Ad Hoc On-demand Distance Vector 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.

Artificial self-attention rabbits battle royale multiscale network based robust and secure data transmission in mobile Ad Hoc networks

In a Mobile Ad hoc Network (MANET), the network structure constantly evolves due to the movement of devices, users, or nodes. The Black Hole Attack (BHA) is recognized as the most impactful threat in MANETs, where an attacker node intentionally discards all data traffic, hence minimizing the network performance. Therefore, developing a secure and robust routing protocol is vital for efficient data transmission in a MANET. Although existing solutions have been designed to counteract malicious nodes, these solution presents drawbacks such as the need for additional hardware, notable delivery delays, limited throughput, increased energy consumption, and minimum packet delivery ratio. Thus, this research work introduces a new updated Ad hoc On-demand Distance Vector (AODV) routing protocol that integrates the benefits of the Artificial Rabbits Battle Royale Optimization (ARBRO), and Self-attention Multiscale Network (SMNet). The role of the ARBRO algorithm is to optimize the route by selecting the most appropriate node properties. Then, SMNet identifies the BHA node using these node properties. The proposed scheme is implemented in MATLAB. Experimental results determines that the introduced approach attains a delay of 0.039 s, a throughput of 94.57 Kbps, and a packet delivery ratio of 98.76 %, which are better than the existing techniques. Simulation results demonstrate that the introduced method improves network performance by enhancing the quality of service in the presence of a BHA.

Detection of black hole attacks in vehicle-to-vehicle communications using ad hoc networks and on demand protocols

PurposeThe potential of vehicle ad hoc networks (VANETs) to improve driver and passenger safety and security has made them a hot topic in the field of intelligent transportation systems (ITSs). VANETs have different characteristics and system architectures from mobile ad hoc networks (MANETs), with a primary focus on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. But protecting VANETs from malicious assaults is crucial because they can undermine network security and safety.Design/methodology/approachThe black hole attack is a well-known danger to VANETs. It occurs when a hostile node introduces phony routing tables into the network, potentially damaging it and interfering with communication. A safe ad hoc on-demand distance vector (AODV) routing protocol has been created in response to this issue. By adding cryptographic features for source and target node verification to the route request (RREQ) and route reply (RREP) packets, this protocol improves upon the original AODV routing system.FindingsThrough the use of cryptographic-based encryption and decryption techniques, the suggested method fortifies the VANET connection. In addition, other network metrics are taken into account to assess the effectiveness of the secure AODV routing protocol under black hole attacks, including packet loss, end-to-end latency, packet delivery ratio (PDR) and routing request overhead. Results from simulations using an NS-2.33 simulator show how well the suggested fix works to enhance system performance and lessen the effects of black hole assaults on VANETs.Originality/valueAll things considered, the safe AODV routing protocol provides a strong method for improving security and dependability in VANET systems, protecting against malevolent attacks and guaranteeing smooth communication between cars and infrastructure.

A COMPARATIVE ANALYSIS OF PROACTIVE ROUTING PROTOCOLS (DSDV, OLSR) & REACTIVE ROUTING PROTOCOLS (AODV, DSR) IN MANET USING NS-3

The abstract outlines a comprehensive analysis focusing on routing protocols in Mobile Ad Hoc Networks (MANETs). Ad-hoc networks are dynamic wireless networks without a central infrastructure. This analysis compares two types of routing protocols—proactive (table-driven) and reactive (on-demand)—using simulation analysis. The protocols DSDV, OLSR, AODV, and DSR are evaluated using NS-3, considering various performance metrics under different scenarios. The research aims to provide insights into protocol strengths and weaknesses, aiding network protocol selection and potential enhancements. This investigation contributes to understanding routing behaviours in ever-changing MANETs, benefiting network design and optimization efforts. Keywords: MANET (Mobile Ad Hoc Network), DSDV (Destination-Sequenced Distance Vector), OLSR (Optimized Link State Routing), AODV (Ad Hoc On-Demand Distance Vector), DSR (Dynamic Source Routing), Routing Information Protocol (RIP)

