNs. A relationship matrix-based dynamic wireless VNE (DWVNE-RM) algorithm is proposed in order to maximize the acceptance ratio of VN requests. The dynamic changes of different VNs are classified into negative changes (requiring resource) and positive changes (releasing resource). Then, the relationship matrix between negative and positive changes is constructed to properly process the resource relationship among different changes in order to improve the acceptance ratio. In addition, the complex interference of ATNs is considered in the mapping or remapping of virtual nodes and links to improve the reliability. Through extensive simulation, DWVNE-RM is compared with multiple existing dynamic algorithms and outperforms over others.

GOR: Group-oblivious multicast routing in airborne tactical networks under uncertainty

Disseminating mission assignment messages always requires effective and flexible multicast routing scheme design in airborne tactical networks, in particular, when the multicast group members are under uncertainty. Traditional IP multicast routing strategies have little regard for the uncertainty of multicasting in airborne tactical networks, wherein the multicast groups are highly unpredictable and are changing over different sessions. In this work, we present a group-oblivious multicast routing strategy, termed as GOR, to hedge against the uncertainty of multicasting in airborne tactical networks. GOR exploits Bit Index Explicit Replication (BIER) technique for the sake of stateless multicast. In order to minimize multicast delay, GOR re-formulates the hierarchical deployment of BIER into a modified group Steiner tree problem for a better routing. Both analytical and experimental results demonstrate that the presented GOR can provide reasonably better multicast performance across all possible sets of group members.

A network business availability modeling method based on Markov chain

Military tactical networks (MTNs) have grown in size and complexity as the volume of battlefield communications business has increased dramatically. There is a critical need for a quantitative evaluation method to assess the performance of MTNs. Based on the transmission characters of battlefield communication business and the availability of communication equipment, this paper proposed a Markov chain-based network steady-state availability model. Using this model and the analysis of the CSMA/CA transmission protocol as preconditions, a delay-based quantitative evaluation model of network business availability is proposed based on statistical principles. The relationship between network business availability and crucial metrics such as node size and node failure/repair ratio is investigated in simulation experiments to ensure the validity and correctness of the proposed model. The work done in this paper contributes to effectively evaluating the overall availability of MTNs in a complex environment.

A Study on Improvement of the Military IdAM Using Edge-Sovereign Identity (ESI)

A framework-level IdAM integration approach requires a stable network infrastructure. Information framework’s operation may be significantly restricted when the network is disconnected from the remote IdAM service. Moreover, military networks, especially tactical networks, are volatile, and network disconnection is also high. In this paper, we proposed an Edge-Sovereign Identity (ESI) that expanded the concept of SSI for use in the military field, designed the structure and function of the proposed concept, and demonstrated its usefulness and validity through examples and prototypes.

IoT and Edge Computing as Enabling Technologies of Human Factors Monitoring in CBRN Environment

Human Factor (HF) monitoring under the critical CBRN environment reduces the likelihood of errors or injuries by first responders who carry out operations within an unknown workspace. Indeed, thanks to the monitoring, analysis and assessment of physical and mental workload and manual handling of equipements by first responders, it is possible to increase safety, efficiency and effectiveness. The IoT and Edge computing, contextualizing the collected data, promises to enhance the CBRN situational awareness by working on the HFs aspects with a view to context-aware reasoning. IoT and edge computing enabling technologies envisage operators needs and behaviours by gathering information about biophysiological conditions, emotional state and operational data by first responders.This study aims to introduce the edge computer for data fusion in tactical networks and computational services, fully integrated in IoT solutions of remote monitoring of HFs. These latter, related to Human Performance and health of responders, may prove useful as innovative tools in CBRN incident management.

Situation-Aware Survivable Network Design for Tactical Environments

A tactical sensor network is a representative safety-critical environment that should satisfy strict guarantee of the requirements of tactical traffic. However, because of the lack of infrastructure in a military network environment, resource constraints on wireless channel and nodes can cause problems such as network congestion and packet collision. If critical tactical data is lost or does not arrive on time, it can degrade the efficiency of military operations and even threaten the survival of soldiers. To resolve this critical issue, we propose a situational backoff reset algorithm that utilizes a quality of service (QoS) field information to determine the priority of received tactical packets and control the deferral time of low-priority traffic. From a packet routing path connectivity perspective, we propose a branch node-based routing algorithm in order to provide a resilient path by excluding the isolated single path. Our simulation results demonstrate that the proposed solution can prioritize tactical traffic from the channel preemption perspective and construct a robust end-to-end path avoiding an isolated single path.