Communication In Ad-hoc Networks Research Articles

Comparative analysis of reactive routing protocols for vehicular adhoc network communications

In the recent past, vehicular adhoc networks (VANETs) have gained a lot of importance. The routing protocols play a vital role to deliver payloads from one vehicle to another one while they are moving at relative speeds. It is a challenging task to select a routing protocol for VANETs because of the uneven distribution and high mobility of vehicles. In this paper, we have analysed the two standard reactive protocols, adhoc on-demand distance vector (AODV) and ant colony optimization (ACO). The performance comparison of AODV and ACO routing protocols has been presented in this paper. The results show AODV performed better in terms of energy consumption and routing overhead. While considering the throughput, energy loss ratio, and delay ACO has performed. ACO resulted as upperhand.

Development of a routing method for ground-air Ad-Hoc network of special purpose

The object of the study is the process of forming control decisions to ensure the operation of the ground-air communication network routing subsystem based on neural network algorithms. The carried-out research is based on the application of the numerical-analytical approach to the selection of modern scientific and applied solutions for building management models for promising Ad-Hoc communication networks. In the Google Collab simulation environment, using the Python programming language, it was possible: firstly, to simulate the operation of a ground-to-air communication network based on previously obtained models and a routing process management system based on the FA-OSELM algorithm. Secondly, in accordance with the scenario of route construction and maintenance described in the article, to experimentally determine the communication metrics of the proposed method of intelligent routing of the ground-air Ad-Hoc special-purpose network, in order to assess its efficiency, adequacy and reliability of the results obtained. Thus, in order to evaluate the effectiveness of the proposed solutions, a comparative analysis of the application of three existing routing methods (FLCA, Q-Routing, Neuro Routing) used in Ad-Hoc networks relative to the developed method was conducted. The result of the experiment showed that the proposed routing method MAODV-FA-OSELM provides significant advantages over analogs. Thus, the method exhibits the best network throughput (2.12e+06), the lowest average network latency (0.12), the lowest packet loss (6.32), the lowest bit error rate (2.41), and the lowest overhead (0.10e+06). However, it should be noted that a promising direction of further research may be the study of the computational complexity of the routing management process and the determination of the minimum allowable representative sample of initial data to ensure online decision-making.

Active manipulation of a tethered drone using explainable AI

Tethered drones are currently finding a wide range of applications such as for aerial surveillance, traffic monitoring, and setting up ad-hoc communication networks. However, many technological gaps are required to be addressed for such systems. Most commercially available tethered drones hover at a certain position; however, the control task becomes challenging when the ground robot or station needs to move. In such a scenario, the drone is required to coordinate its motion with the moving ground vehicle without which the tether can destabilize the drone. Another challenging aspect is when the system is required to operate in GPS denied environments, such as in planetary exploration. In this paper, to address these issues, we take advantage of passive or force-based control in which the tension in the tether is sensed and used to drive the drone. Fuzzy logic is used to implement the force-based controller as a tool for explainable Artificial Intelligence. The proposed fuzzy logic controller takes tether force and its rate of change as the inputs and provides desired attitudes as the outputs. Via simulations and experiments, we show that the proposed controller allows effective coordination between the drone and the moving ground rover. The rule-based feature of fuzzy logic provides linguistic explainability for its decisions. Simulation and experimental results are provided to validate the novel controller. This paper additionally develops an adaptive controller for estimating unknown constant winds on these tethered drone systems using a proportional controller. The simulation results demonstrate the effectiveness of the proposed adaptive control scheme in addressing the effect of wind on a tethered drone.

Distributed Data-Driven Learning-Based Optimal Dynamic Resource Allocation for Multi-RIS-Assisted Multi-User Ad-Hoc Network

