Demand Distance Vector Research Articles

Energy and Mobility Models based Performance Evaluation in MANET

Mobile ad hoc networks are constituted with randomly moving nodes and movement of these nodes is depended upon moving model used in the network. Performance of the network directly depends on the movements and energy consumed in a specific time period by the nodes. Also performance of the protocol used for communication depends on the type of mobility model used by that specific protocol. In this paper, performance of AODV (Ad hoc On demand Distance Vector) routing protocol have been evaluated in respect of five mobility models Random Way Point Mobility Model, Manhattan Grid Mobility Model, Gauss Markov Mobility Model, Random Direction Mobility Model, RPGM (Reference Point Group Mobility)). Performance metrics are considered as: average energy consumption and average residual energy. By varying the network connections, speed of the nodes, and node densities, in different scenarios, routing protocol has been simulated in network simulator 2. Simulation results show that reference point group mobility model is best suitable model as compared to other mobility models for AODV protocol in terms of energy consumption.

EOEEORFP: Eagle Optimized Energy Efficient Optimal Route-Finding Protocol for Secure Data Transmission in FANETs

This FANETs (Flying Adhoc NETworks) are supported by UAVs (Unmanned Aerial Vehicles) which carry out the task of transmitting and receiving data. Transmission and routing are complicated by the highly mobile AUVs. Node links are temporary and may result in transmission related issues. FANETs are prone to network attacks, especially black hole attacks leading to heavy data loss. This may lead to packet drops which might compromise the transmitted data. The proposed Eagle Optimized Energy Efficient Optimal Route-Finding Protocol (EOEEORFP) selects an efficient route towards the destination. Factors like trust degree, priority queue, network delay, hop count and energy consumption levels are taken into consideration in designing the routing strategy. These factors help in identifying the nodes that form the trusted nodes in the routing path. This is achieved by employing the biological behavior of eagles in finding their prey. The suggested protocol works in two stages. In the initial stage, it sets up an optimal route with selective nodes (trusted nodes). In the second stage, the network security is fortified by eradicating black hole attacks by using RREP (Route Reply) packets strategically. The EOEEORFP protocol assures the successful data delivery by employing a trusted routing path. The proposed EOEEORFP protocol is assessed against Adhoc On demand Distance Vector (AODV) and AODV-V2 protocols to measure its performance. EOEEORFP achieves very good PDR and throughput while conserving the network energy by minimizing the network delay.

Incremental Online Machine Learning for Detecting Malicious Nodes in Vehicular Communications Using Real-Time Monitoring

Detecting malicious activities in Vehicular Ad hoc Networks (VANETs) is an important research field as it can prevent serious damage within the network and enhance security and privacy. In this regard, a number of approaches based on machine learning (ML) algorithms have been proposed. However, they encounter several challenges due to data being constantly generated over time; this can impact the performance of models trained on fixed datasets as well as cause the need for real-time data analysis to obtain timely responses to potential threats in the network. Therefore, it is crucial for machine learning models to learn and improve their predictions or decisions in real time as new data become available. In this paper, we propose a new approach for attack detection in VANETs based on incremental online machine learning. This approach uses data collected from the monitoring of the VANET nodes’ behavior in real time and trains an online model using incremental online learning algorithms. More specifically, this research addresses the detection of black hole attacks that pose a significant threat to the Ad hoc On Demand Distance Vector (AODV) routing protocol. The data used for attack detection are gathered from simulating realistic VANET scenarios using the well-known simulators Simulation of Urban Mobility (SUMO) and Network Simulator (NS-3). Further, key features which are relevant in capturing the behavior of VANET nodes under black hole attack are monitored over time. The performance of two online incremental classifiers, Adaptive Random Forest (ARF) and K-Nearest Neighbors (KNN), are assessed in terms of Accuracy, Recall, Precision, and F1-score metrics, as well as training and testing time. The results show that ARF can be successfully applied to classify and detect black hole nodes in VANETs. ARF outperformed KNN in all performance measures but required more time to train and test compared to KNN. Our findings indicate that incremental online learning, which enables continuous and real-time learning, can be a potential method for identifying attacks in VANETs.

