On-demand Distance Vector Routing Research Articles

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.

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.

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.

Minimizing End-To-End Time Delay in Mobile Ad-Hoc Network using Improved Grey Wolf Optimization Based Ad-Hoc On-demand Distance Vector Protocol (IGWO-AODV)

Mobile Ad-Hoc network is one of the instant network with unknown mobile devices. Each and every node in the network may act differently. Because of this time taken to travel packet from source to destination will take more time. This work proposes Improved Grey Wolf Optimization Based Ad-Hoc On-Demand Distance Vector routing protocol for reduce the End-to-End time delay in MANET.

Self-reconfigurable partial mesh using ZigBee control board towards fail-proof and reliable home area networking

This paper deals with the development of customized home area networking (HAN) with a higher degree of reliability so that a robust communication network can be provided to smart home owners. The proposed HAN is built with the multi-gateway-based partial mesh networking topology using state-of-the-art ZigBee control boards (ZCBs) where each individual appliance within the home can be monitored and controlled remotely. The gateway is actually used to coordinate amongst the In-home display (IHD), ZCBs, smart meter, and remote server-based home energy management software or even with the mobile Apps in such a way that the best possible energy usage can be made. In order to enhance the reliability of this proposed HAN, the active and pseudo gateway concept is introduced in which under the failure of the active gateway (AG), pseudo gateway (PG) takes control, and the HAN gets reconfigured automatically. Malfunctioning or failure of any ZCB or even gateway node is detected during route discovery with ad-hoc on-demand distance vector (AODV) routing. The reliability of the proposed system is estimated using possible path models and region models considering all of its running conditions. The proposed system is simulated and a prototype laboratory setup with 15 and 10 numbers of ZCBs is built for experimental verification. Various failure conditions are experimented with to demonstrate the alternate routes and activation of PG as AG. The availability of an alternate route and/or gateway makes this proposed HAN a fail-proof and reliable one and this is reflected from the relative values obtained from the simulated and experimental results.

End to end delay distribution analysis and interference aware high throughput for Wireless Mesh Networks

The wireless mesh network is an innovative and efficient wireless communication approach with immense potential to transform future wireless networks. This cutting-edge wireless technology provides a wide range of wireless services for personal, local, campus, and metropolitan environments. The wireless mesh network consists of a cluster of mobile wireless nodes that can dynamically and instantaneously create random and temporary network topologies, forming a wireless ad-hoc network. Ad hoc wireless networks are particularly advantageous due to their cost-effectiveness and ease of deployment. In order to further optimize the performance of ad-hoc networks, different routing algorithms such as Ad-hoc On-Demand Distance Vector Routing (AODV), Dynamic Source Routing Algorithm (DSR) and Destination Sequenced Distance Vector (DSDV) have been thoroughly researched via simulation.

Design of a Self-Organizing Routing Protocol for Underwater Wireless Sensor Networks Based on Location and Energy Information

Underwater wireless sensor networks (UWSNs) are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, variable topology, limited battery, low processing power and so on. These new features pose many challenges to the design of self-organizing routing protocol for UWSNs. This paper focuses on the application of Ad Hoc On-demand Distance Vector (AODV) routing protocol in UWSNs. In order to solve the problems of packet collision and excessive energy consumption associated with the flooding-based routing discovery method and the periodic hello packet routing maintenance mechanism of AODV, a routing discovery and maintenance method based on location and energy information is proposed, and it is referred to as the route-focusing AODV (RFAODV) routing protocol. In the RFAODV protocol, the routing discovery process is focused on a few nodes through forwarding area control and dynamic delay adjustment. In addition, feedback from a media access control layer and residual energy control are used for routing maintenance. We implement the RFAODV and evaluate its performance according to the sea trial data as parameters in the NS-2. The simulation results show that compared with the other protocols, RFAODV improves the routing discovery success ratio by at least 18%, increases the packet transmission ratio by at least 4%, reduces the protocol overhead by at least 15% and reduces the energy consumption by at least 5% under various simulation scenarios. RFAODV is suitable for large-scale, high-load and dynamic networks underwater wireless sensor networks.