This study investigates the problem of decentralized dynamic resource allocation optimization for ad-hoc network communication with the support of reconfigurable intelligent surfaces (RIS), leveraging a reinforcement learning framework. In the present context of cellular networks, device-to-device (D2D) communication stands out as a promising technique to enhance the spectrum efficiency. Simultaneously, RIS have gained considerable attention due to their ability to enhance the quality of dynamic wireless networks by maximizing the spectrum efficiency without increasing the power consumption. However, prevalent centralized D2D transmission schemes require global information, leading to a significant signaling overhead. Conversely, existing distributed schemes, while avoiding the need for global information, often demand frequent information exchange among D2D users, falling short of achieving global optimization. This paper introduces a framework comprising an outer loop and inner loop. In the outer loop, decentralized dynamic resource allocation optimization has been developed for self-organizing network communication aided by RIS. This is accomplished through the application of a multi-player multi-armed bandit approach, completing strategies for RIS and resource block selection. Notably, these strategies operate without requiring signal interaction during execution. Meanwhile, in the inner loop, the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm has been adopted for cooperative learning with neural networks (NNs) to obtain optimal transmit power control and RIS phase shift control for multiple users, with a specified RIS and resource block selection policy from the outer loop. Through the utilization of optimization theory, distributed optimal resource allocation can be attained as the outer and inner reinforcement learning algorithms converge over time. Finally, a series of numerical simulations are presented to validate and illustrate the effectiveness of the proposed scheme.

NextGenV2V: Authenticated V2V communication for next generation vehicular network using (2, n)-threshold scheme

Securing end-to-end communication in Vehicular Ad-hoc Networks (VANET) is crucial due to zero trust between the communicating entities. Additionally, the underlying communication needs to be lightweight in many cases, especially when vehicles are moving at high speeds or deploying applications like Vehicular Sensor Networks (VSN) and next-generation vehicular networks with densely deployed small-cells and micro-cells. The traditional VANET facilitates two types of communication: Vehicle-to-Infrastructure (V2I) communication to establish trust between a Vehicle User (Vi) and roadside infrastructure, followed by Vehicle-to-Vehicle communication for information exchange. Unlike existing protocols that encounter security issues and high authentication delay as they require communication with a Trusted Authority (TA) every time Vi needs authentication or re-authentication, we present a symmetric key-based an authenticated V2V communication for next generation vehicular network using (2, n)-threshold scheme, called NextGenV2V. In NextGenV2V, authentication of a newly visited Vi is performed with the help of TA, but re-authentication of a pre-authenticated Vi is done without the support of TA. This significantly reduces communication overhead during re-authentication and improves the overall authentication delay. NextGenV2V is designed in such a way that at least 2 out of n registered vehicle users must cooperate to compute a shared secret key. This feature ensures improved security, as attackers cannot breach the system’s security unless two or more vehicles are compromised. Furthermore, considering that an attacker cannot physically be present in more than one location simultaneously, the system’s security remains intact even if a current vehicle is compromised. The proposed protocol is also verified to resist known security attacks, both formally and informally. To demonstrate the effectiveness of NextGenV2V, a comparative performance analysis is presented that proves its suitability for next-generation vehicular networks.

Optimizing VANET Communication through Realistic Traffic Simulation

This article explores the optimization of communication in Vehicular Ad-Hoc Networks (VANETs) through the use of realistic traffic simulation in Raipur City, located in the state of Chhattisgarh. VANETs are a specialized type of Mobile Ad-Hoc Networks (MANETs) that enable vehicles to communicate with each other and with roadside infrastructure, improving road safety, traffic efficiency, and providing additional services. However, VANETs encounter challenges due to the dynamic nature of vehicular environments, including high mobility, intermittent connectivity, and varying traffic conditions. To address these challenges, this study proposes the Integration to Message Exchange (IME) method, which incorporates realistic traffic simulation into VANET communication optimization strategies. Realistic traffic simulation models vehicle behavior and interactions with the road network, considering factors such as traffic flow, congestion, and road conditions. By integrating this simulation into VANET communication optimization algorithms, the performance of the proposed IME method and other routing strategies is evaluated under realistic traffic scenarios. The results demonstrate that the IME method significantly improves message delivery rates and reduces message latency compared to the D-LAR and AODV routing methods. In comparison to the DLAR method, the IME method increases the packet delivery ratio by 4.82%, reduces end-to-end delay by 4.0%, increases throughput by 4.85%, decreases routing overhead by 8.79%, and normalizes routing load by 7.71%. The city of Raipur in Chhattisgarh is the geographical context for this research. Raipur is a rapidly growing urban area with diverse traffic patterns and road conditions. By conducting experiments and simulations in this specific setting, the findings of this study can directly address the challenges faced by VANETs in Raipur City.

