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Due to the high-speed mobility and restricted initial energy of nodes in mobile ad hoc networks (MANETs), the input and output rates of node data processing mismatch the data processing capabilities of nodes. In addition, the limited bandwidth of the communication paths and the insufficient path cache space can lead to the inability of fast and efficient data transmission in the networks, and even the networks can be paralyzed in the state of extreme congestion. As a common routing protocol in mobile ad hoc networks, AODV (Ad hoc On-demand Distance Vector) usually uses the minimum number of routing hops as a single metric for routing path selection, which cannot effectively determine the congestion status of nodes and data transmission paths in the networks. Based on this, this paper proposes a multi-path selection optimization algorithm based on node load states (BLS-AODV) to try to solve the problem of insufficient accuracy of path congestion state prediction that exists in AODV. The proposed algorithm takes node degree, node congestion and energy consumption as optimization indexes, and uses the minimum path congestion as the routing path selection criterion to avoid involving nodes with high congestion and high energy consumption in communication paths, thus reducing the impact of network congestion on routing performance. The simulated results show that the proposed algorithm not only effectively reduces the network overhead and delay, but also increases the data transmission success rate, thus improving the overall performance of the network. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc networks (VANETs) facilitate real-time communication between vehicles and infrastructure, but ensuring efficient and reliable communication is a challenge due to the high mobility and dynamic nature of the network. To address these challenges, we propose an intelligent routing protocol that introduces a novel clustering algorithm for selecting cluster heads (CHs). The algorithm uses a weight function that considers vehicle speed, inter-vehicle distance, and lifetime within a cluster. This selection method enhances route stability, reduces long-range communication, and significantly lowers control overhead. Moreover, we developed a new architecture for cluster management in VANETs by redefining both the election and handover processes. In this new design, we establish distinct areas and threshold distances for each stage. The election area is where the current CH crosses the election threshold distance and initiates the election process for a new CH. Once the election is completed and a new CH is selected, the handover area comes into effect. This area marks the transition point where the responsibilities of the current CH are transferred to the newly elected CH. This modification enhances cluster management, improves communication reliability, and reduces control overhead during the transition phases. Additionally, our approach integrates advanced technologies such as fog computing for enhanced location awareness and software-defined networking (SDN) for increased programmability and scalability. A dual-phase strategy is employed, with SDN handling primary packet routing and AODV serving as a fallback mechanism in case of SDN failure, ensuring robust communication under varying network conditions. We evaluated our protocol using the NS3 simulator, comparing it with five existing VANET routing protocols, that are, IDVR, VDLA, IRTIV, GPCR, and ICDRP, on key performance metrics such as throughput and end-to-end (E2E) delay. We also compared it with CBDRP, BRAVE, MoZo, CORA, and ICDRP protocols on control overhead. The results show significant improvements in network performance, and particularly, throughput increases by 22,451.8%, 176,296.2%, 191,450.2%, 255,222.7%, and 69.6%, while E2E delay decreases by 87.35%, 90.16%, 92.79%, 97.61%, and 48.50% compared to IDVR, VDLA, IRTIV, GPCR, and ICDRP, respectively. Furthermore, Hello message overhead is reduced by 99.37%, 98.68%, 97.31%, 84.36%, and 11.24%, compared to CBDRP, BRAVE, MoZo, CORA, and ICDRP, respectively, while overall control overhead improves by 29.21% compared to ICDRP. Finally, our protocol achieves a 99% SDN packet delivery ratio and an E2E delay of less than 0.15 s, demonstrating superior performance across key metrics. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc networks (VANETs) represent a critical component of intelligent transportation systems, with substantial research dedicated to developing reliable, scalable, and efficient routing protocols. The integration of the Internet of Things with VANETs significantly enhances vehicular communication, safety, and traffic management by enabling real-time data exchange and improving connectivity between vehicles and infrastructure. This paper proposes a novel protocol that integrates several key technologies, including software-defined networking (SDN), which offers scalability, programmability, and global network information, and fog computing, which supports location-based services in compliance with VANET standards. Additionally, we introduce a novel cluster head (CH) selection algorithm aimed at improving protocol efficiency. This algorithm considers three dimensions: network lifetime, average distance, and signal-to-interference noise ratio, reducing control overhead, long-distance communication, and packet loss due to collisions within clusters, respectively. The algorithm elects CHs based on a weighted value to improve network performance. Furthermore, a dual-phase strategy is implemented, where the classic AODV protocol serves as a fallback mechanism when SDN encounters complex packet processing challenges. Interestingly, we assess our protocol’s performance in terms of throughput and end-to-end delay and compare it to five closely related routing protocols, namely IDVR, VDLA, IRTIV, GPCR, and ICDRP. We consider further control overhead in the evaluation and comparisons. The comparison, in this perspective, is conducted with CBDRP, BRAVE, MoZo, CORA, and ICDRP. Our proposed protocol has produced outstanding simulation results. Specifically, across IDVR, VDLA, IRTIV, GPCR, and ICDRP, respectively, the throughput is improved by 21,969%, 172,425%, 187,727%, 249,867%, and 65.2%, respectively, while the end-to-end delay is decreased by 91.6%, 93.5%, 95%, 98%, and 14.41%, respectively. Compared to CBDRP, BRAVE, MoZo, and CORA, Hello messages are reduced by 99.5%, 98.92%, 97.81%, and 87.3%, respectively. When compared to ICDRP, our protocol control overhead messages are reduced by 21.2%. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks (MANETs) are decentralized networks of mobile devices connected by wireless links, enabling various applications across domains. Research on MANETs often relies on simulations for efficient and replicable evaluations due to the absence of central administration and complex real-world scenarios. Effective simulation necessitates the integration of mobility models to orchestrate node movement. In this study, we explore existing mobility models, propose evaluation metrics, and conduct simulations to characterize, compare, and rank these models. Additionally, we analyze ad hoc routing protocols, focusing on packet delivery ratio, average packet arrival time, and total control packets. Notable protocols such as AODV, DSR, DSDV, and TORA are scrutinized, considering factors like node count and mobility, to provide comprehensive insights into their performance and efficacy. [ABSTRACT FROM AUTHOR]