Trust Enabled Cluster Aware Routing Protocol Design with Energy Considerations using Fuzzy Strategies

In this modern era, wireless communication technologies are getting high impact over network industries. Due to this drastic development of communication technologies, a network needs to be more precise with certain metric such as: energy consumption, throughput, trust management, performance and lifetime. These are all the primary concern while handling the transactions with wireless communication systems. In this paper, a new approach of network routing protocol is introduced, which will replace the issues found in existing routing protocols and provide good support while communication between entities. The proposed paper introduces a new routing protocol called Modified Adhoc On-Demand Distance Vector (MAODV), in which the classic AODV protocol supports mobile nodes with several impacts such as mobility, failure prevention, loss management and so on. However, the issues in industry still remains, so, that a new approach or routing protocol is required to overcome such issues. This is the concern to develop a new routing protocol for establishing communication between mobile nodes or wireless devices. The drastic development of communication devices requires some latest technologies to provide range free communication model with the assistance of internet support. A term, 'Internet of Things (IoT)', which rules the world now-a-days through its power of connectivity and establishing the bridge between communication devices around the globe without any range restrictions. In this paper, a cluster based routing strategy is designed with the help of fuzzy assistance. The cluster based routing protocols divides the range of communication into clusters and electing the cluster head based on the communication needs and provides a range free communication model with the hands of IoT support. This cluster based routing model provides support for both inter and intra-cluster communications, which all will be brief in further sections. The proposed model of wireless communication assures the following things such as Improved Energy Efficiency, reduced packet loss and delay, improved throughput ratio and lifetime over resulting scenario with the help of a new algorithm called Fuzzy Assisted Cluster enabled Routing Model (FACeRM) with the association of new routing protocol MAODV.

Secure malicious node detection in flying ad-hoc networks using enhanced AODV algorithm

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.

Analysing the Performance of a Trust-Based AODV in the Presence of a Flooding Attack

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.

Trust based Routing – A Novel Approach for Data Security in WSN based Data Critical Applications

Wireless technology has changed the way entities communicate with one another. Wireless networks have created several opportunities in fields such as military, health care, and habitat monitoring, to name a few. However, only a few data-critical applications are built on wireless sensor networks, such as border reconnaissance, detecting infringement, and patient monitoring. These applications require the processing of a large amount of private data. Because most applications are data-sensitive, securing data transmission among wireless sensor networks is crucial. While incorporating data security, the most important requirement of wireless sensor nodes being energy optimized also need to be kept in consideration. There are various forms of assaults that are relevant in Wireless Sensor Networks (WSN). Attacks like Black Hole attacks, sink hole attacks, False data Injection attacks etc. are the most commonly seen attacks on WSNs. The common element in all these attacks is the concept of malicious / compromised node - a node which either drops / modifies the data content while forwarding it. Existing techniques for data security generally use cryptographic algorithms, but the use of cryptographic algorithms is in contrast with the energy optimization requirement of sensor nodes. An energy efficient data security scheme needs to be developed. The proposed system analyses several attacks and proposes a multi-layer data security approach to prevent change of data / dropping of data by the compromised nodes. The proposed system is a routing protocol referred as Trust Based Routing (TBR). A concept of trust value of a node is the core idea of TBR. Forwarding node is selected based on highest trust value and thus avoid malicious / compromised nodes from being involved in the routing process. The trust factor is calculated by considering the number of packets dropped, packets rejected, and the node's remaining energy. The idea of TBR is enhanced by incorporating the concept of past trust and trust of node towards a specific destination. This proposed scheme is referred as Extended Trust Based Routing (ETBR). This scheme is further enhanced by including Direct Trust, Indirect Trust and Energy Trust concepts. This scheme is referred as Consolidated Trust Estimation – Trust Based Routing (CTE-TBR). Network Simulator NS2 is used to simulate the proposed schemes. Various network factors are compared to classic Adhoc On-Demand Vector (AODV) and newly proposed schemes. The result indicates the effectiveness of the proposed data security scheme in terms of energy efficiency and Packet Delivery ratio (PDR).

