Mission-critical Networks Research Articles

An One-Time Pad Cryptographic Algorithm with Huffman Source Coding Based Energy Aware Sensor Node Design

Recently, the security-based algorithms for energy-constrained sensor nodes are being developed to consume less energy for computation as well as communication. For the mission critical wireless sensor network (WSN) applications, continuous and secure data collection from WSN nodes is an essential task on the deployed field. Therefore, in this manuscript, One-Time Pad Cryptographic Algorithm with Huffman Source Coding Based Energy Aware sensor node Design is proposed (EA-SND-OTPCA-HSC). Before transmission, the distance among transmitter and receiver is rated available in mission critical WSN for lessen communication energy consume of sensor node. For the mission critical WSN applications, continuous and secure data collection from WSN nodes is an essential task on the deployed field. The periodic sleep/wake up scheme with Huffman source coding algorithm is used to save energy at the node level. Then, one-time pad cryptographic algorithm in each sensor node, the vernam cipher encryption technique is applied to the compact payload. The proposed technique is executed and efficacy of proposed method is assessed using Payload Vs Energy consume for one sensor node, communication energy consume for one sensor node with different distances, energy consume for one sensor node under various methods, Throughput, delay and Jitter are analyzed. Then the proposed method provides 90.12%, 89.78% and 91.78% lower delay and 88.25%, 95.34% and 94.12% lesser energy consumption comparing to the existing EA-SND-Hyb-MG-CUF, EA-SND-PVEH and EA-SND-PIA techniques respectively.

Emerging Trends in UAVs: From Placement, Semantic Communications to Generative AI for Mission-Critical Networks

Emerging Trends in UAVs: From Placement, Semantic Communications to Generative AI for Mission-Critical Networks

Tuneman: Customizing Networks to Guarantee Application Bandwidth and Latency

We examine how to provide applications with dedicated bandwidth and guaranteed latency in a programmable mission-critical network. Unlike other SDN approaches such as B4 or SWAN, our system Tuneman optimizes both routes and packet schedules at each node to provide flows with sub-second bandwidth changes. Tuneman uses node-level optimization to compute node schedules in a slotted switch and does dynamic routing using a search procedure with Quality of Service– (QoS) based weights. This allows Tuneman to provide an efficient solution for mission-critical networks that have stringent QoS requirements. We evaluate Tuneman on a telesurgery network using a switch prototype built using FPGAs and also via simulations on India’s Tata Network. For mission-critical networks with multiple QoS levels, Tuneman has comparable or better utilization than SWAN while providing delay bounds guarantees.

Contextual information aware optimal communication in radio networks in considering the pervasive computing -A literature review

The modern tactical network demands a highly dynamic communications environment that involves autonomous platforms and systems. In order to achieve the full potential of modern technologies, it is critical to ensure the critical data finds the optimum path at the right time in a highly aggressive environment employing secure and best possible available communication path or network resources. Moreover, Contextual information aware optimal communication, such as the power of the radios, battery level, distance among the radios, and maximum and minimum data rates of the radio aware optimal path selection, remains an unresolvable research area. The mentioned limitation engenders various complex challenges in mission-critical networks. Therefore, contextual information-aware optimal communication in radio networks is a priority demand raised as a primary objective for military communication research. In this paper, we have performed a comprehensive review of various proposed methodologies to achieve the objective, followed by a critical comparative analysis to anticipate the state of the mentioned research area that leads to a future research direction for military researchers.

Enabling Next-Generation Public Safety Operations with Mission-Critical Networks and Wearable Applications

Public safety agencies have been working on the modernization of their communication networks and the enhancement of their mission-critical capabilities with novel technologies and applications. As part of these efforts, migrating from traditional land mobile radio (LMR) systems toward cellular-enabled, next-generation, mission-critical networks is at the top of these agencies’ agendas. In this paper, we provide an overview of cellular technologies ratified by the 3rd Generation Partnership Project (3GPP) to enable next-generation public safety networks. On top of using wireless communication technologies, emergency first responders need to be equipped with advanced devices to develop situational awareness. Therefore, we introduce the concept of the Internet of Life-Saving Things (IoLST) and focus on the role of wearable devices—more precisely, cellular-enabled wearables, in creating new solutions for enhanced public safety operations. Finally, we conduct a performance evaluation of wearable-based, mission-critical applications. So far, most of the mission-critical service evaluations target latency performance without taking into account reliability requirements. In our evaluation, we examine the impact of device- and application-related parameters on the latency and the reliability performance. We also identify major future considerations for better support of the studied requirements in next-generation public safety networks.

