Ad Hoc Networks Research Articles

BRIDGING CONNECTIVITY GAPS WITH DYNAMIC AND SELF-ORGANIZING COMMUNICATION IN AD-HOC WIRELESS NETWORKS

Ad-hoc wireless networks are characterized by their dynamic and self-organizing nature, making them suitable for scenarios where traditional infrastructure-based networks are impractical or unavailable. However, the inherent mobility and decentralized nature of ad-hoc networks pose significant challenges in maintaining reliable connectivity. This paper proposes a novel approach to address these challenges by leveraging the Zone Routing Protocol (ZRP) to facilitate dynamic and self-organizing communication in ad-hoc wireless networks. The ZRP divides the network into overlapping zones, with each node responsible for routing within its respective zone. By dynamically adjusting zone boundaries based on network topology changes, ZRP enables efficient routing while minimizing overhead. This adaptability is crucial in ad-hoc environments where node mobility and network topology fluctuations are common. The evaluation results demonstrate significant improvements in connectivity, reduced routing overhead, and enhanced resilience to network dynamics compared to traditional routing protocols.

Cognitive routing in software defined networks using learning models with latency and throughput constraints

<p>To address latency and throughput challenges in software defined networks (SDNs), the research investigates cognitive routing's revolutionary implications. In today's data-driven world, network performance optimisation is crucial. Cognitive routing is a dynamic and potentially disruptive network management technology. Cognitive routing, strengthened by reinforcement learning and adaptive decision-making, is crucial to network efficiency and responsiveness, according to our study. The results show that cognitive routing optimises performance by limiting delay and maximising throughput. SDN application cognitive routing engine (CRE) driving forces, design, and preliminary assessment are described in this article. The CRE finds almost optimal paths for a user's quality of service (QoS) need while minimising monitoring overhead. Instead of global monitoring to find optimal paths, local monitoring achieves this. In ad-hoc networks, finding a trustworthy path reduces latency and ensures network stability. The proposed system was simulated utilising many parameters. Compared to previous SDN-based systems, end-to-end latency and ping round-trip time were better.</p>

Blockchain-Based Trust Management Model for Vehicular Ad Hoc Networks

Blockchain-Based Trust Management Model for Vehicular Ad Hoc Networks

ENHANCING SERVICE DISCOVERY IN MOBILE AD HOC NETWORKS USING SEMANTIC CLUSTERING AND HYBRID TRUST MANAGEMENT

Mobile Ad Hoc Networks (MANETs) facilitate communication among mobile devices without relying on fixed infrastructure. However, service discovery in MANETs faces challenges due to the dynamic topology and limited resources of nodes. Existing solutions often lack efficient resource utilization and fail to address trust management adequately. The conventional approaches for service discovery in MANETs are inefficient due to their inability to incorporate semantic clustering and robust trust management. Semantic clustering enhances the accuracy of service discovery by grouping nodes based on similar interests or functionalities. Meanwhile, traditional trust management mechanisms are inadequate in dynamic environments, leading to unreliable service discovery results. The proposed methodology involves developing a semantic clustering algorithm to organize nodes based on their semantic similarities. Additionally, a hybrid trust management system is implemented to assess the reliability of discovered services. The system combines both reputation-based and recommendation-based trust models to enhance the accuracy of trust evaluations. Through extensive simulations and experiments, the effectiveness of the proposed approach is demonstrated. The results indicate that the integration of semantic clustering and hybrid trust management significantly improves service discovery efficiency and reliability in MANETs. The approach achieves higher precision and recall rates compared to conventional methods, even under dynamic network conditions.