Modelling and modular supervisory control for the AODV routing protocol

The model of the Ad-hoc on Demand Distance Vector (AODV) routing protocol, being favorable in several wireless networks (Vehicular Ad-Hoc Networks (VANET), ZigBee etc.) is presented for a network with parametric number of nodes in the Ramadge Wonham (RW) framework of discrete event systems (DES). For a generic network, consisting of n nodes, the first goal is to introduce two specification rules, per node. The first rule guarantees the hierarchy of the requests of the nodes and the routing paths. The second rule offers a first level security regarding requests’ replies. The two rules are expressed as two regular languages. Each regular language is realized by a supervisor automaton. The two supervisor automata of each node compose the local controllers of a distributed supervisory control architecture controlling the total network. The physical realizability of the local controlled automaton is proved. Also, the nonblocking property and the satisfactory marked behavior of the total controlled automaton are proved. The complexity of the proposed distributed architecture is computed. To illustrate the effectiveness of the present control scheme, a four-node network simulation of the controlled automaton of the protocol is presented.

Quad-Interleaving Routing Algorithm for Performance Enhancement of Oil and Gas Pipeline Network Monitoring

The pipeline is one of the main modes oftransportation for the oil and gas industry that could be laid offshore and onshore. Pipeline transportation requires close monitoring as a failure in pipelines causes disruption of supply, loss of precious commodities and not to mention irreversible environmental damage will be an essential topic. The major issue in AODV and DSDV is when the network gets more extensive, which causes high packet traffic resulting in high packet loss, energy consumption and passive nodes. This research aims to establish a routing algorithm with better performance focusing on throughput, fairness index, delivery ratio and passive nodes and energy consumption. The study is confined to wireless sensor network simulation on Network Simulator Tool. A technique of quad-interleaving Ad-hoc On- demand Distance Vector (QAODV) routing algorithm has been developed where predefined Alpha, Beta, Charlie and Delta nodes will communicate with the nodes which belong to their family. The results of the developed routing protocol have been compared with standard AODV, DSDV and OLSR routing protocols. The developed routing algorithm has produced a massive improvement in the delivery ratio (25% more), throughput (44% more), passive nodes (71 less), fairness index (0.06 more) and energy consumption (0.22J less).

INFLUENCE WITH TRAFFIC RATE AND BEACON TIME FOR JAMMING ATTACK ON 802.11B IN MOBILE AD HOC NETWORKS

MANETs have distinctive characteristics like dynamic topology, wireless radio medium, restricted resources and lack of centralized administration; as a result, they're liable to differing types of attacks in several layers of protocol stack. Every node in a Manet is capable of acting as a router. The need for a secure Manet networks is powerfully tied to the protection and privacy options. This Jamming attacks are one in every of them. These occur by transmittal continuous radio ways in which to inhibit the transmission among sender and receiver. These attacks have an effect on the network by decreasing the network performance with buffer size, beacon amount varied as certained result on mobile ad-hoc network degrade the performance with Jamming attack. This work includes a network with high Mobility IEEE 802.11b with improved AODV (Ad hoc On Demand Distance Vector) routing protocol parameters. FTP with high rate is being generated within the network. For the Simulation purpose we tend to utilized OPNET (Optimized Network Engineering Tool) MODELER 14.5 is employed for simulation. The performance of network is measured with relation to the QoS parameters.

Secure and Light Weight Aodv (Slw-Aodv) Routing Protocol for Resilience Against Blackhole Attack in Manets

This paper aimed at the detection of blackhole attacks and proposed a new method called as Secure and Light Weight Adhoc On demand Distance Vector Routing (SLW-AODV). SLW-AODV is an extended version of the traditional AODV routing protocol. The proposed SLW-AODV ensures resilience for both blackhole and cooperative blackhole attacks. It employs a simple Challenge, Response and Confirm (CRC) strategy with chaotic maps for the identification of both blackhole and cooperative blackhole attacks. SLW-AODV identifies the attacked nodes at both route discovery and data forwarding process. For experimental validation, we have conducted extensive simulations and the performance is validated through Packet Delivery Ratio, Throughput and Average end-to-end delay. The obtained performance metrics shows an outstanding performance than the state-of-the art methods.

Neighbour Node Ratio AODV (NNR-AODV) Routing Protocol for Wormhole Attack Detection in Manets

This paper aimed at the detection of wormhole attack and proposed a new method called as Neighbour Node Ratio Adhoc On demand Distance Vector Routing (NNR-AODV). NNR-AODV is an extended version of the traditional AODV routing protocol. The proposed NNR-AODV calculates the neighbour node count for every node and based on that it will decide whether the wormhole is present or not. Furthermore, NNR-AODV is able to detect both external and internal wormhole attacked nodes. Also, NNR-AODV derived a Neighbor node Threshold value which is based on the cumulative distances between nodes present in the wormhole attack. For experimental validation, we have accomplished an extensive simulation and the performance is measured through Number of bogus links, Detection rate, False positive Rate, Packet delivery ratio and Packet loss ratio. The obtained results have shown superior performance in the detection of wormhole attacks than the existing methods.