A Novel Self-Forming Virtual Sub-Nets Based Cross-Layer MAC Protocol for Multihop Tactical Network

A tactical network mainly consists of software-defined radios (SDRs) integrated with programmable and reconfigurable features that provide the addition and customization of different waveforms for different scenarios, e.g., situational awareness, video, or voice transmission. The network, which is mission-critical, congested, and delay-sensitive, operates in infrastructure-less terrains with self-forming and self-healing capabilities. It demands reliability and the need to survive by seamlessly maintaining continuous network connectivity during mobility and link failures. SDR platforms transfer large amounts of data that must be processed with low latency transmissions. The state-of-the-art solutions lack the capability to provide high data throughput and incorporate overhead in route discovery and resource distribution that is not appropriate for resource-constrained mission-critical networks. A cross-layer design exploits existing resources to react to environment changes efficiently, enable reliability, and escalate network throughput. A solution that integrates SDR benefits and cross-layer optimization can perform all the mentioned operations efficiently. In tactical networks, SDR’s maximum usable bandwidth can be utilized by exploiting radios’ autonomous behavior. This paper presents a novel virtual sub-nets based cross-layer medium access control (VSCL-MAC) protocol for self-forming multihop tactical radio networks. It is a MAC-centric design with cross-layer optimization that enables dynamic routing and autonomous time-slot scheduling in a multichannel network environment among SDRs. The cross-layer coupling uses link-layer information from the hybrid of time division multiple access and frequency division multiple access (TDMA/FDMA) MAC to proactively enable distributed intelligent routing at the network layer. The virtual sub-nets based distributed algorithm exploits spectrum resources and provides call setup with persistently available k-hop route information and simultaneous collision-free transmission of voice and data. The experimental results over extensive simulations show significant performance improvements in terms of minimum control overhead, processing time in relay nodes, a substantial increase in network throughput, and lower data latency (up to 76.98%) compared to conventional time-slotted MAC protocols. The design is useful for mission-critical, time-sensitive networks and exploits multihop simultaneous communication in a distributed manner.

Service-Based Resilience via Shared Protection in Mission-Critical Embedded Networks

Mission-critical networks, which for example can be found in autonomous cars and avionics, are complex systems with a multitude of interconnected embedded nodes and various service demands. Their resilience against failures and attacks is a crucial property and has to be already considered in their design phase. In this paper, we introduce a novel approach for optimal joint service allocation and routing, leveraging virtualized embedded devices and shared backup capacity for the fault-tolerant design of mission-critical networks. This approach operates in phases utilizing multiple optimization models. Furthermore, we propose a new heuristic that ensures resource efficiency and fault-tolerance against single node and link failures as pre-requisite for resilience. Our experiments for different application scenarios indicate that our heuristic achieves results close to the optimum and provides 50% of capacity gain compared to a dedicated capacity protection scheme. Moreover, our heuristic ensures fault-tolerance against at least 90% of all potential single node failures.

IEEE Access Special Section Editorial: Mission-Critical Sensors and Sensor Networks (MC-SSN)

Mission-critical sensors and sensor networks (MC-SSN) have been applied to missions such as battlefield, border patrol, search and rescue, critical structure monitoring, and surveillance. To support critical missions, sensors and sensor networks need to be flexible and interactive and continuously work despite limited bandwidth, intermittent connectivity, and with a large number of devices on the network. Sometimes, humans will be the elements within mission-critical sensors and sensor networks that are most vulnerable to deception, and humans will be handicapped when they are concerned about the received information from the network is not trustworthy, even if their concern is misplaced. In MCSSN, the advantages of linking multiple electronic support measures and electronic attack assets to achieve improved capabilities across a networked mission-critical force have yet to be quantified. Algorithms are sought for fused and/or coherent cross-platform radio frequency (RF) sensing. The MC-SSN algorithms should be capable of utilizing RF returns from multiple aspects in time-coordinated sensors and sensor networks. Such adaptation, management, and reorganization of information sources, devices, and networks must be accomplished almost autonomously in order to avoid imposing additional burdens on the humans, and without much reliance on support and maintenance services. Moreover, humans, under extreme cognitive and physical stress, will be strongly challenged by the massive complexity of the MC-SSN and the information it will provide and carry. Advances in technologies that capitalize on the benefits of the MC-SSN have to assist humans in making effective use of this massive, complex, confusing, and potentially deceptive ocean of information while taking into account the ever-changing mission. New approaches and low-complexity algorithms are expected to enable MC-SSN to automatically manage and effect risk and uncertainty in a highly deceptive, mixed cooperative/adversarial, information-centric environment.