LAPEP—Lightweight Authentication Protocol with Enhanced Privacy for effective secured communication in vehicular ad-hoc network

LAPEP—Lightweight Authentication Protocol with Enhanced Privacy for effective secured communication in vehicular ad-hoc network

Efficiency Assessment of Routing Protocols for Enhanced Communication in Vehicular Ad Hoc Networks

Efficiency Assessment of Routing Protocols for Enhanced Communication in Vehicular Ad Hoc Networks

An aeronautical data communication demand model for the North Atlantic oceanic airspace

Information exchange via aeronautical data communication is of increasing importance for the communication between pilots and air traffic control, providing the basis for surveillance of aircraft in oceanic or remote airspaces, as well as enabling the communication between an airlines’ fleet and its operational control. The aeronautical data communication that is being transmitted via data link encompasses, among others, surveillance-related aircraft position updates, clearances for flight path change requests, maintenance-related status reports, estimated arrival times and weather information in accordance with the required performance, that is set by technical standards. Aeronautical data communication events are driven by an aircraft’s flight phase, the current airspace or may occur in a randomized manner throughout the flight. As the usage of aeronautical data communication is expected to grow in future, ample data link technologies are being evaluated and developed. The usability and operational value of new data link technologies for aeronautical applications can be evaluated by applying suitable models of the respective data link communication pattern combined with operational simulations. Current models for aeronautical data communication demand support the design and evaluation of direct aircraft-to-ground communication networks. The geographical location of the data communication demand is secondary for these models, since coverage areas can be defined, where direct communication links are available. New data link technologies offer the opportunity of direct data transfer between aircraft and forwarding of messages from sending aircraft to a ground entity via ad-hoc communication networks between aircraft. This is of special interest for the North Atlantic oceanic airspace, an airspace with high traffic density and little ground infrastructure, where communication currently relies mostly on satellite-based systems. For these airborne ad-hoc networks the definition of coverage areas around ground or space-based entities is not possible. To assess the new data link technology a model for aeronautical data link communication demand is needed, that accounts for operationally derived communication events such as handover procedures at boundaries of oceanic control areas or status reports at route-specific waypoints, which cause an accumulation in certain geographical regions that pose a challenge to the dynamic connectivity coverage of aeronautical ad-hoc networks. Addressing this issue, we present a new modelling approach for air traffic service communication that considers the operational context of the simulated airspace and provides a geospatial data communication demand distribution, which is derived from air traffic management procedures, airspace geometries and events inherent to each flight path. The air traffic service communication is then validated based on 2019 air traffic and performance monitoring data provided by ICAO supplemented by an existing model for communication related to airline operational control. In a next step, the communication demand per area in the North Atlantic Oceanic airspace is being assessed. The aeronautical data traffic model shows deviations of less than one message per aircraft and airspace when compared to recorded data traffic from 2019 for two key services in the most frequented North Atlantic oceanic control areas. Therefore, it is assumed to be suitable for the evaluation of network-based data link technology and operational impact assessments.

Trust Model for Reliable Grouping-Based Communications in Vehicular Ad-Hoc Networks

Trust Model for Reliable Grouping-Based Communications in Vehicular Ad-Hoc Networks

Intelligent Driver Model-Based Vehicular Ad Hoc Network Communication in Real-Time Using 5G New Radio Wireless Networks

Vehicular ad hoc networks (VANETs) are self-organizing, open-structure inter-vehicle communication networks, along with wireless communication technology and transportation. Vehicle communication aims to improve the driver’s response-ability and ensure traffic safety when encountering traffic accidents. The 5G NR on V2V communication, compared to fourth-generation (4G) long-term evolution (LTE), is more sophisticated and has ultra-high reliability. This research proposes intelligent driver model-lane changes (IDM-LC) and intelligent driver model-avoidance (IDM-A) models, which enhance the performance accuracy of the V2V communication through the 5G NR system. In this case, the authenticity of the vehicle movement models is tested on different road scenarios, i.e., square, hexagon, heptagon and triangle. In these scenarios, the vehicles’ movements over the 5G networks receive widespread coverage whenever the vehicles receive signals from the roadside unit (RSU). Hence, the flexibility of VANET is used to improve the device-to-device (D2D) or vehicle-to-vehicle (V2V) communication efficiency in the fifth-generation (5G) new radio (NR) system. In addition, the VANET simulation platform, i.e., simulation of urban mobility (SUMO) and network simulator-3 (NS-3), simulate and evaluate the comparison of V2V through the 5G networks, which receives widespread coverage in 15 to 20 m/s. The simulation results and analysis show that the V2V communication through the 5G system performs better on the IDM models.