SECURING MOBILE AD-HOC NETWORKS USING ROBUST SECURED IPS ROUTING APPROACH THROUGH ATTACK IDENTIFICATION AND ELIMINATION IN MANETS

Mobile Ad-hoc Networks (MANETs) are susceptible to various security threats due to their decentralized and dynamic nature. Among these threats, Distributed Denial of Service (DDoS) and sibling attacks pose significant challenges to the integrity and availability of network services. This paper presents a novel approach for securing MANETs against DDoS and sibling attacks through a robust Intrusion Prevention System (IPS) integrated with a secured routing mechanism. The proposed methodology leverages residual transfer learning to adapt a pre-trained model for intrusion detection to the MANET environment, enhancing its effectiveness in identifying and mitigating attacks. The problem of securing MANETs against DDoS and sibling attacks is exacerbated by the lack of centralized infrastructure and the dynamic topology of the network. Traditional security mechanisms designed for wired networks are often ineffective in MANETs due to their reliance on centralized control and communication. This research addresses this gap by proposing an IPS solution tailored specifically for MANETs, capable of detecting and preventing attacks without relying on centralized coordination. By utilizing residual transfer learning, the proposed methodology addresses the challenge of limited labeled data in the MANET domain. Transfer learning enables the adaptation of knowledge from a pre-trained model on non-MANET data to improve the performance of intrusion detection in MANET environments. The integration of the IPS with a secured routing approach ensures that detected attacks are efficiently handled within the network, minimizing their impact on performance and ensuring continued operation. Experimental results demonstrate the effectiveness of the proposed approach in mitigating DDoS and sibling attacks in MANETs. The integrated solution achieves high detection rates while minimizing false positives, thereby enhancing the security and resilience of MANETs against evolving threats.

Enhancing Road Safety: Machine Learning-Driven Vehicle Speed Monitoring and Alerting in VANET Environments-A Review

Inexperienced and fast driving poses a significant threat to the safety of innocent people, resulting in severe automobile accidents. Presently, most efforts have been made in detecting the driver behavior, as traditional methods show limited success the researchers have delved into the machine learning and the deep learning methods for predicting the vehicle speed and as well as altering. This review explores at the manner in which machine learning and the deep learning can be used to improve road safety using Vehicle Ad-hoc Networks. The primary objective revolves around a Machine Learning-Driven Vehicle Speed Monitoring and Alerting System, which is intended to reduce the dangers associated with variable speeds in VANET environments. The paper reviews the existing research, approaches, and breakthroughs in the use of machine learning algorithms for real-time vehicle speed monitoring. This analysis intends to provide insights into the emerging environment of intelligent transportation systems, with a focus on the role of artificial intelligence in identifying and responding to potential risks. It presents an in-depth review of the challenges, opportunities, and future prospects for using machine learning to improve road safety within the VANETs.

Vehicle Identity Anonymity Framework with Accountability for VANET Environment

<p>In recent years, there has been rapid development in vehicle safety technology, with the emergence of various active safety systems including blind spot information systems, adaptive cruise control, and front collision warning systems. Simultaneously, car manufacturers and technology companies are actively exploring technologies in the realm of autonomous driving. To facilitate such applications, vehicles are required to communicate with each other, exchanging vital information such as position, speed, and acceleration. However, this exchange of information poses a potential risk of drivers’ personal data being compromised. For safety purposes, vehicles must undergo appropriate authentication before engaging in communication with other vehicles. Ensuring this authentication process maintains the anonymity of the vehicles is crucial. Yet, striking a balance between protecting vehicle anonymity and enabling vehicle identification when necessary remains a challenging issue. This paper introduces a multi-tier Vehicular Ad-Hoc Network (VANET) framework designed to uphold the conditional anonymity and traceability of vehicles. The implementation of a group signature mechanism facilitates anonymous authentication, thereby enabling the realization of conditional anonymity and traceability. Moreover, comprehensive simulations and security analyses were conducted to validate the effectiveness of the proposed framework, demonstrating its efficiency while incorporating robust safety considerations.</p> <p> </p>

Information Technology Security and Privacy Protection in Vehicular Networks (VANETs)