Detection and prevention of sinkhole attacks in MANETS based routing protocol using hybrid AdaBoost-Random forest algorithm

WSN (Wireless Sensor Network) is considered as one of the promising technologies which are utilized in various fields for various applications. Along with it, MANET (Mobile Ad Hoc Network) has attracted a distinct attention, as they serve communication means across innumerable domain. In recent years, due to the development of both wired and wireless technologies, attacks are becoming more frequent and these attacks can be in various form such as worm hole, black hole, grey-hole, sinkhole and others. These attacks can cause loss of security, increase the number of drop packets, decrease packet delivery ratio which result in poor routing performance. In order to overcome these issues, the proposed study employs PBCS (Particle Bee Colony Swarm) algorithm for finding the shortest path between the nodes, which helps in reducing the routing cost and makes the model more efficient and effective. In addition to this, Hybrid AdaBoost-Random forest algorithm is utilized in proposed model. This model helps in reducing the training time which makes the model more reliable and efficient than existing models. It can be implemented in huge dataset and in Hybrid AdaBoost-Random Forest algorithm, estimator of random forest is used, which result in high accuracy and low loss. AODV (Ad-Hoc on Demand Vector) protocol helps to identify the prevention of attack as this routing protocol perform better for longer and extensive duration of traffic than other protocols. The performance of the proposed model is evaluated using different metrics which includes accuracy, recall, precision, sensitivity and specificity. Besides, energy consumption, throughput, network lifetime, delay of the proposed model is also evaluated. The proposed model is then compared with various existing models in order to determine the efficiency and effectiveness of the proposed framework.

IoT energy efficiency routing protocol using FHO‐based clustering and improved CSO model‐based routing in MANET

SummaryMany protocols, services, and electrical devices with built‐in sensors have been developed in response to the rapid expansion of the Internet of Things. Mobile ad hoc networks (MANETs) consist of a collection of autonomous mobile nodes that can form an ad hoc network in the absence of any pre‐existing infrastructure. System performance may suffer due to the changeable topology of MANETs. Since most mobile hosts operate on limited battery power, energy consumption poses the biggest challenge for MANETs. Both network lifetime and throughput improve when energy usage is reduced. However, existing approaches perform poorly in terms of energy efficiency. Scalability becomes a significant issue in large‐scale networks as they grow, leading to overhead associated with routing updates and maintenance that can become unmanageable. This article employs a MANET routing protocol combined with an energy conservation strategy. The clustering hierarchy is used in MANETs to maximize the network's lifespan, considering its limited energy resources. In the MANET communication process, the cluster head (CH) is selected using Fire Hawk Optimization (FHO). When choosing nodes to act as a cluster for an extended period, CH election factors in connectivity, mobility, and remaining energy. This process is achieved using an optimized version of the Ad hoc On‐Demand Distance Vector (AODV) routing protocol, utilizing Improved Chicken Swarm Optimization (ICSO). In comparison to existing protocols and optimization techniques, the proposed method offers an extended network lifespan ranging from 90 to 160 h and reduced energy consumption of 80 to 110 J, as indicated by the implementation results.