Black‐hole attack and counter measure in ad hoc networks using traditional routing optimization

SummaryAd hoc networks have constraints like energy, memory, computation power, and communication range which makes the nodes vulnerable for attacks. In this article, black hole attack detection mechanism is carried out on traditional ad hoc on demand distance vector routing (AODV) protocol. Initially the proposed work proceeded with black‐hole attack configured on conventional AODV protocol. Black‐hole node will give route reply with highest sequence number to entice the sender to create a route through it. By using intruder detection system threshold mechanism, the black‐hole nodes are identified and isolated. In this article, maximal destination sequence number is estimated by using linear regression technique. Performance comparison is carried out with normal, black hole based and black hole detected routing mechanisms. The simulation findings show that that incorporated method enhances network performance by improving QoS under black hole attack.

Evaluation of Traffic Models under Multiple Black hole Attack in Wireless Mesh Network

Wireless networks are the networks in which data communication is done through the wireless channels and wireless nodes. In such type of the networks, cooperation of the all nodes is required. Due to which, chances of security attacks is possible and network performance and security is badly affected. Black hole attack is a security attack comes under the active, internal as well as external attacks. In black hole attack, malicious node presents a suitable, shortest and low cost path. If the above path is selected for data transmission, malicious node drops the received packets and as a result performance of the network is degraded. In this paper, impact of Random Direction (RD) and Reference Point Group Mobility (RPGM) models have been analyzed for wireless mesh network in the presence of multiple black hole attacks. By varying the number of network connections and node density, (Ad hoc on demand distance vector) AODV routing protocol is evaluated. Normalized routing load, average end to end delay, average throughput, and total number of packets received are considered as performance metrics. Bonn-motion tool has been used to create the scenario of mobility models. In the presence of black hole attack, and under RPGM mobility model, AODV routing protocol presents better results in respect of average throughput, normalized routing load. Simulation work has been carried out on network simulator version NS-2.35.

A Survey on Various MANET Protocols

In recent years, mobile technology is popular among the human society which makes the humans connected virtually to both living things [Social Media] and non living things [IOT]. MANET plays a vital role in wireless network infrastructure. Ad-hoc Wireless network consist of a two or more mobile nodes connected wirelessly in a self configured, self-healing network without having a constant framework. Each and every device in MANET was able to move freely in any directions to share the information between each devices or nodes of network. Many routing protocols for such networks have been proposed so far to find optimized routes from source to the destination and prominent among them are Dynamic Source Routing (DSR), Ad-hoc On Demand Distance Vector (AODV), and Destination-Sequenced Distance Vector (DSDV) routing protocols. The charateristics comparison of these protocols should be considered as the primary step to understand the routing protocol in a perfect manner.

Fitness Sorted Red Deer-Cat Swarm Optimization-based Autonomous QoS-aware Multicast Communication System in MANET

A mobile ad hoc network (MANET) is a set of autonomous mobile devices connected by wireless links in a distributed manner and without a fixed infrastructure. Mobile Ad-Hoc Networks (MANETs) is considered as an infrastructure-less and constant self-configured network of wireless devices. Here, multicast has emerged as an efficient tool for communication. Recently, distinct research works have been studied in wireless MANETs for designing multicast routing protocols. Multicasting is a procedure used for allowing the users to send the same messages simultaneously to a set of users. Though, it suffers from different problems regarding implementation in ad-hoc networks owing to its shorter battery lifetime, and lack of bandwidth dynamic nature of the mobile devices. Hence, the main aim of this paper is to propose a new QoS-aware multi-cast routing protocol in MANET using the hybrid meta-heuristic algorithm. The proposed routing protocol will focus on the development of a hybrid meta-heuristic-based “reliable neighbor nodes selection” scheme over the Multicast Ad-Hoc on Demand Distance Vector routing protocol (MAODV) protocol. The “reliable neighbor nodes selection” is accomplished by Fitness sorted Red Deer-Cat Swarm Optimization (FRD-CSO) algorithm focusing on the constraints like energy model, mobility model, and reliability pair factor. Once the optimal node selection is performed, the proposed QoS-aware protocol is validated by the route discovery mechanism and route reply process. The simulation has been performed to show the efficiency of the designed multicast routing over other multicast routing protocols that demonstrates the noteworthy enhancement in terms of diverse performance measures.