Abstract: As Vehicular ad hoc networks (VANETs) become more sophisticated, the importance of integrating data protection and IT Security is increasingly evident. This paper offers a comprehensive investigation into the challenges and solutions associated with the privacy implications within VANETs, rooted in an intricate landscape of cross-jurisdictional data protection regulations. Our examination underscores the unique nature of VANETs, which, unlike other ad-hoc networks, demand heightened security and privacy considerations due to their exposure to sensitive data such as vehicle identifiers, routes, and more. Through a rigorous exploration of pseudonymization schemes, with a notable emphasis on the Density-based Location Privacy (DLP) method, we elucidate the potential to mitigate and sometimes sidestep the heavy compliance burdens associated with data protection laws. Furthermore, this paper illuminates the IT Security vulnerabilities inherent to VANETs, proposing robust countermeasures, including secure data transmission protocols. In synthesizing our findings, we advocate for the proactive adoption of protective mechanisms to facilitate the broader acceptance of VANET technology while concurrently addressing regulatory and IT Security hurdles.

A Review of Power Management Approaches for Mobile Ad Hoc Networks

A Review of Power Management Approaches for Mobile Ad Hoc Networks

A Reliable Transmission on Cluster Based Wireless Ad Hoc Network with Adaptive Negotiations Using Vector Assisted Energy Efficient Dynamic Opportunistic Routing Mechanism

A Reliable Transmission on Cluster Based Wireless Ad Hoc Network with Adaptive Negotiations Using Vector Assisted Energy Efficient Dynamic Opportunistic Routing Mechanism

Cooperative Sensing Assisted Cross layer QoS Assured Routing in Cognitive Radio Adhoc Networks: Ensuring Security and Privacy

Cooperative Sensing Assisted Cross layer QoS Assured Routing in Cognitive Radio Adhoc Networks: Ensuring Security and Privacy

A Comparative Study on Software-Defined Network with Traditional Networks

The emergence of a technological age, in which nearly everything is linked and accessible from anywhere, is largely due to the Internet. Hence, traditional Networks continue to be difficult and complex to operate despite their widespread deployment. As a consequence, it is challenging to set up the networks in accordance with the established protocols and respond to variations in load and defects by reconfiguring the structure. The data and control layers are packaged together in the contemporary systems, further complicating problems by vertically integrating them. Because of their limited resources and unsecured transmission channel, wireless sensor networks (WSNs) are particularly vulnerable to persistent security attacks. Many hundreds of self-organized and resource-constrained sensor nodes make up the WSN. It is possible to build an ad-hoc network of sensors without a specified architecture or centralised control because these sensor nodes are often organised in a scattered form. The underlying problem is to strengthen the privacy enforcement in these systems because WSNs will have power over real-time applications, where unauthorized conduct might lead to significant harm. In order to address this issue, the software-defined network (SDN) technology was developed. With the creation of SD, network operators now have more legitimacy and influence over the networks. Based on a global perspective and centralised management of the network topology, SDN has increased the rigour of its enhancing security. This study describes the software-defined network, outlining its fundamental ideas, how it differs from conventional networking, and its architectural tenets. Also, it highlighted the key benefits of SDN while emphasizing availability, maliciousness, packet delivery and duplication ratio, and efficiency.

Mobile Adaptive Routing Algorithm for Road-Aware Infrastructure-Assisted Communication in Cognitive Internet of Vehicles

The Internet of Things (IoT) is expanding the capabilities of traditional vehicular ad-hoc networks (VANET) into the Internet of Vehicles (IoV). However, there are a few challenges that need to be addressed in order to enhance the intelligence of IoV, leading to the development of a new evolving technology called Cognitive Internet of Vehicles (CIoV). In this study, we propose a road-aware infrastructure-assisted and vehicle-to-vehicle (V2V) adaptive routing system to select the most efficient route for delivering data from the source to the destination vehicle, with the aim of reducing data delivery delay. The performance is measured and evaluated based on packet delivery ratio (PDR), average end-to-end (E2E) delay, and normalised routing overhead using MATLAB. By comparing the proposed mobile adaptive routing algorithm (MARA) with existing protocols, it has been examined and found to outperform the existing ones in terms of performance.

Advancements and Challenges in IoT Simulators: A Comprehensive Review.