The important feature that differentiates Mobile Ad-hoc NETworks (MANETs) to other Wireless or Wired Networks is the density of the nodes and mobility. MANET is a Network without Infrastructure, in which each node acts as a data sender, sink and router. Node density and Mobility are the key features that differentiate the MANET from the other wired and wireless networks. The self-configuring infrastructures without a network of mobile devices are connected via wireless connections. Any device on the MANET network can move to any direction and it frequently changes its connections with other devices. This network is an association of wireless nodes which may be dynamically configured at any time and from any location without utilizing the network infrastructure that is already in place. In multi-hop routing mode, nodes within radio range use other nodes as relays while distant nodes communicate directly over wireless links. The density of nodes or network scalability implies the quantity of nodes in the designed network scenario. The routing protocols are therefore designed for adapting the dynamic topology change while maximize its packet delivery ratio while minimize latency and throughput, with minimal number of packet losses and average jitter. Many researchers have been done the research work on MANET Routing Protocols. In this article, four routing protocols are used for the simulated scalable ad-hoc MANET implementations. The scalability refers to the variation in the number of nodes in a designed network scenario. For this research work, four scalable networks (25, 50, 75 100) are discussed. The five performance metrics are analyzed over four categories of node densities. The experimental results show that Ad Hoc Demand Vector (AODV) is 13.65% performed well in throughput than the other protocols; Dynamic Source Routing (DSR) is 12.66% performed well in goodput; DSR is 65% performed better than other protocols in the packet received; DSR is 10.3% performed better than other protocols in the received rate. [ABSTRACT FROM AUTHOR]

The rise of autonomous vehicles necessitates advanced communication networks for effective data exchange. The routing protocols Ad hoc On-Demand Distance Vector (AODV) and Greedy Perimeter Stateless Routing (GPSR) are vital in mobile networks (MANETs) and vehicular ad hoc networks (VANETs). However, their performance is affected by changing network conditions. This study examines key routing parameters—MaxJitter, Hello/Beacon Interval, and route validity time—and their impact on AODV and GPSR performance in urban and highway scenarios. The simulation results reveal that increasing MaxJitter enhances AODV throughput by 12% in cities but decreases it by 8% on highways, while GPSR throughput declines by 15% in cities and 10% on highways. Longer Hello intervals improve AODV performance by 10% in urban settings but reduce it by 6% on highways. Extending route validity time increases GPSR's Packet Delivery Ratio (PDR) by 10% in cities, underscoring the need to optimize routing parameters for enhanced VANET performance. [ABSTRACT FROM AUTHOR]

Abstract The Flying Ad-hoc Network (FANET) can be defined as the Ad-hoc network that connects unmanned aerial vehicles flying in the space with each other and with a ground base station. However, the 3D movement of these drones with higher speeds results in a network of highly dynamic topology and intermittent connections, making the standard Ad Hoc routing protocols are not suitable for FANET. The approaches followed to address this issue include designing from scratch a routing protocol specific to FANET or modifying the existing protocols. From the view point of reliability, accuracy, and time, it is preferable to base the work on a protocol standard. But before amending the standard, tuning its performance and applying it under suitable conditions may be satisfactory for the new use. Therefore, this work considers flat FANET of fully mission-controlled drones and performs an extensive parametric simulation study to determine the best conditions and parameters’ values for applying the popular Ad Hoc On-demand Distance Vector (AODV) to it. After deducing the recommended operating environment (FAODVN-OE), some examples of amendments were suggested to further improve the performance. It was found that the modified FAODVN-OE achieves high performance compared to the default standard in terms of jitter and delay. It helped reduce jitter and delay by an average of 93.2% and 83.8%, respectively, while exhausting less energy; however the network experiences a 24.5% reduction in packet delivery ratio.