MILP, Pseudo-Boolean, and OMT Solvers for Optimal Fault-Tolerant Placements of Relay Nodes in Mission Critical Wireless Networks*

In critical infrastructures like airports, much care has to be devoted in protecting radio communication networks from external electromagnetic interference. Protection of such mission-critical radio communication networks is usually tackled by exploiting radiogoniometers: at least three suitably deployed radiogoniometers, and a gateway gathering information from them, permit to monitor and localise sources of electromagnetic emissions that are not supposed to be present in the monitored area. Typically, radiogoniometers are connected to the gateway through relay nodes. As a result, some degree of fault-tolerance for the network of relay nodes is essential in order to offer a reliable monitoring. On the other hand, deployment of relay nodes is typically quite expensive. As a result, we have two conflicting requirements: minimise costs while guaranteeing a given fault-tolerance. In this paper, we address the problem of computing a deployment for relay nodes that minimises the overall cost while at the same time guaranteeing proper working of the network even when some of the relay nodes (up to a given maximum number) become faulty (fault-tolerance). We show that, by means of a computation-intensive pre-processing on a HPC infrastructure, the above optimisation problem can be encoded as a 0/1 Linear Program, becoming suitable to be approached with standard Artificial Intelligence reasoners like MILP, PB-SAT, and SMT/OMT solvers. Our problem formulation enables us to present experimental results comparing the performance of these three solving technologies on a real case study of a relay node network deployment in areas of the Leonardo da Vinci Airport in Rome, Italy.

Special Issue on Recent Trends in Artificial Intelligence Techniques for Fault-Tolerance, Reliability and Availability in Mission-Critical Networks

Special Issue on Recent Trends in Artificial Intelligence Techniques for Fault-Tolerance, Reliability and Availability in Mission-Critical Networks

A New Approach to Optimizing Network Bandwith and Transfer Rate on Mission Critical Computer Networks: “Network Quality and Resource Manager”

In this paper, a new approach and solution of the one of the biggest problem on mission critical networks, network and bandwidth optimization will be described.
 The developed “Network Quality and Resource Manager” ensures the quality of network bandwidth and transfer rate on isolated mission critical networks like high resolution IP based security camera surveillance systems.
 The “Network Quality and Resource Manager” uses “Quality of Service”, and “Address Resolution Protocol Table” via Simple Network Management Protocol (a.k.a. SNMP) over manage-able at-least 2nd layer network devices. Hence NQRM uses SNMP, it is vendor independent and can work with any network architecture.

Analysis of Interference Between LTE System and TETRA System in The 800 MHz Band

Wireless communication is used in many sectors to support the need of communication, the example of wireless communication is applied in mission critical network. Wireless communication system that used in mission critical are Terrestrial Trunked Radio (TETRA) and Long Term Evolution (LTE). TETRA systems supports voice services while LTE supports voice and data services. Co-exsitence between LTE and TETRA in same frequency band is one of the optimilazition quality for mission critical network. For this final project analyses interference in co-exsitence between LTE and TETRA in frequency band 800 MHz. There are four scenarios using extended-hata model propagation in urban area. There are several parameters that reviewed, desired Received Signal Strength (dRSS), interfering Received Signal Strength (iRSS), Carrier to Interference ratio (C/I) and probability of interference. In all scenarios occur Co-Channel Interference (CCI) between LTE and TETRA in frequency band 800 MHz so the performance not optimal. The performance increased when add guard band variation. The variation that applied are 0,5 MHz, 0,75 MHz, 1 MHz. Based on the result of the simulation that have been done, proposed the used of guard band variation for elevate the performance.