The Internet of Things (IoT) has emerged as an important concept, bridging the physical and digital worlds through interconnected devices. Although the idea of interconnected devices predates the term "Internet of Things", which was coined in 1999 by Kevin Ashton, the vision of a seamlessly integrated world of devices has been accelerated by advancements in wireless technologies, cost-effective computing, and the ubiquity of mobile devices. This study aims to provide an in-depth review of existing and emerging IoT simulators focusing on their capabilities and real-world applications, and discuss the current challenges and future trends in the IoT simulation area. Despite substantial research in the IoT simulation domain, many studies have a narrow focus, leaving a gap in comprehensive reviews that consider broader IoT development metrics, such as device mobility, energy models, Software-Defined Networking (SDN), and scalability. Notably, there is a lack of literature examining IoT simulators' capabilities in supporting renewable energy sources and their integration with Vehicular Ad-hoc Network (VANET) simulations. Our review seeks to address this gap, evaluating the ability of IoT simulators to simulate complex, large-scale IoT scenarios and meet specific developmental requirements, as well as examining the current challenges and future trends in the field of IoT simulation. Our systematic analysis has identified several significant gaps in the current literature. A primary concern is the lack of a generic simulator capable of effectively simulating various scenarios across different domains within the IoT environment. As a result, a comprehensive and versatile simulator is required to simulate the diverse scenarios occurring in IoT applications. Additionally, there is a notable gap in simulators that address specific security concerns, particularly battery depletion attacks, which are increasingly relevant in IoT systems. Furthermore, there is a need for further investigation and study regarding the integration of IoT simulators with traffic simulation for VANET environments. In addition, it is noteworthy that renewable energy sources are underrepresented in IoT simulations, despite an increasing global emphasis on environmental sustainability. As a result of these identified gaps, it is imperative to develop more advanced and adaptable IoT simulation tools that are designed to meet the multifaceted challenges and opportunities of the IoT domain.

Enhancing Intrusion Detection Systems through Distributed Ledger Technology for Secure Logging

Nodes in Mobile Ad Hoc Networks (MANETs) are limited battery powered. That’s why energy efficient routing has become an important optimization criterion in MANETs. The conventional routing protocols do not consider energy of the nodes while selecting routes which leads to early exhaustion of nodes and partitioning of the network. This paper attempts to provide an energy aware routing algorithm. The proposed algorithm finds the transmission energy between the nodes relative to the distance and the performance of the algorithm is analyzed between two metrics Total Transmission energy of a route and Maximum Number of Hops. The proposed algorithm shows efficient energy utilization and increased network lifetime with total transmission energy metric.

Optimizing Multichannel Path Scheduling in Cognitive Radio Ad Hoc Networks using Differential Evolution

One important area of study in cognitive radio ad hoc networks is multi-channel path scheduling. Cognitive radio networks have trouble communicating and using the spectrum effectively because of weather and dispersion. Optimizing multichannel path scheduling enhances network performance and reliability in a cognitive radio ad hoc net. The Optimizing Multichannel Path Scheduling (OMPS) model methodically tackles various scheduling problems. For the OMPS model, this domain is new. It effectively resolves multichannel path scheduling. The computer method used in the study is called Differential Evolution. During optimization, several factors are carefully considered, including Channel Fade Margin, Cross-Correlation and Coherence Time, Spectral Efficiency, Interference Level, Power Consumption, Retransmission Rate, Access Probability, and Propagation Delay. To increase the scheduling efficiency of the DE algorithm, many steps are meticulously planned: initialization, mutation, crossover, fitness evaluation, selection for iteration evolution, and termination. Latency, Packet Delivery Ratio (PDR), Spectrum Utilization, Interference Level, Energy Efficiency, and Established Path Success Rate are all assessed by the OMPS model. These indicators assess the effectiveness and dependability of the network. OMPS performs better in crucial simulations than the existing model. The demonstration demonstrates decreased latency for real-time applications, greater packet delivery ratios (PDRs), improved spectrum efficiency, channel interference, energy efficiency, and connection formation odds, as well as increased throughput that enhances network resource utilization. To do this, a variety of multichannel path scheduling situations are simulated.