The AODV (Ad-hoc On-demand Distance Vector) scheme delivers reliable transmission in wireless ad-hoc networks, with loop-free operation, self-starting behavior, and scalability. It streamlines transmission by automatically finding the closest data receiver in an anycast group, minimizing latency. It also enhances path recovery efficiency by initiating restoration from intermediate routers along the original path. Leveraging these capabilities makes AODV highly effective for monitoring elderly patients and those with disabilities. The proposed system integrates Wireless Sensor Nodes (WSNs) to monitor the patient's position using a triaxial accelerometer for fall detection, along with ECG monitoring. These components are integrated into a ZigBee network architecture. The patient's position is relayed to nearby emergency centers via the ZigBee network, utilizing the Received Signal Strength Indicator (RSSI) parameter to identify and designate the nearest center as the destination. Experimental findings using an ARM7 Microcontroller (ARM LPC2148) with a ZigBee transceiver (CC2530) illustrate the system's effectiveness in measuring RSSI values and accurately identifying and transmitting data to the nearest emergency center, showcasing its potential for real-world healthcare monitoring application. [ABSTRACT FROM AUTHOR]

The working of a Mobile Ad hoc NETwork (MANET) relies on the supportive cooperation among the network nodes. But due to its intrinsic features, a misbehaving node can easily lead to a routing disorder. This paper presents two trust-based routing schemes, namely Trust-based Self-Detection Routing (TSDR) and Trust-based Co-operative Routing (TCOR) designed with an Ad hoc On-demand Distance Vector (AODV) protocol. The proposed work covers a wide range of security challenges, including malicious node identification and prevention, accurate trust quantification, secure trust data sharing, and trusted route maintenance. This brings a prominent solution for mitigating misbehaving nodes and establishing efficient communication in MANET. It is empirically validated based on a performance comparison with the current Evolutionary Self-Cooperative Trust (ESCT) scheme, Generalized Trust Model (GTM), and the conventional AODV protocol. The extensive simulations are conducted against three different varying network scenarios. The results affirm the improved values of eight popular performance metrics overcoming the existing routing schemes. Among the two proposed works, TCOR is more suitable for highly scalable networks; TSDR suits, however, the MANET application better with its small size. This work thus makes a significant contribution to the research community, in contrast to many previous works focusing solely on specific security aspects, and results in a trade-off in the expected values of evaluation parameters and asserts their efficiency.

The presented paper offers an in-depth look at mesh routing protocols, focusing on how well they perform under different conditions of node density and mobility. To make accurate comparisons, the study uses robust non-parametric statistical methods, including the Kruskal-Wallis, Mann-Whitney, correlation and covariance tests, to pinpoint which protocols stand out across crucial Quality of Service (QoS) metrics. These metrics cover energy consumption, end-to-end delay, packet delivery ratio, throughput, and network overhead. The research simulates several mesh network scenarios to collect important data for a comprehensive assessment of the reliability and effectiveness of each protocol. The Kruskal-Wallis test identifies large differences in performance across different circumstances. Following that, the Mann-Whitney test offers a closer look, comparing protocols in detail to identify those that work best under specific conditions. The study finds that protocol performance can vary dramatically depending on network density and how mobile the nodes are. It outlines which protocols excel in more stable setups and which remain dependable in fast-changing, dynamic networks. For network designers and operators, these insights are incredibly valuable, offering practical guidance on optimizing performance in real-world deployments. Furthermore, the research underscores why non-parametric statistical methods are so crucial. Network data often show high variability and don't always follow normal distribution patterns, making traditional parametric techniques less reliable. By choosing a more flexible and accurate approach, this study makes a meaningful contribution to wireless communication, providing a clearer picture of how different routing protocols hold up under real-world conditions. [ABSTRACT FROM AUTHOR]

In this study, we propose a novel approach to enhance the security and efficiency of Vehicular Ad-Hoc Networks (VANETs) by integrating user authentication and cluster-based routing. The proposed method is divided into two segments. The first segment focuses on user authentication using a curve fitting technique, implemented via MATLAB simulation. Nodes are randomly deployed with geostationary coordinates and node keys. These nodes are clustered based on their geographical locations, and their legitimacy is verified using curve fitting. This ensures that only authenticated nodes participate in the network, thereby enhancing security and reliability. The second segment employs a modified Ad hoc On-Demand Distance Vector (AODV) protocol for routing, adapted to the clustered network structure. Route Requests (RREQs) are sent to Zone Heads (ZH) for validation and then forwarded to Cluster Heads (CH), where idle and execution costs are calculated based on buffer states and execution capacities. The proposed method also incorporates fog computing to enable localized data processing, reducing latency and improving scalability. The performance of the proposed method was evaluated through extensive simulations, measuring key metrics such as throughput, Packet Delivery Ratio (PDR), and latency. Results show that the proposed method achieves a throughput of 8367.141811 packets per second, a PDR of 0.83336875, and a latency of 6.606503751 seconds, outperforming state-of-the-art algorithms by significant margins. Specifically, the proposed method demonstrates a 7.5% improvement in throughput over Khudhair et al. and a 12.9% improvement over Ahmad et al. In terms of PDR, it shows an 8.8% increase over Khudhair et al. and a 7.1% increase over Ahmad et al. The latency reduction compared to these algorithms is 9.1% and 10.5%, respectively. These enhancements are attributed to the efficient clustering and authentication mechanisms, along with the integration of fog computing. The proposed method thus provides a comprehensive solution for secure and efficient VANET communication, paving the way for advanced intelligent transportation systems. [ABSTRACT FROM AUTHOR]