Efficient Coherent Trust based Location Aware Clustering for Communication in Mobile Ad Hoc Networks

Efficient Coherent Trust based Location Aware Clustering for Communication in Mobile Ad Hoc Networks

A Multi-Tier Trust-Based Security Mechanism for Vehicular Ad-Hoc Network Communications

Securing communications in vehicle ad hoc networks is crucial for operations. Messages exchanged in vehicle ad hoc network communications hold critical information such as road safety information, or road accident information and it is essential these packets reach their intended destination without any modification. A significant concern for vehicle ad hoc network communications is that malicious vehicles can intercept or modify messages before reaching their intended destination. This can hamper vehicle ad hoc network operations and create safety concerns. The multi-tier trust management system proposed in this paper addresses the concern of malicious vehicles in the vehicle ad hoc network using three security tiers. The first tier of the proposed system assigns vehicles in the vehicle ad hoc network a trust value based on behaviour such as processing delay, packet loss and prior vehicle behavioural history. This will be done by selecting vehicles as watchdogs to observe the behaviour of neighbouring vehicles and evaluate the trust value. The second tier is to protect the watchdogs, which is done by watchdogs' behaviour history. The third security tier is to protect the integrity of data used for trust value calculation. Results show that the proposed system is successful in identifying malicious vehicles in the VANET. It also improves the packet delivery ratio and end-to-end delay of the vehicle ad hoc network in the presence of malicious vehicles.

LA-SPA: A new learning automata-based approach for the parking space selection and reservation

Nowadays, with the increasing number of vehicles in the urban environment, finding a parking space has become an important and challenging issue. Vehicles may have to spend a lot of time looking for a parking space, which can lead to excessive fuel consumption, area traffic congestion, increased air pollution, and even driver impatience and immorality. To solve this problem, this article has used Roadside-to-Vehicle/Vehicle-to-Roadside (R2V/V2R), Roadside-to-Roadside (R2R) and Parking-to-Roadside/Roadside-to-Parking (P2R/R2P) communication in Vehicular Ad-hoc Network (VANET) and learning automata with variable actions to select and reserve the most suitable parking space. The performance of the proposed method was evaluated using computer simulation. The simulation results showed the efficiency of the proposed method in terms of improving service quality, reducing computational overhead, and making optimal use of parking resources in the city compared to existing methods. The proposed algorithm helps reduce air and noise pollution by reducing traffic congestion caused by parking space searches, and also helps increase the use of parking facilities efficiently.

Improving the geo-drone-based route for effective communication and connection stability improvement in the emergency area ad-hoc network

Current work focuses on establishing communication connectivity that is specially designed for wireless mobile sensor networks, especially the high connectivity stability of the disaster area network. Existing system focuses on location initial communications and utilizes networks based on most Internet Protocol (IP) frameworks. To solve these problems, reduce the number of neighboring countries (node density) and avoid high mobility notes (node speed). This proposed Geographic Node Speed Drone Based Routing Path Optimization (GNSDRPO) system to significantly reduce overall overhead and node speed improves overall performance by detecting the area of disaster. To keep the drone-based disaster network in the area, this drone communicates from time to time and shares information with the anchor tip. Geo-tracking appears to be a promising approach to improving routing performance on the MANET. Geographic navigation appears to be a promising approach to improving routing performance on MANET. This method is to reach the anchor end node using a geographical map-based mapping (GGMBM). The mobile anchor enables GPS on the mobile network and constantly broadcasts its location to assist locations. In the first step, the node looks for the expected ETX (Expected number of Transfers) locally and remotely and calculates the distance estimated by it. RSSI results are stored in the node's local memory. The node calculates the expected ETX (Expected number of Transfers), connection loss rate and new location information over short distances. Freeway heuristic algorithm improves data speed and performance and determines path, optimization problem. This proposed method improves efficient communication, increases efficiency and reduces latency in the disaster area network compared to other methods.