Self-Forming Multiple Sub-Nets Based Protocol for Tactical Networks Consisting of SDRs

The paper presents a novel approach for tactical networks in which radios form self-regulatory virtual sub-nets on the basis of control messages. The design uses hybrid of frequency division multiple access (FDMA) and time division multiple access (TDMA) approaches with less call setup delays and increases in network throughput. This multiple sub-nets based distributed algorithm exploits available spectrum resources, provides collision-free simultaneous transmissions and autonomous selection of time slots over different frequency sub-bands with self-organizing and self-forming network capabilities. We propose two schemes which provide multi-channel medium access control with autonomous scheduling of time slots for software-defined radios (SDRs). The schemes use request and acknowledgment frames as control messages to devise a distributed solution. These control messages alone help to form virtual sub-nets, preserve frequency channels and schedule transmissions over multiple time slot intervals, depend on the type of data messages. In order to demonstrate the behavior of sub-nets for tactical networks, theoretical findings are exploited with experimental analysis to provide practical implementation of schemes using contention-free time slotted common control channel for nodes coordination and time slotted collision-free multi-channel environment for data transmissions. The results show the effective coexistence of multiple transmissions in a network with increase in network throughput and lower the data latency up-to 76.8%, when compare to conventional MAC protocols. The design is workable for time sensitive, mission critical networks and expected to support multi-hop transmissions in similar manner.

Two-Dimensional Direction-of-Arrival and Polarization Parameter Estimation Using Parallel Co-Prime Polarization Sensitive Array

Target detection is critical in many mission critical sensors and sensor network (MC-SSN) applications. For target detection in complicated electromagnetic environment, DOA estimation using polarization sensitive array (PSA) has been receiving increased attentions. In this paper, we propose the parallel co-prime polarization sensitive array (PCP-PSA) which consists of the cocentered orthogonal dipole triads (CODTs) to estimate two-dimensional direction-of-arrival (2D DOA) and polarization parameters. The degrees of freedom (DOFs) have been extended due to the co-prime structure, so that the more signals can be detected and the estimation accuracy is improved. In order to reduce the computation complexity, we construct a new cross-covariance matrix based on the CODTs, which converts the two-dimensional DOA estimation into two independent one-dimensional DOA estimations. Then, the spatial smoothing-based multiple signal classification algorithm(MUSIC) and the sparse representation-based method are applied to estimate 2D DOA with only one-dimensional (1D) peak searching and 1D dictionary, respectively. Finally, the polarization parameters are estimated by using the cross-covariance matrix between components of electric field vector. Compared with previous PSA-based algorithms, the proposed algorithm based on PCP-PSA can solve the underdetermined 2D DOA and polarization parameters estimation problem and has better estimation accuracy. Theoretical analyses and simulation results verify the effectiveness of the proposed methods in terms of computational complexity and estimation accuracy.

Energy aware endurance framework for mission critical aerial networks

Recently, aerial networks have been offered as assistant communication infrastructures against some temporary operations especially in mission critical events. However, the lifetime of an aerial component is much less than the estimated operational time because of power supply capacity restrictions. Thus, there should be some replenishment processes between Aerial Base Stations (ABSs) to maintain the physical presence of the topology, i.e. the endurance. During a replenishment process, the relation between energy consumption and flight characteristic of a drone should be carefully taken in to account, because motional energy consumption is much more than the communicational and computational ones. For this purpose, we provide an energy aware endurance framework by modeling an energy consumption digraph model, representing an Aerial Pickup and Delivery Problem (APDP) for flight planning and implementing a novel algorithmic solution. Moreover, replenishment factor (γ) and flight planning cost (δ) parameters are presented to compare the evaluation of the proposed method with a simple replenishment approach. A social event in a stadium is selected as the evaluation environment, and is simulated for three scenarios using Software in the Loop (SITL) simulator with MAVLink Proxy drone controller. According to the evaluation results obtained from simulation logs, our design provides 13% more endurance per ABS (η), an average of 15% less energy consumption w.r.t. δ parameter and 11% less γ value compared to the simple replenishment strategy.

Medium Access Control for Unmanned Aerial Vehicle Based Mission Critical Wireless Sensor Networks in 3D Monitoring Networks

In this paper, a novel medium access control (MAC) layer protocol is introduced for unmanned aerial vehicle (UAV)-based mission critical wireless sensor networks (MC-WSN), which is an important application of mission critical sensor and sensor networks (MC-SSN). The UAVs hovering in the three-dimensional monitoring networks are distributed in subsets according to their distance from the center station. UAVs in the same subset are contending for access and transmission, while each subset is allotted a slot based on adaptive time division multiple access (TDMA) scheme. As a multi-channel system, a novel channel allocation algorithm is presented for subset relay transmission period to optimize the performance of networks. The UAV returning period for charging is utilized in the protocol to enhance the transmission throughput and mitigate delay. Detection slot and position prediction algorithm are designed in the UAV returning period to improve the throughput and reduce the delay. The simulation results verify the improvement on throughput and delays of the proposed protocol for UAV-based MC-WSN.