Recently, there has been a focus on the significance of swarm intelligenceinspired routing algorithms for achieving optimum solutions in biologically inspired wireless sensor networks (WSNs). These protocols depict a network of wireless mobile nodes forming an infrastructure that is agile, dynamic, and independent of a central administrative facility. Among the challenges faced by bio-inspired WSNs, mobility awareness and excessive energy consumption (EC) stand out as significant hurdles, particularly in dynamic models with intermittent connections. This project seeks to tackle these obstacles by deploying the hybrid energy efficiency (HEED) approach to distributed clustering for network system cluster formation, along with fusion routing protocol of particle swarm optimization (PSO) and PIO to select cluster-heads and optimize solutions in bio-inspired WSNs. The success of the suggested approach is assessed using a variety of criteria, such as energy usage, rate of packet delivery, EC, and routing overhead and network lifetime. The methods like ad hoc on-demand distance vector's (AODV) and ant colony optimization (ACO) methods are employed in the testing and validation. In comparison to the reactive AODV routing protocol and ACO, the suggested routing protocol (HPSOPIO) reduces energy usage and increases network lifespan. [ABSTRACT FROM AUTHOR]

The conventional clustering and routing approaches used in mobile ad hoc networks (MANETs) may fail to work effectively in a dynamic network environment where nodes are highly mobile and the traffic load may also vary significantly. These limitations result in negative effects such as high packet drop rates, delays in data transmission, and low delivery rates, which make these methods unfit for modern high-density networks. To overcome these issues, this paper proposes a new deep learning-based classifier for adaptive clustering in MANETs. Through the use of machine learning algorithms, the proposed method is able to adapt to node clustering through node behavior, mobility, and content distribution in real-time, thus improving network performance. This work compares the performance of the network on networks that contain 50, 100, and 200 nodes via a clustering algorithm. The performance parameters considered include the delivery ratio, packet drop ratio, and end-to-end delay. The evaluation findings show that the developed deep learning-based classifier is far more effective than the non-clustered and conventional clustering approaches are. In particular, the classifier approach provides a delivery rate of up to 89.4%, which is significantly better than that of the baseline scenarios and decreases packet drop rates by more than 70%, especially in high-density node scenarios. In addition, the proposed approach reduces the network delay and effectively handles the inherent dynamic characteristics of MANETs. [ABSTRACT FROM AUTHOR]

As a result of recent advancements in electronics technology, wireless sensor networks (WSNs) may now make use of a vast array of tiny sensors (WSN). WSN are viewed as problematic networks because of the environments in which they may operate and the technology they rely on. For instance, routing protocols need to be prepared for and capable of recovering from unexpected events like node failures and packet losses. The dynamic nature of these routing environments necessitates that every WSN routing protocol have mechanisms for adapting to new conditions. In many applications, security affects performance and energy efficiency. To provide such security services, we require resilient key management techniques. Security Power Aware Routing-Salp Swarm Optimization (SPAR-SSO) protocol uses a unique cryptosystem. SPAR-SSO uses connection quality estimation and power aware routing to reduce power consumption and delay while increasing packet delivery ratio. WSNs must conserve energy because the nodes are battery-powered. If the route with the greatest energy savings is constantly chosen for delivery, the nodes along this route will be overused and drained quickly, leading to network partitioning. In SPAR-SSO, an optimal path to the sink node is chosen. This technology is interesting because to its ease in enterprise and tractability in network transportation administration to deliver integrated services. It delivers a collision-free medium and minimizes entire energy expended in attainment the terminus, dropping energy each unit or packet. Moreover, Salp Swarm Optimization (SSO) is applied to optimize the results. The Packet Delivery Ratio (PDR) and End to End Delay is used as parameters to compare the performance of SPAR-SSO protocol. The results are compared with existing results and presented the success of the proposed method. Results show the proposed algorithm is suitable and compatibility with cyber-physical systems. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc network (VANET) is one of the challenging research areas in recent times with applications to intelligent traffic systems. In VANET, the link between vehicles going in opposite directions only lasts for a very short time when they are within range of each other, otherwise lost, hindering the complete exchange of meaningful information. Most valuable applications on VANET are related to safety-related applications that require real-time response. If the safety and the real-time requirements are not met, serious consequences may result in the form of traffic accidents or failed rescue operations. Flooding attacks on route request packet (RREQ) disrupt the communication between parties, reduce the successful packet delivery rate, and introduce excessive packet transmission delays. This type of attacks, when executed over VANET, may result in disastrous consequences for critical applications such as collision warning or autonomous vehicle assistance. Many security solutions have been proposed; however, they all have several limitations: either they fail to recognise malicious nodes when they attack with low frequency rates, or they suffer performance degradation because of the burden of add-on security measures by the solutions even when malicious nodes are not present in the environment. This paper proposes a Median Filter based flooding attacks detection algorithm (MFFDA) that enables efficient and reliable operation on VANET. The MFFDA solution is novel in three aspects: (1) it uses a route discovery frequency vector (V) to capture a node's behavioral history; (2) it uses a nonlinear mapping to transform the representational space V into a new space VMF through the use of a Median Filter; (3) it utilises a robust statistic-the median value (mv)—of the data sample V and a suitable separating hyperplane to detect malicious nodes. The paper also proposes the Flooding Attacks Prevention and Detection Routing Protocol (FAPDRP), that incorporates the proposed MFFDA for routing protection. Using NS2, the paper simulated the FAPDRP and related protocols in both attacked and normal network scenarios. The results show that the proposed solution has an accuracy over 98.5% under the minimal flooding attacks 10 pkt/s, outperforms those of previous studies. In addition, the performance of FAPDRP approaches that of the AODV in both attacked and normal network scenarios. This confirms that the proposed MFFDA satisfies the delay, efficiency, and reliability constraints for VANET environment. [ABSTRACT FROM AUTHOR]