Reinforcement Learning Environment for Advanced Vehicular Ad Hoc Networks Communication Systems.

Ad hoc vehicular networks have been identified as a suitable technology for intelligent communication amongst smart city stakeholders as the intelligent transportation system has progressed. However, in a highly mobile area, the growing usage of wireless technologies creates a challenging context. To increase communication reliability in this environment, it is necessary to use intelligent tools to solve the routing problem to create a more stable communication system. Reinforcement Learning (RL) is an excellent tool to solve this problem. We propose creating a complex objective space with geo-positioning information of vehicles, propagation signal strength, and environmental path loss with obstacles (city map, with buildings) to train our model and get the best route based on route stability and hop number. The obtained results show significant improvement in the routes’ strength compared with traditional communication protocols and even with other RL tools when only one parameter is used for decision making.

Energy-efficient dynamic wireless communication for wireless mobile ad-hoc networks using hybrid cryptography-based acknowledgement method

Energy efficiency continues to be a key factor limiting the ability to deploy ad-hoc networks. Deploying an energyefficient system that maximizes network lifetime has been a major challenge for many years. Many algorithms have been proposed to solve this problem. This paper proposes a new intrusion detection system—Enhanced Adaptive 3 Acknowledgment (EA3ACK)—using the Energy Efficiency Dynamic State (EEDS) algorithm. This algorithm is designed to increase network lifetime and residual energy by constantly monitoring individual nodes in the network, thereby improving the network's quality of service. The Network Simulator (NS2) is used to implement and test the proposed system.

ANALYSIS OF ENHANCED ENERGY EFFICIENT SINKHOLE ATTACK PREVENTION ON AD-HOC NETWORKS

Abstract- MANET is one of self-configuring fastest emerging, technology, due to commencement of economical, small & more powerful wireless devices. It is being used in most of applications, ranging from military to civilian, where each node acts as router. To facilitate communication in ADHOC network, a routing protocol is vital whose primary goal is to establish accurate & efficient route between pair of nodes, due to this lot of routing protocols have been proposed for MANET & its success depends on people’s confidence in its security. In this paper we discuss an energy efficient technique of sinkhole analysis on Ad-Hoc networks.

Methodology for estimating the energy reserve of a mobile ad-hoc communication network with UV-C channel

Communication systems of the solar-blind ultraviolet range UV-C from 200 to 280 nm provide the possibility of communication in the absence of line of sight due to the strong scattering of UV radiation in the atmosphere. For the effective use of UV-C communication systems, an adequate assessment of the energy budget of the UV channel is necessary. Analytical expressions are obtained that characterize the energy reserve of the UV-C system in relation to the specified characteristics of the optical receiver, transmitter, and UV channel. Based on the analytical and numerical model of losses in the UV channel, the energy reserve of the UV-C communication system is modeled on the distance between the transmitter and receiver, the elevation angles and the azimuthal deviation of the transmitter and receiver. The results obtained can be used to calculate and optimize ad-hoc communication networks with UV-C channel, characterized by changes in the spatial location of network nodes during operation.

A novel cluster based highway mobility model (CHMM) for low power vehicular networks

One of the most essential variables for building a routing protocol for vehicular communication in Vehicular Ad Hoc Network (VANET). The study of these vehicular ad-hoc networks (VANETs) necessitates efficient and accurate modelling tools, and the key element of the mobility model in the VANET is for influencing the route-finding process and altering failure. Because network communications might alter vehicle mobility and driver behavior, these tools should incorporate a vehicle mobility model. In this paper, designing a new realistic model of node motion based on vehicle movement on roads. It shows how a well-known vehicle mobility concept has been implemented. Various events are used to integrate vehicle mobilitywith network communication. User-created event handlers can send network messages or alter vehicle mobility when the model receives a network message or updates vehicle mobility. In order to aid in the creation of the simulations, implementing a straight highway mobility model which is called as Highway Mobility Model based on Cluster that manages vehicle mobility efficiently.