SDODV: A smart and adaptive on-demand distance vector routing protocol for MANETs

SDODV: A smart and adaptive on-demand distance vector routing protocol for MANETs

Clustering based secure error report fault tolerant routing in mobile adhoc networks

A Mobile Ad-hoc Network (MANET) is a self-constructed network consisting of spatially distributed nodes that cooperatively arrange themselves without any centralized manager or fixed based stations. In MANET, the nodes are deployed in a dynamic scenario, so, the nodes may fail as a result of energy depletion, hardware failure, communication link errors, and malicious attacks. Therefore, it is necessary to design energy-efficient fault-tolerant algorithms and protocols for MANETs. Since the development of Mobile Ad-hoc networks was originally motivated by military applications, such as battlefield surveillance and healthcare applications it is required to have a fast recovery mechanism to overcome the fault condition. In this research work, a fault-tolerant Routing mechanism is designed and implemented to address the fault conditions such as node failure, link failure, and critical battery issues called Fault tolerant cluster based AODV with Error Reporting Routing (CAODVERR) protocol, and to improve the stability of the MANET. Also, an Error reporting mechanism has been incorporated with the Ad-hoc On-Demand Distance Vector (AODV) routing protocol.

Secured mobile IOT ecosystem using Enhanced Multi-level Intelligent Trust Scheme

The Internet of Things (IoT) is a collection of heterogeneous, interconnected mobile ad-hoc networks (MANETs) devices. High-level security is always required to protect sensitive information travelling over MANET-IoT networks. IoT security ensures the privacy, confidentiality, and security of the users, infrastructure, and data. The Enhanced Multi-Level Intelligent Trust Scheme (EMITS) initially designs to authenticate and validate the data for the Mobile IoT (MIoT) ecosystem. The proposed model used the AODV (Adhoc On-Demand Distance Vector Routing) routing protocol with an intelligent trust scheme. This paper aims to present a MANET-IoT-based model combined with a hybrid cryptographic scheme that ensures secure communication between mobile IoT ecosystems against the black hole attack. The performance of the proposed EMITS-MIoT model is verified based on the packet delivery ratio (PDR), packet loss ratio (PLR), false positive ratio (FPR), false negative ratio (FNR), and attack detection rate (DR). The EMTS-IoT technique shows a 3–5% success in data transmission over existing techniques.

Analysis of Latency and Bandwidth for Edge-Based Short Length in Edge Computing Devices for Short Ranges and Long Ranges

Objectives: To propose an IoT-based design in an edge computing environment for short ranges and long ranges of real-time data streaming to the client. Methods: Multimedia data is used in this work. Here we have used Opnet for creating a physical architecture and to analyze the quality-of-service parameters like delay, throughput, and jitter for different Ad-hoc routing protocols like Ad-hoc on-Demand Distance vector routing, Dynamic source routing, Optimized Link State Routing, Temporally ordered routing algorithm and Geographic Routing Protocol for edge-based short length in edge computing devices for short ranges and long ranges. Riverbed academic modeler (formerly known as OPNET) has been used as a simulation tool to analyze the latency and bandwidth for edge computing under the pre-configured set-up. The simulation is accomplished using MATLAB to find the fluctuation of the delay, throughput, and jitter for edge-based short length in edge computing devices for short ranges and long ranges by applying the datasets in the edge computing environment. Findings: The results we got through simulations from different routing protocols like AODV, DSR, OLSR, TORA, and GRP of delay, throughput, and jitter shows that the proposed system strengthens the existing cloud-based system, leading to greater QoS.AODV surpasses all other protocols with a minimal delay of 0.24 msec and OLSR achieves the best performance with an average delay of 0.3 msec, better throughput of 180 bits/sec, and a load of 1410 bits/sec for the three key parameters of latency, throughput, and jitter. Novelty: The study compares the performance of different routing protocols and shows a reduction in the delay of 0.24 msec with respect to time as compared to other existing works. The proposed research is designed for a media streaming application based on the mobile nodes regarded as an edge devices fordifferent QoS parameters like throughput, delay, and load, and by comparing the existing work we found that AODV outperforms all other routing protocols with a minimum delay. Keywords: Edge Computing; Cloud Computing; Latency; Bandwidth; Throughput; Jitter

Enhanced On-demand Distance Vector Routing Protocol to prevent Blackhole Attack in MANET