Enhancing the security of Wireless Sensor Networks (WSNs) improves the usability of their applications. Therefore, finding solutions to various attacks, such as the blackhole attack, is crucial for the success of WSN applications. This paper proposes an enhanced version of the AODV (Ad Hoc On-Demand Distance Vector) protocol capable of detecting blackholes and malfunctioning benign nodes in WSNs, thereby avoiding them when delivering packets. The proposed version employs a network-based reputation system to select the best and most secure path to a destination. To achieve this goal, the proposed version utilizes the Watchdogs/Pathrater mechanisms in AODV to gather and broadcast reputations to all network nodes to build the network-based reputation system. To minimize the network overhead of the proposed approach, the paper uses reputation aggregator nodes only for forwarding reputation tables. Moreover, to reduce the overhead of updating reputation tables, the paper proposes three mechanisms, which are the prompt broadcast, the regular broadcast, and the light broadcast approaches. The proposed enhanced version has been designed to perform effectively in dynamic environments such as mobile WSNs where nodes, including blackholes, move continuously, which is considered a challenge for other protocols. Using the proposed enhanced protocol, a node evaluates the security of different routes to a destination and can select the most secure routing path. The paper provides an algorithm that explains the proposed protocol in detail and demonstrates a case study that shows the operations of calculating and updating reputation values when nodes move across different zones. Furthermore, the paper discusses the proposed approach's overhead analysis to prove the proposed enhancement's correctness and applicability. [ABSTRACT FROM AUTHOR]

A mobile ad-hoc network (MANET) is a network of mobile nodes that dynamically form a transitory network lacking any existence of infrastructure and any form of centralized management. Nodes in ad hoc networks are powered by batteries with a limited lifespan and communicate in a restricted bandwidth. The unpredictable environment of a MANET may run into a major concern in the routing mechanism, therefore the need for a routing protocol with robust performance is still one of the key challenges in MANET deployment. In this work, a comparative comparison and extensive simulation analysis have been carried out for three major routing protocols: destination sequenced distance vector (DSDV), dynamic source routing (DSR) and ad hoc on-demand distance vector (AODV). Protocol evaluation has been extended by considering several simulation arrangements, different classes of traffic load patterns and diverse performance metrics. Based on packet rate change, node quantity and node speed, simulation scenarios were generated. Protocols were investigated against energy consumption, throughput, lost packets, routing load and packet delivery fraction for three types of traffic load patterns regular, irregular and joint traffic. DSR and AODV protocols proved to be more reliable when joint traffic was implemented when node speed and packets variations are considered. DSDV protocol verifies outstanding response over other protocols in terms of energy consumption when either regular or irregular traffic is applied. The simulation results for DSR protocol have verified the superiority over other protocols in 9 simulation scenarios when diverse metrics are considered. DSDV showed optimal performance in 7 cases, especially at low packet rates and in networks with minimum number of nodes. Similarly, AODV protocol showed outstanding performance in 6 scenarios, when higher packet rates and node mobility are considered. [ABSTRACT FROM AUTHOR]

Abstract In wireless networking, the security of flying ad hoc networks (FANETs) is a major issue, and the use of drones is growing every day. A distributed network is created by a drone network in which nodes can enter and exit the network at any time. Because malicious nodes generate bogus identifiers, FANET is unstable. In this research study, we proposed a threat detection method for detecting malicious nodes in the network. The proposed method is found to be most effective compared to other methods. Malicious nodes fill the network with false information, thereby reducing network performance. The secure ad hoc on-demand distance vector (AODV) that has been suggested algorithm is used for detecting and isolating a malicious node in FANET. In addition, because temporary flying nodes are vulnerable to attacks, trust models based on direct or indirect reliability similar to trusted neighbors have been incorporated to overcome the vulnerability of malicious/selfish harassment. A node belonging to the malicious node class is disconnected from the network and is not used to forward or forward another message. The FANET security performance is measured by throughput, packet loss and routing overhead with the conventional algorithms of AODV (TAODV) and reliable AODV secure AODV power consumption decreased by 16.5%, efficiency increased by 7.4%, and packet delivery rate decreased by 9.1% when compared to the second ranking method. Reduced packet losses and routing expenses by 9.4%. In general, the results demonstrate that, in terms of energy consumption, throughput, delivered packet rate, the number of lost packets, and routing overhead, the proposed secure AODV algorithm performs better than the most recent, cutting-edge algorithms.