A Review Paper of M-AODV Routing Protocol in VANET to Detect and Prevent Black Hole Attack

Abstract: In the field of contemporary intelligent transportation, vehicular ad hoc networks (VANETs) are a popular and promising technology. They are employed to provide effective life safety, intelligent transportation systems, and traffic information systems (TIS). Due to the nodes' mobility and the connections' brittleness, the VANET is open to a variety of security risks. One type of security risk known as a "black hole attack" involves a node presenting itself to other nodes in such a way that it has the quickest and most direct access to the target. As a result, an effective method for the detection and eradication of the Black hole attack in the Vehicular Ad Hoc Networks (VANET) is given in this research study. One of the most widely used routing protocols for VANET, AODV (Ad hoc On Demand Distance Vector) is used to achieve the suggested method. In the first stages of route discovery, the technique can identify both a single black hole attack and a cooperative black hole attack. The simulation is carried on NS2 and the results of the proposed scheme are compared to [14] and the fundamental AODV routing protocol, this results are examined on various network performance metrics such as packet delivery ratio, throughput and endto-end delay. The found results show the efficacy of the proposed method as throughput and the delivery ratio of the network does not deteriorate in presence of the back holes

Efficient Ad Hoc On Demand Distance Vector Routing Protocol Based on Route Stability in MANETs

Efficient Ad Hoc On Demand Distance Vector Routing Protocol Based on Route Stability in MANETs

Energy Factor Based Routing Algorithm for Lifetime Enhancement in Mobile Ad-Hoc Networks

Energy consumption and dissipation of mobile nodes is considered as one of the significant aspect affecting the entire lifetime of Mobile Ad-Hoc Networks (MANETs), as the nodes depends on limited battery power. In addition, spatial and temporal characteristics of mobile nodes also make energy imbalance in the network. Towards this, there are several studies that emphasis on improving the network lifetime and reliability by altering the existing MANET routing protocols. In this paper, an Energy Factor based Ad-Hoc On Demand Distance Vector routing algorithm (EF-AODV) is proposed in MANETs for lifetime enhancement. The proposed technique includes two algorithms by leveraging the cross layer paradigm. Firstly, proposed EF-AODV dynamically chooses intermediate nodes based on battery power, and mobility of the nodes in the direction of destination. Secondly, for uniform energy consumption, we calculate the energy factor at each intermediate mobile node by considering the sleep and ideal states of the nodes along with mobility. Further, the energy factor is considered as a key metric to obtain the optimal path from the source to the destination to balance the energy disparity in the network, leading to reduced delay in packet transmission. The path with highest energy factor value is selected for networking of data packets. Upon extensive simulation using Network Simulator (NS-2.34), we illustrate that the proposed EF-AODV outperforms over existing ad-hoc routing approaches under the various performance metrics.

A Comparative Study of Routing Protocols for Minimum Path Cost Matric in MANETS

The Routing is the process of transmitting data packets from one node to another another node from source to destination The Mobile Adhoc Networks (MANETs ) doesn't have any fixed network structure or any centralized process to administer. The selection of the route is important for performance of packet transfer from source to destination. These routing protocol are classified as inter domain routing and Intra domain routing protocol. The routing protocols have been classified into Non Reactive , Reactive and Hybrid protocols. In the present paper we proposes to compare reactive routing protocols videlicet Ad hoc On Demand Distance Vector (AODV), Dynamic Source Routing (DSR) protocols, Temporarily Ordered Routing Algorithm (TORA) and Associativity Grounded Routing (ABR) protocol.The Routing in MANETs is a one of the robustly and demanding task and has entered a great quantum of mindfulness from experimenters around the globe. To overcome this problem, a colorful number of routing classes have been introduced and the number is still rising day by day fastly. It's relatively hard to decide which protocols or routing classes may do well under an quantum of different network scripts similar as network volume and network topology etc. The study and performance of the above mentioned protocol has also been tabulated in the present two tables . The protocols are based on minimum power and temporary configuration of topology. The table 1 gives comparison of the main characteristics of routing protocols and Table2. provide comparison of various reactive routing protocol.