An Energy-Efficient Routing Protocol Based on Elephant Herding Optimization in MANET

Background: A mobile ad hoc network (MANET) is a collection of self-organizing mobile nodes creating an ad hoc network without fixed infrastructure. Routing is a major issue in mobile networks that may reduce network performance due to frequent network topology changes. Routing protocols are so important in dynamic multi-hop networks that many studies have focused on the routing problem in MANETs. Methods: In this research work, a proposed ad hoc on-demand distance vector (AODV) with an elephant herding optimization (EHO) called AODVEHO is used as an optimal path selection method that creates a set of best paths between destination and source. objective: The research's objectives include load balancing, minimizing latency, increasing network speed, and minimizing energy consumption. Results: To validate the performance of proposed AODVEHO, AntHocNet, AODV, and designation sequence distance vector (DSDV). Various performance measures are considered to validate our proposed research work, such as packet delivery ratio (PDR), end-to-end delay (E2ED), and average energy consumption (AEC). method: elephant herding optimization with MANET utilized to achieved a changes in network topology and circumstances, minimizing latency, increasing throughput, preserving energy, and achieving Quality of Service (QoS) standards. Conclusion: Experimental results are indicated that the AODVEHO achieved a higher routing overhead (73 %), PDR (89.87 %), low E2ED rate (95.22 %), AEC (75.60 %), and dead nodes (75%) when compared to other routing schemes. result: SI can assist in locating close to optimum routes by redefining the routing issue as an optimisation challenge. The present reserch work a novel routing approach is developed based on EHO for finding optimal path in MANET environment. Robustness of the developed ADOVEHO is compared with benchmark routing approaches such as AntHocNet[27], AODV[28] and DSDV[29] conclusion: Optimizing energy utilization in MANET is an important study topic that has recently expanded with a high concentration of advantages from swarm intelligence algorithms and their optimization capabilities. The proposed work introduces the AODVEHO energy-efficient routing algorithm, which is based on AODV and EHO. In studies, the NS-3 tool was used to create four routing protocols, including the newly designed AODVEHO in addition to the AODV protocol, AntHocNet, and DSRV. The recommended protocol outperformed the other deployed protocols, according to the results, when it comes to load balancing, as shown by its superior PDR.

ANN-Based Intelligent Secure Routing Protocol in Vehicular Ad Hoc Networks (VANETs) Using Enhanced AODV

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.

Cross-Layer Energy Efficient (CLEE) Routing Algorithm for Mobile Ad-Hoc Networks

Ad-hoc routing algorithms in Wireless Sensor Networks (WSN) rely on nodes’ position awareness by regularly updating routing data of neighbouring nodes. Meanwhile, the transmission energy usage is not optimised as a result of this repeated updates and routing table deployment. Therefore, it is very critical to consider techniques of optimising or conserving energy in the design of wireless sensor networks (WSNs) in order to prolong the lifetime of the individual nodes. One of these techniques is the Cross-layer design which, is considered as an efficient method for addressing this challenge with WSNs. In this paper, we propose a Cross-Layer Energy Efficient (CLEE) routing algorithm to establish an optimal route from the source node to the destination node by selecting candidate nodes from neighbouring nodes based on the distance between these nodes and the rate of energy consumption by a possible candidate node. Then to select a designated node from the candidate nodes, the algorithm further computes the Signal Strength Quality (SQS) and the Link Lifetime (LL) as well as the Throughput (TH) rate of selected nodes. The proposed algorithm was simulated with a network size of 600 X 600 on Network Simulator 3 (NS3) in order to analyse its performance. An evaluation of the performance of the proposed CLEE protocol with existing similar protocols such as Ad-hoc On-Demand Distance Vector (AODV) and Dynamic Source Routing (DSR) reveals that CLEE outperformes AODV and DSR by conserving about 44% of available energy.

Frozen Base Gateway Discovery Algorithm for Mobile Ad-Hock Network with Internet Connectivity Using AODV + Routing Algorithm