The rise of autonomous vehicles necessitates advanced communication networks for effective data exchange. The routing protocols Ad hoc On-Demand Distance Vector (AODV) and Greedy Perimeter Stateless Routing (GPSR) are vital in mobile networks (MANETs) and vehicular ad hoc networks (VANETs). However, their performance is affected by changing network conditions. This study examines key routing parameters—MaxJitter, Hello/Beacon Interval, and route validity time—and their impact on AODV and GPSR performance in urban and highway scenarios. The simulation results reveal that increasing MaxJitter enhances AODV throughput by 12% in cities but decreases it by 8% on highways, while GPSR throughput declines by 15% in cities and 10% on highways. Longer Hello intervals improve AODV performance by 10% in urban settings but reduce it by 6% on highways. Extending route validity time increases GPSR’s Packet Delivery Ratio (PDR) by 10% in cities, underscoring the need to optimize routing parameters for enhanced VANET performance.

In modern communication systems, wireless ad hoc networks are essential in which network lifetime and performance depend heavily on the energy economy. However, an energyefficient protocol is necessary since ad hoc network nodes run on limited battery power and it is impractical to replace or recharge the battery crucial to the ad hoc network's design. In ad hoc networks, the shortest path is always chosen by traditional routing techniques. Ad hoc networks will divide if energy consumption isn't taken into account, as some nodes will quickly run out of power. This work offers a thorough analysis of the energy consumption features of well-known routing methods in wireless ad hoc networks. Also, a new protocol Enhanced Energy Aware Multipath Routing Protocol (EEAMRP) is proposed. EEAMRP takes multipath selection into account to reduce the energy consumption. Number of simulations are carried out over a range of network situations, including different topologies, node configurations, mobility models, and traffic patterns, using Network Simulator 2 (NS2). Enhancing routing protocols to increase the lifetime of ad hoc networks has been a busy field of study in recent years. This work's major objective is to assess each protocol's energy efficiency using important performance indicators such as transmission energy, idle energy, receiving energy, node lifetime, and remaining energy. EEAMRP, in particular, performs better than AODV, DSR, and DSDV in terms of transmission energy, idle energy, and receiving energy. By utilizing energy-aware methods and multipath routing, EEAMRP minimises energy consumption through route selection, improving network efficiency and extending node lifetime. Moreover, EEAMRP distributes traffic load efficiently to reduce congestion and energy consumption by dynamically choosing several disjoint pathways between source and destination nodes. This work examines the functionality of three well-known protocols: Dynamic Source Routing (DSR), Ad hoc OnDemand Distance Vector (AODV), and Destination-Sequenced Distance Vector (DSDV), in comparison to the novel Enhanced Energy-Aware Multipath Routing Protocol (EEAMRP). Through meticulous analysis, EEAMRP emerges as a standout performer, showcasing superior energy efficiency. Its adeptness in maximizing the lifespan of ad-hoc networks signifies a promising advancement in the realm of wireless communication protocols. [ABSTRACT FROM AUTHOR]

The primary goal of this study is to investigate and evaluate the performance of wireless Ad-Hoc routing protocols using the OPNET simulation tool, as well as to recommend the most effective routing strategies for the wireless mesh environment. Investigations have been testified to analyze the performance of the reactive and proactive Ad-Hoc routing protocols in different scenarios. Application and wireless metrics were configured that were used to test and evaluate the performance of routing protocols. The application metric includes web browsing metrics such as HTTP page response time, voice and video metrics such as end-to-end delay, and delay variation. The wireless network metrics include wireless media access delay, data dropped, wireless load, wireless retransmission attempts, and Packet Delivery Ratio. The simulations results show that the AODV overcome DSR and OLSR in terms of PDR (76%), wireless load (22.692 Mbps), voice delay variation (102.685 ms), HTTP page response time (15.317 sec), voice and video packet end-to-end delay (206.527 and 25.294 ms), wireless media access delay (90.150 ms), data dropped (10.003 Mbps), wireless load (22.692 Mbps), and wireless retransmission attempts (0.392 packets). [ABSTRACT FROM AUTHOR]

Vehicular Ad hoc Networks (VANETs) have become prominent in the past few years for the transportation sector. Vehicular mobility poses a significant challenge for establishing private communications in VANETs. The classical Ad hoc On-Demand Distance Vector (AODV) routing protocol used in VANET assumes that all nodes are non-malicious. To address this matter, this paper proposes making AODV routing protocols more secure by using a privacy scheme in AODV for vehicle-to-vehicle communication. The AODV privacy scheme tries to keep the automobile network connected reliably and stably during communication with the secured transmission of messages and minimize the risk of unauthorized access to sensitive information from eavesdropper attacks. The proposed privacy secure AODV routing named PSAODV used pseudonym changes in vehicle communication to hide the target vehicle's location. A VANET simulator based on OMNET++ and SUMO are used for evaluating the PSAODV routing protocol. A simulation study was conducted that compared the PSAODV with SE-AOMDV, ECC-AODV, and AODV in fundamentals of efficiency and confidentiality. The analysis results showed that PSAODV routing demonstrates routing efficiency with privacy by diminishing the effect of eavesdropping of vehicles information based on various scenarios in urban cities. [ABSTRACT FROM AUTHOR]