Distance Enhancement of Quantum Cryptography through MANET

In the modern technology world, the cryptographic techniques are plays a major role. There are so many modern cryptographic algorithms are used to secure information through message transformation. Quantum cryptography evolved from the merging of physics and cryptography to reduce the threat that encryption encounters. It is one of the emerging fields in the computer technology. The primary objective of quantum cryptography research is to develop cryptographic algorithms and protocols that are resistant to quantum computer attacks and increase the communication distance. The various quantum cryptography protocols are demonstrated, as well as how this technology has led to the establishment of secure communication between sender and the receiver through using of MANET. We will look at the properties of quantum cryptography and the benefits of MANET it can provide in the future internet. One of the best ways for increasing the distance of message transmission over the internet is to use MANET in the field of quantum cryptography. An Ad hoc on demand distance vector (AODV) is a routing protocol for Mobile Ad hoc networks

Black Hole Attacks on MANETs: Analysis and Prevention

Wireless network technically, refers to the category of network in which communication is carried out without using wires. In modern era wireless network has great importance because the communication is taking place with the use of radio waves. Thus, the use of ad-hoc network starts yielding a great importance in variety of applications. The certain research work is carried out in this particular field. MANET is a constructed from various mobility in the form of mobile nodes and anytime without any need of fixed infrastructure. MANET can be made on fly due to lack of fixed infrastructure. MANET is numerous threats types of attacks due to dynamic changing topologies and wireless medium. Security of the MANET becomes one of the challenging tasks. Black hole attacks is the main type of attack that are possible in MANET. Black hole node not forward any data packets to the neighbour node instead it drops all the data packets. Black hole attacks are bit hard to detect due to lack of centralized access. This research work concentrates to enhance the security of MANET by identifying and blocking black hole assaults from occurring. A reactive routing system such as Ad-Hoc on Demand Distance Vector has previously been used to address security problems in the MANET (AODV). Various attack types were investigated, and the consequences of these assaults were detailed by describing how MANET performance was disrupted. Network Simulator 3 (NS3) is used for the simulation process.

Studying Routing Issues in Vanets Using Ns-3 and SUMO

Vehicular Ad-hoc Networks VANETs are normally sparse, highly dense, and highly mobile with many different and ever-changing topologies. These characteristics impose a challenge on finding a routing algorithm that fits the requirements of such network. The aim of this work is to study the performance issues of VANETs under different scenarios using realistic mobility models. In this paper, a comparative study is done among Ad-hoc On- Demand Distance Vector (AODV), Optimized Link State Routing (OLSR) and position-based routing protocols, namely Greedy Perimeter stateless routing (GPSR), and Max duration Min angle GPSR (MMGPSR). The comparison is done using key quality of service QoS metrics such as average routing goodput, end-to-end delay, MacPhy overhead, and packet delivery ratio PDR. The study is conducted using Network Simulator 3 (NS3) and SUMO.

Adaptive mobility-aware and reliable routing protocols for healthcare vehicular network.

Healthcare vehicles such as ambulances are the key drivers for digital and pervasive remote care for elderly patients. Thus, Healthcare Vehicular Ad Hoc Network (H-VANET) plays a vital role to empower the digital and Intelligent Transportation System (ITS) for the smart medical world. Quality of Service (QoS) performance of vehicular communication can be improved through the development of a robust routing protocol having enhanced reliability and scalability. One of the most important issues in vehicular technology is allowing drivers to make trustworthy decisions, therefore building an efficient routing protocol that maintains an appropriate level of Quality of Service is a difficult task. Restricted mobility, high vehicle speeds, and continually changing topologies characterize the vehicular network environment. This paper contributes in four ways. First, it introduces adaptive, mobility-aware, and reliable routing protocols. The optimization of two routing protocols which are based on changing nature topologies of the network used for vehicular networks has been performed, amongst them, Optimized Link State Routing (Proactive) and Ad-hoc on Demand Distance Vector (Reactive) are considered for Packet Delivery Ratio (PDR) and throughput. Furthermore, Packet Loss Ratio (PLR), and end-to-end (E2E) delay parameters have also been calculated. Second, a healthcare vehicle system architecture for elderly patients is proposed. Third, a Platoon-based System model for routing protocols in VANET is proposed. Fourth, a dynamic channel model has been proposed for the vehicle to vehicle communication using IEEE8011.p. To optimize the QoS, the experimental setup is conducted in a discrete Network Simulator (NS-3) environment. The results reveal that the AODV routing protocol gives better performance for PDR as well as for PLR and the communication link established is also reliable for throughput. Where OLSR produces a large average delay. The adoptive mobility-aware routing protocols are potential candidates for providing Intelligent Transportation Systems with acceptable mobility, high reliability, high PDR, low PLR, and low E2E delay.