A mobile ad-hoc network (MANET) is a self-organized, auto-configured network and the mobile nodes have been free to move. To enable the MANET to connect to the internet it uses an intermediate bridge called a gateway. The MANET and the internet gateway is a heterogeneous network, which needs a gateway discovery. There are three types of gateway discovery mechanisms: proactive, reactive, and hybrid gateway discovery mechanism. The main challenge in the integration of the MANET and the Internet is, that there are high link disconnection results from node mobility and limited energy. In addition link disconnection, packet drop, and end-to-end delay. This study examines the impact of node mobility and energy in the frozen path from the source node to the destination node of MANET In this study, the Ad-hoc on-demand distance vector routing (AODV) routing protocol is used and modified to examine the gateway selection for MANET and the Internet. Moreover, the AODV+ control message RREQ and RREP and the routing table are improved to store the energy factor, path queue length, and frozen factor of the path. The proposed gateway discovery algorithm is known as frozen-based gateway AODV+ (F_AODV+), The stability factors of the path from the source node to the gateway, are calculated using a simple additive weighting method of the energy factor, average path queue node, and the path with the Maximum energy factor and minimum queue length is the more Frozen to select Frozen gateway from the source node to distension node.A mobile ad-hoc network (MANET) is a self-organized, auto-configured network and the mobile nodes have been free to move. To enable the MANET to connect to the internet it uses an intermediate bridge called a gateway. The MANET and the internet gateway is a heterogeneous network, which needs a gateway discovery. There are three types of gateway discovery mechanisms: proactive, reactive, and hybrid gateway discovery mechanism. The main challenge in the integration of the MANET and the Internet is, that there are high link disconnection results from node mobility and limited energy. In addition link disconnection, packet drop, and end-to-end delay. This study examines the impact of node mobility and energy in the frozen path from the source node to the destination node of MANET In this study, the Ad-hoc on-demand distance vector routing (AODV) routing protocol is used and modified to examine the gateway selection for MANET and the Internet. Moreover, the AODV+ control message RREQ and RREP and the routing table are improved to store the energy factor, path queue length, and frozen factor of the path. The proposed gateway discovery algorithm is known as frozen-based gateway AODV+ (F_AODV+), The stability factors of the path from the source node to the gateway, are calculated using a simple additive weighting method of the energy factor, average path queue node, and the path with the Maximum energy factor and minimum queue length is the more Frozen to select Frozen gateway from the source node to distension node.

Detecting Distributed Denial of Service (DDoS) in MANET Using Ad Hoc On-Demand Distance Vector (AODV) with Extra Tree Classifier (ETC)

Detecting Distributed Denial of Service (DDoS) in MANET Using Ad Hoc On-Demand Distance Vector (AODV) with Extra Tree Classifier (ETC)

Improvising QoS through Cross-Layer Optimization in MANETs

In Mobile Adhoc Networks (MANETs), nodes are mobile and interact through wireless links. Mobility is a significant advantage of MANETs. However, due to the unpredictable nature of mobility, the link may fail frequently, degrading the Quality of Service (QoS) of MANETs applications. This paper outlines a novel Ad hoc On-Demand Distance Vector with Proactive Alternate Route Discovery (AODV-PARD) routing protocol that uses signal strength-based link failure time estimation. The node predicts the link failure time and warns the upstream node through a warning message about the failure. On the basis of this information, a mechanism for identifying alternate routes is started in order to reroute traffic to the alternate route prior to the link failure. It significantly reduces packet loss and improves all the QoS parameters. The suggested protocol is compared to the traditional Ad hoc On-Demand Distance Vector (AODV) routing protocol and shows that the outlined protocol results in an improvement in QoS.

Develop a new handling method for selfish nodes in mobile ad-hoc networks

Mobile ad-hoc networks (MANETs) have been a crucial element of next-generation wireless networking technologies during the last decade. Because they allow users to access information and communicate with each other without infrastructure. Selfishness is one of the numerous undesirable behaviors that MANET network nodes may exhibit since this selfish node attempts to safeguard its own resources while accessing the services of other nodes and consuming their resources. Hence, a potential that the network's overall performance may degrade. This study developed a new method named detection, reintroduced, and collaborative of selfish node (DRCSN) that proposed detecting selfish nodes based on two factors: energy and the communication ratio (CR) and handling the rate of selfish nodes. Thus, selfish nodes were exploited to the maximum degree and significantly improve network performance. DRCSN was implemented inside ad-hoc on-demand distance vector (AODV) protocol. The test scenarios were implemented using the network simulator-2 (NS-2); many scenarios were created according to two important network parameters: the number of nodes and movement nodes. The proposed method improved the MANET's performance by increasing both the throughput and packet delivery ratio in the network in addition to that it reduced retransmission rate, delay, and power consumption compared to the related methods.