Routing protocol plays a vital role in FANETs (Flying Ad-Hoc Networks) by facilitating communication between nodes and enabling the establishment of efficient routes. In a FANET, where the nodes can be drones, airplanes or other unmanned aerial vehicles, mobility is a key aspect that requires proper route management. Among the most well-known and widely used routing protocols in different types of networks is AODV (Ad hoc On-Demand Distance Vector). AODV is a reactive routing protocol specially designed for ad hoc networks, including FANET networks. It offers an efficient solution to establish dynamic routes between nodes when direct communication between a source node and the destination node is not possible. However, most of the studies available in the literature mainly focus on the comparison between different routing protocols. They often neglect to examine in detail the performance of the same routing protocol under different circumstances or conditions. This paper offers a thorough investigation into the influence of noise on the AODV protocol in FANET networks. Furthermore, we introduce a proposed enhancement to the AODV protocol, specifically designed to improve its ability to withstand the effects of noise. Additionally, we present simulation results that evaluate the performance of AODV in terms of throughput, End-to-End Delay, Packet Delivery Ratio (PDR), and energy consumption. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks (MANETs) are wireless multi-hop networks that do not rely on any fixed infrastructure, unlike traditional networks. Nodes in MANETs are formed dynamically and are free to move in any direction at variable speeds. The special characteristics of MANETs make them vulnerable to flooding attacks, which can have a negative impact on their performance. Moreover, due to their nature, employing solutions designed for traditional networks is not feasible. One potential solution to enhance the performance of MANETs in the face of network attacks is to implement trust management. This paper evaluates the performance of Ad hoc On-Demand Distance Vector (AODV) Routing in the presence of a flooding attack. We propose a direct trust management scheme to detect and isolate malicious nodes and implement this scheme on AODV. We name the modified protocol Trusted AODV (TAODV) and, finally, compare the performance of AODV and TAODV when both are under a flooding attack to measure the improvement achieved by our suggested scheme. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks (MANETs), which correspond to a novel wireless technology, are widely used in Internet of Things (IoT) systems such as drones, wireless sensor networks, and military or disaster relief communication. From the perspective of communication and data collection, the success rate of collaborations between nodes in mobile ad hoc networks and reliability of data collection mainly depend on whether the nodes in the network operate normally, namely, according to the established network rules. However, mobile ad hoc networks are vulnerable to attacks targeting transmission channels and nodes owing to their dynamic evolution, openness, and distributed characteristics. Therefore, during the network operation, it is necessary to classify and detect the behavior and characteristics of each node. However, most existing research only analyzes and considers responses against a single or small number of attacks. To address these issues, this article first systematically analyzed and classified common active attacks in MANETs. Then, a node trust model was proposed based on the characteristics of various attacks; subsequently, a new secure routing protocol, namely, TC-AODV, was proposed. This protocol has minimal effect on the original communication dynamics and can effectively deal with Packet drop, wormhole, Session hijacking, and other main attacks in MANETs. The NS3 simulation results show that the proposed routing protocol attains good transmission performance, can effectively identify various attacks and bypass malicious nodes, and securely complete the communication process.

Di era Internet of Things (IoT) yang semakin berkembang, Wireless Sensor Network (WSN) berperan penting dalam menghubungkan perangkat, memfasilitasi pertukaran data, dan menghemat sumber daya. Namun, WSN masih menghadapi tantangan operasional, seperti pengumpulan data sensor yang luas, operasional dengan energi terbatas, dan adaptasi dengan dinamika lingkungan yang berubah. Penelitian ini mengkaji implementasi protokol Ad hoc On-Demand Distance Vector (AODV) bersama ESP-NOW pada mikrokontroler ESP32, dengan tujuan utama meningkatkan efisiensi operasional WSN. Metode pengujian yang digunakan melibatkan pengujian dalam berbagai kondisi WSN, baik untuk node statis maupun dinamis, di lingkungan dengan dan tanpa hambatan fisik, untuk mengevaluasi kinerja AODV secara menyeluruh. Hasil pengujian menunjukkan tingkat keberhasilan komunikasi antar-node sebesar 86,6%, menandakan potensi signifikan dari integrasi ESP32 dan ESP-NOW dalam implementasi AODV di WSN. Penelitian ini penting karena membantu dalam mengatasi tantangan operasional dalam Wireless Sensor Network (WSN) yang merupakan bagian integral dari IoT, dan kontribusinya terletak pada pengembangan dan implementasi protokol AODV dengan ESP-NOW pada ESP32, yang berpotensi meningkatkan efisiensi dan adaptabilitas WSN, sehingga mendukung perkembangan dan peningkatan aplikasi IoT di masa depan. Abstract In the rapidly evolving era of the Internet of Things (IoT), Wireless Sensor Networks (WSN) play a crucial role in connecting devices, facilitating data exchange, and conserving resources. However, WSNs continue to face operational challenges, such as extensive sensor data collection, limited energy operation, and adaptation to changing environmental dynamics. This study examines the implementation of the Ad hoc On-Demand Distance Vector (AODV) protocol in conjunction with ESP-NOW on the ESP32 microcontroller, primarily aiming to enhance the operational efficiency of WSNs. The testing methodology employed involves trials under various WSN conditions, for both static and dynamic nodes, in environments with and without physical obstacles, to comprehensively evaluate the performance of AODV. The results show a successful inter-node communication rate of 86.6%, indicating the significant potential of integrating ESP32 and ESP-NOW in the AODV implementation within WSNs. This research is important as it helps in addressing the operational challenges in Wireless Sensor Networks (WSN), which are an integral part of IoT, and its contribution lies in the development and implementation of the AODV protocol with ESP-NOW on ESP32, which has the potential to enhance the efficiency and adaptability of WSNs, thereby supporting the development and improvement of IoT applications in the future.