Wireless networks are becoming increasingly popular. Mobile ad hoc networks are one category among the different types of wireless networks that transmit packets from the sender node to the receiver node without the use of abase station or infrastructure, as the nodes serve as both hosts and routers. These networks are referred to as mobile because they are movable. MANET is an ad-hoc network that can change positions at any time, and nodes can join or leave at any moment, making it vulnerable to attacks such as Blackhole. Existing solutions, in some ways, led to more memory space consumption, while others led to an overhead. This research proposes an Enhanced On-demand Distance Vector (AODV) routing protocol to prevent Blackhole attacks on MANETs using Diffie Hellman and Message Digest 5 (DHMD), implemented using Network Simulator 2 (NS2). The performance of the proposed protocol was evaluated using the following parameters: Packet Delivery Ratio, throughput, End to End (E2E)Delay, and routing overhead. It was concluded that DHMD has reduced network over head as it resulted to 23% while AODV resulted at 38%and memory consumption for DHMD gave 0.52ms compared to AODV that gave 0.81msdue to Blackhole prevention. This research will help to mitigate the effect of blackhole attacks in a network and increase network performance by reducing overhead and memory consumption.

Efficient Optimal Routing Algorithm Based on Reward and Penalty for Mobile Adhoc Networks

Mobile adhoc networks have grown in prominence in recent years, and they are now utilized in a broader range of applications. The main challenges are related to routing techniques that are generally employed in them. Mobile Adhoc system management, on the other hand, requires further testing and improvements in terms of security. Traditional routing protocols, such as Adhoc On-Demand Distance Vector (AODV) and Dynamic Source Routing (DSR), employ the hop count to calculate the distance between two nodes. The main aim of this research work is to determine the optimum method for sending packets while also extending life time of the network. It is achieved by changing the residual energy of each network node. Also, in this paper, various algorithms for optimal routing based on parameters like energy, distance, mobility, and the pheromone value are proposed. Moreover, an approach based on a reward and penalty system is given in this paper to evaluate the efficiency of the proposed algorithms under the impact of parameters. The simulation results unveil that the reward penalty-based approach is quite effective for the selection of an optimal path for routing when the algorithms are implemented under the parameters of interest, which helps in achieving less packet drop and energy consumption of the nodes along with enhancing the network efficiency.

A Cross-Layer Solution for Contention Control to Enhance TCP Performance in Wireless Ad-Hoc Networks

With the development of wireless technology, users not only have wireless access to the Internet, but this has also sparked the emergence of Wireless Ad-hoc Networks (WANETs); this promising networking paradigm has the potential to adopt the shape of new emergent networks such as the Internet of Things (IoT), Vehicular Ad-hoc Networks (VANET) and Wireless Sensor Networks (WSN). However, channel contention (CC) is one of the key reasons why the TCP performs poorly in WANETs. This paper presents a mechanism called Cross-layer Solution for Contention Control (CSCC) to enhance TCP performance in WANETs. Each node starts marking packets in the proposed mechanism when its CC level reaches a certain threshold. As a result, the source node adjusts the congestion window (cwnd) size to a good state to control the insertion ratio of packets into the network. To provide a fair share to each flow, the flow having a large cwnd is penalized more. Numerous simulations have been conducted across several topologies to clarify the performance of the suggested mechanism. The simulation findings show that, in the presence of the Ad-hoc On-demand Distance Vector (AODV) routing and Dynamic Source Routing (DSR) protocols, the proposed CSCC mechanism outperformed TCP NewReno in terms of throughput and fairness. In comparison to TCP NewReno, the suggested mechanism has fewer retransmitted packets.