Trust-Based Routing Selection Policy on Mobile Ad-Hoc Network Using Aodv Routing Protocol

This study presents an enhanced Ad-hoc On-demand Distance Vector (AODV) routing protocol, termed Proposed_TAODV, designed to improve security in Mobile Ad-Hoc Networks (MANETs) of 150 nodes by incorporating trust-based mechanisms. Through a comprehensive simulation, the Proposed_TAODV is evaluated against existing AODV and Dynamic Source Routing (DSR) protocols under conditions of increasing malicious node presence. The results reveal that Proposed_TAODV maintains a higher Packet Delivery Ratio, experiences lower Average End-to-End Delay, and achieves greater Throughput compared to the benchmarks, indicating its superior performance and robustness. The integration of Direct Trust Evaluation, Indirect Trust Evaluation, and Trust Aggregation methods into the AODV protocol clearly enhances the MANET's resilience to security threats, establishing the Proposed_TAODV as a promising approach for securing MANETs against various forms of attacks and network disruptions.

Performance Evaluation of Routing Protocols for Vehicle Re-Routing in ITS-based Vehicular Networks

This study aims to assess the performance of routing protocols in Intelligent Transportation System (ITS)-based vehicular networks, specifically in accident and highway scenarios. The effective management of traffic flow in these situations is crucial for ensuring the safety and smooth operation of vehicular networks. Therefore, it is imperative to evaluate routing protocols to identify the most suitable one for these scenarios. The evaluation considers various commonly used routing protocols in vehicular networks, including Ad hoc On-Demand Distance Vector (AODV), Ad hoc On-Demand Multipath Distance Vector (AOMDV), and Destination-Sequenced Distance Vector (DSDV). The evaluation is based on several performance metrics, such as packet delivery ratio, end-to-end delay, network throughput, normalized routing load, and routing overhead. These metrics provide insights into the effectiveness and efficiency of the routing protocols in handling re-routing in accident and highway scenarios. The research is divided into two modules, Module I and Module II, to evaluate the effectiveness of routing protocols in these distinct scenarios using the NS2 simulation tool. The simulation results are analyzed and compared to determine the performance of the routing protocols in each module. The findings indicate that AODV consistently achieves the highest throughput, packet delivery ratio, and lowest end-to-end delay, routing overhead, and normalized routing load, followed by AOMDV and then DSDV. The findings of this study contribute to the understanding of the strengths and weaknesses of different routing protocols in accident and highway scenarios. This knowledge can assist in the development of more efficient and reliable routing protocols for vehicular networks.

Irregularity Behaviour Detection - Ad-hoc On-Demand Distance Vector Routing Protocol (IBD - AODV): A Novel Method for Determining Unusual Behaviour in Mobile Ad-hoc Networks (MANET)

All the communication in the mobile ad-hoc network (MANET) will depend on the intermediate neighbour nodes or router nodes. Routing protocol is very important in MANET, because all the communication will be done in the MANET depending on the neighbour or intermediate node. If the intermediate node is a malicious node, all the data will be lost or changed by the intermediate or malicious node. Ad-hoc On-demand Distance Vector routing protocol is one of the moderate routing protocol in MANET. The Ad-hoc On-demand Distance Vector Routing protocol does not have any security mechanism. This work is going to find the Irregularity Behaviour Detection (IBD) over the Ad-hoc On-Demand Distance Vector Routing (AODV) protocol. IBD is finding a trusted node by using the trust value (TV) of the node. This TV includes network performance, node energy level, and node position value. IBD-AODV is implemented and tested in the OmNetpp 6.0 simulator.