A vehicular ad hoc network (VANET) is a sophisticated wireless communication infrastructure incorporating centralized and decentralized control mechanisms, orchestrating seamless data exchange among vehicles. This intricate communication system relies on the advanced capabilities of 5G connectivity, employing specialized topological arrangements to enhance data packet transmission. These vehicles communicate amongst themselves and establish connections with roadside units (RSUs). In the dynamic landscape of vehicular communication, disruptions, especially in scenarios involving high-speed vehicles, pose challenges. A notable concern is the emergence of black hole attacks, where a vehicle acts maliciously, obstructing the forwarding of data packets to subsequent vehicles, thereby compromising the secure dissemination of content within the VANET. We present an intelligent cluster-based routing protocol to mitigate these challenges in VANET routing. The system operates through two pivotal phases: first, utilizing an artificial neural network (ANN) model to detect malicious nodes, and second, establishing clusters via enhanced clustering algorithms with appointed cluster heads (CH) for each cluster. Subsequently, an optimal path for data transmission is predicted, aiming to minimize packet transmission delays. Our approach integrates a modified ad hoc on-demand distance vector (AODV) protocol for on-demand route discovery and optimal path selection, enhancing request and reply (RREQ and RREP) protocols. Evaluation of routing performance involves the BHT dataset, leveraging the ANN classifier to compute accuracy, precision, recall, F1 score, and loss. The NS-2.33 simulator facilitates the assessment of end-to-end delay, network throughput, and hop count during the path prediction phase. Remarkably, our methodology achieves 98.97% accuracy in detecting black hole attacks through the ANN classification model, outperforming existing techniques across various network routing parameters. [ABSTRACT FROM AUTHOR]

In the process of data transmission in mobile ad hoc networks, it is essential to establish optimal routes from source nodes to destination nodes. However, as network density increases, this process is often accompanied by a significant rise in network overhead. To address this issue, the ND-AODV (neighborhood density AODV) protocol has been introduced, which reduces the probability of transmitting control information in high-density node environments to mitigate network overhead. Nevertheless, this may come at the cost of reduced routing accuracy, potentially leading to unnecessary resource wastage in certain scenarios. Furthermore, ND-AODV does not comprehensively consider the location of the receiving nodes, which limits its ability to reduce network overhead effectively. To overcome these limitations, this paper introduces a novel routing approach, known as CND-AODV (common neighborhood density AODV). In comparison to ND-AODV, CND-AODV offers a more comprehensive solution to the challenges posed by high-density network environments. It intelligently processes control information based on the special positioning of the receiving nodes, thereby significantly reducing unnecessary network overhead. Through simulation experiments comparing performance metrics such as throughput, packet delivery rate, and latency, the results clearly indicate that CND-AODV substantially decreases network overhead, enhancing network performance. Compared to ND-AODV, this innovative routing approach exhibits significant advantages. It provides a more efficient and reliable solution for ad hoc networks in high-density environments. [ABSTRACT FROM AUTHOR]

Generally, a wireless sensor network (WSN) is made up of autonomous devices that are spatially distributed and use sensors to monitor environmental conditions. Due to some of the diverse applications, such as healthcare monitoring, management of disasters, smartphones, military, and other systems of surveillance, deployment of sensor nodes is more which are independent and distributed in harsh environments. Clustering stabilizes the network and gives the maximum efficiency of energy where sensor nodes are grouped into clusters that give preservation of energy. The proposed work is mainly on a heterogeneous wireless sensor network (HWSN) which has various levels of energy developed to overcome some of the issues. Many protocols have been developed and designed for enhancing the performance of HWSN. The proposed work presents a model with the concept of Improved-Multiple Input Multiple Output (IMIMO) which provides secured routing against attacks. The research work is focused mainly on the detection and prevention of black hole attacks using an algorithm called Modified Back Propagation Neural Network (Modified-BPNN). Considering the previous research, the objective is to provide secure routing and increase network performance. The modified-BPNN algorithm reconstructs the network by eliminating the malicious nodes which disturb the network operation. The proposed algorithm works better for data transmission with secured routes and also network performance is achieved by expanding the MAC parameters. Throughput, Packet Delivery Ratio (PDR), Packet Loss, and Routing Overhead are evaluated using NS 2.35 simulator tool and compared with the existing Protocols such as DSR, AODV, and MAODV. [ABSTRACT FROM AUTHOR]