A lightweight privacy preserving distributed certificate-less aggregate based mutual authentication scheme for vehicular adhoc networks

A lightweight privacy preserving distributed certificate-less aggregate based mutual authentication scheme for vehicular adhoc networks

Topology Control Using Optimized Clustering Scheme in Mobile Ad Hoc Network

Due to mobile nodes (MNs), the topology of mobile ad hoc networks (MANETs) frequently varies. Clustering techniques are suggested as a solution to this. Grouping MNs in a MANET has the benefit of reducing congestion and making topology repairs simple. Clustered MN dividing is a multi-objective optimization problem when the MANET size is huge. MANET is partitioned into clusters using a variety of evolutionary methods, including genetic algorithms (GAs). GA has early convergence. Thus, an improved rabbit optimization algorithm (IROA)-based clustering is presented in this work. Using this algorithm, cluster heads (CHs) are selected. Besides, multi-objective functions are used in this algorithm for selecting suitable CHs. Based on the selected CHs, clusters are formed. To manage the topology after clustering, cluster maintenance phase is included. Simulation results of the article depict that the proposed clustering scheme achieves better throughput and energy efficiency.

Performance evaluation of routing in flying ad-hoc networks using nature-inspired algorithms

Flying ad-hoc network (FANET) has been growing rapidly and can utilized in sectors such as disaster response, healthcare, military, agriculture, and more. These networks utilize Unmanned aerial vehicles (UAVs), required advanced routing algorithms for effective communication. Due to the lack of suitable routing algorithms, FANETs often encounter communication issues. This article explores the integration of Nature-inspired based routing algorithms into the FANET framework. Specifically, it examines the two distinct algorithms namely, swarm intelligence and genetic algorithms. Simulated results demonstrate the superiority of the proposed algorithm over standard benchmark schemes. Validation of the proposed algorithm using performance parameters, such as throughput, reveals significant improvements over benchmark schemes. Moreover, the packet delivery ratio for providing resources to FANET users is 98% while achieving minimum end-to-end delay for the proposed scheme. These findings underscore the potential of Nature-inspired algorithms (NIAs) across various scenarios within the FANET framework.

The study of DDPG based spatiotemporal dynamic deployment optimization of Air-Ground ad hoc network for disaster emergency response

In situations where natural disasters damage public communication networks, self-organized emergency communication networks play a vital role as important resources for disaster monitoring and emergency response. Geographical conditions, communication capacity, power availability, terminals’ position changes during disasters, and data volume, on the other hand, have a direct impact on emergency terminals’ effectiveness in disaster monitoring and data processing. As a result, the ability to detect calamities quickly and give real-time reactions suffers. To ensure effective emergency communication coverage when public networks are disrupted, intelligent, rapid and reliable optimization of the spatiotemporal dynamic deployment of Ad Hoc Network (ANET) is crucial for disaster monitoring and emergency response. The Deep Deterministic Policy Gradient (DDPG) method is used in this study to assist the spatiotemporal dynamic deployment of air-ground ANET (AGANET) nodes, including unmanned aerial vehicle (UAV) ANET nodes and ground-based ANET nodes. Its goal is to develop a reliable model for ensuring the deployment of AGANET nodes for multi-terminal disaster monitoring. The paper describes the spatiotemporal dynamic deployment of AGANET nodes and develops a reinforcement learning model. Subsequently, it describes a DDPG reinforcement-based optimization method for the spatiotemporal dynamic deployment of AGANET nodes. Specifically, this method includes a greedy matching strategy based on real-time environmental information of AGANET nodes and ground-based sensing terminals, a DDPG AGANET node three-dimensional initialization algorithm, and a DDPG dynamic solution algorithm for spatiotemporal dynamic deployment reinforcement learning model of AGANET. AGANET nodes and ground-based sensing terminals can all work together in this way to provide high-quality emergency AGANET services. When compared to traditional methods, it offers better communication dependability, enhanced efficiency, and cheaper costs associated with building emergency networks. It is also crucial for emergency response in instances where the public network fails.