Adaptive Fuzzy Tree System for Target Tracking in Mission Critical Sensor Networks

The emergence of mobile sensors dramatically improves the availability of mission critical sensors and sensor networks (MC-SSN), enabling it to be utilized in more challenging tasks. However, current researches aimed to target tracking in mobile MC-SSN are very limited. This paper first proposes an adaptive fuzzy tree system (AFS) for target tracking in MC-SSN. To avoid oversimplifying the target mobile pattern, which is unrealistic in real tracking tasks, we introduce the target circle into the model considerations to add a bit of uncertainty about the target position. At each time step of the tracking process, strategy-selection layer will activate the pursuit strategy or the diffusion strategy for the specific situation, which makes the system more intelligent and can be applicable to various scenarios. The pursuit strategy is built by a two-layer fuzzy tree to select and mobilize sensors that have not detected target, while the diffusion strategy uses a fuzzy inference system to balance the density of detected sensors. And all the hyper-parameters are tuned by particle swarm optimization (PSO). We performed a large number of simulations with two target trajectories: line and irregular. The simulation results show that the AFS significantly outperforms the state-of-the-art algorithm. Moreover, it is highly robust to various target motion patterns, making it competent for a variety of real target tracking scenarios.

A Mathematical Model for Cross Layer Protocol Optimizing Performance of Software-Defined Radios in Tactical Networks

Unlike conventional mobile ad hoc networks, tactical networks, which provide communication of software-defined radios (SDRs) in mission critical and time-sensitive applications, require cognitive functions across the TCP/IP stack to encounter strict constraints while providing smooth incorporation with IP-based applications. The tactical applications are mission-critical and thus pose unique requirements for the network, including decentralized control and mission specific latency bounds for end-to-end data delivery. This paper presents a mathematical model for a cross-layer design, which optimizes trade-offs among different configurations of the SDRs to achieve maximum performance in terms of energy efficiency, reliable packet delivery at an appropriate data rate and within affordable latency bounds in multi-hop tactical networks. The proposed model is used in a number of mission-critical network scenarios to demonstrate enhanced performance, where SDRs effectively adapt to the dynamic environment.

Integration of sparse singular vector decomposition and statistical process control for traffic monitoring and quality of service improvement in mission-critical communication networks

Mission-Critical Communication Networks (MCCNs) are wireless networks whose malfunction can cause significant problems. The nature of MCCNs puts an extremely high standard on the Quality of Service (QoS). QoS assurance starts from monitoring and change/anomaly detection of network packets data. This problem has been primarily studied by the research community of communication networks, in which the existing methods fall short for providing a privacy-preserving, minimum-disruption, global monitoring tool. Another relevant research area is Multivariate Statistical Process Control (MSPC), in which generic methods have been developed for monitoring high-dimensional data streams. These methods do not account for the special data distribution and correlation structure of packet streams. Nor are they efficient enough to suit real-time analytics in MCCNs. We propose a method called Sparse Singular Value Decomposition (SSVD)-MSPC. SSVD-MSPC addresses the aforementioned limitations and additionally provides key capabilities toward QoS improvement, including monitoring, fault identification, and fault characterization. Extensive case studies are conducted for MCCNs that experience faults of different magnitudes and various temporal shapes. SSVD-MSPC achieves good performance across the different settings in comparison with existing methods.

Modeling Geographically Correlated Failures to Assess Network Vulnerability

Current communication networks are facing more and more threats from large-scale regional damages, such as natural disasters (e.g., earthquake or tornado) and physical attacks (e.g., electromagnetic pulse attack or dragging anchors). Recently, several region failure models have been proposed to evaluate the impact of such geographically correlated failures on communication networks. These works mainly adopt a kind of “deterministic” models, where network components within the affected area would fail simultaneously. Such failure models simplify the analysis but may fail to reflect some important behaviors of attacks and thus cause significant over- or under-estimation of region failures. To emulate the impact of realistic catastrophe events such as earthquake and tornado, this paper introduces two probabilistic failure models: 1) a concentric circle model and 2) a line segment model. In the probabilistic models, both the location and effect of the damage are treated as random events. The failure may randomly incur on the entire network plane, and the failure probability of a device depends on many factors, e.g., link length and distance to the damage center. We develop an efficient grid partition-based scheme to estimate the network vulnerability. Based on the grid partition scheme, we further develop a sampling scheme to significantly reduce the computation cost. The probability model helps us more deeply understand the network behaviors under region failure and facilitates the design and maintenance of future highly survivable mission critical networks.