A Deep Learning-Based Routing Approach for Wireless Mesh Backbone Networks

Optimal routing decisions are key in communication network environments to minimize bottlenecks such as traffic congestion and limited bandwidth. Routing in wireless mesh backbone networks is the focus of this study given that they are popular particularly for providing broadband connectivity to a huge number of users accessing and transmitting multimedia data hence are susceptible to communication-oriented bottlenecks. Existing routing solutions are mainly optimistic approaches. These mainly depend on link states, distance and hop counts which present a routing generalization bottleneck especially in huge wireless mesh networks because it is difficult to get the entire footprint of the network. Simply put, it is very difficult to determine an optimal route in a huge wireless mesh network (WMN) with dynamic network conditions. Since deep learning has a strong generalization ability. In this paper, a deep learning-based routing approach is proposed with the goal of ensuring a defined optimal quality of service (QoS) in a WMN. In order to achieve the study purpose, a wireless mesh network simulation environment is built and a network data feature set is orchestrated to generate a data set used to train a Long short Term Memory (LSTM)-based deep learning model that estimates the route with the optimal QoS. The generated data set is validated by training other learning models including the Multilayer Perceptron (MLP), Logistic Regression (LR) and Random Forest (RF). Our results show that the routes selected by the LSTM-based model provides the best packet delivery ratio (PDR) and throughput. Our results further show that the learning models (MLP, LR, RF) also provide better PDR and throughput compared to the traditional Ad-hoc On-demand Distance Vector (AODV) routing protocol.

Avoid Suspicious Route of Blackhole Nodes in MANET’s: Using A Cooperative Trapping

Mobile Ad hoc Network (MANET) is decentralized wireless network and can communicate without existing infrastructure in many areas. MANET is vulnerable to various attacks that affect its performance such as blackhole attack. Blackhole attacker, inject fault routing information to persuade the source node to select the path with malicious node as the shortest path. To eliminate malicious nodes from launching any collaborative attack. A cooperative Trapping Approach (CTA) was proposed based on modifying Ad-hoc On-demand Distance Vector (AODV) routing protocol and trapping the malicious nodes by responding to the trap request message. The approach aims to eliminate and rule out both single and collaborative malicious blackhole nodes from any attack. The approach realizes a backward tracking mechanism to perform the elimination process. The proposed algorithm (CTA) was executed using NS-2 network simulator. The performance metrics that has been considered to evaluate the performance of the proposed algorithm such as throughput, end to end delay, packet delivery ratio, and consuming energy. The experimental results have shown the performance metrics of the proposed approach outperformed other state of at algorithms.

Modified Adhoc On-Demand Distance Vector for Trust Evaluation And Attack Detection

Recently, Wireless Sensor Network (WSN) becomes most potential technologies for providing improved services to several data gathering and tracking applications. Because of the wireless medium, multi-hop communication, absence of physical protectivity, and accumulated traffic, WSN is highly vulnerable to security concerns. Therefore, this study explores a specific type of DoS attack identified as a selective forwarding attack where the misbehaving node in the network drops packet on a selective basis. It is challenging to determine if packet loss is caused by a collision in the medium access path, poor channel quality, or a selective forwarding assault. Identifying misbehaving nodes at the earliest opportunity is an acceptable solution for performing secure routing in such networks. As a result, in this study effort, we present a unique Modified Ad Hoc On-Demand Distance Vector (AODV) Routing protocol depending upon the One time password (OTP) method that employs the RSA algorithm. Finally, a trust evaluation process determines which approach is the most optimal. According to the simulation findings of the suggested routing protocol and comparison with existing routing protocols provided in this article, the proposed work is both efficient and cost-effective.

A Novel Cross-Layer Adaptive Fuzzy-Based Ad Hoc On-Demand Distance Vector Routing Protocol for MANETs

One of the essential processes in Mobile Ad hoc Networks (MANETs) is blind flooding to discover routes between source and destination mobile nodes. As the density of nodes in the network increases, the number of broadcast packets increases exponentially. This can lead to broadcast storms, a drain on the device’s battery, and reduced network efficiency. We propose a Cross-layer Adaptive Fuzzy-based Ad hoc On-Demand Distance Vector routing protocol (CLAF-AODV) to minimize the routing broadcast traffic by considering the quality of service (QoS) (e.g. delay, throughput, packet loss), stability, and adaptability of the network. The suggested method employs two-level fuzzy logic and a cross-layer design approach to select the appropriate nodes with a higher probability of participating in broadcasting by considering parameters from the three first layers of the Open Systems Interconnection (OSI) model to achieve a quality of service, stability, and adaptability. It not only investigates the quality of the node and the network density around the node to make a decision but also investigates the path that the broadcast packet traveled to reach this node. Simulation results reveal that our proposed protocol reduces the number of broadcast packets and significantly improves network performance with respect to throughput, packet loss, normalized routing load, collision rate, and average energy consumption compared to the standard AODV and the Fixed Probability AODV (FP-AODV) algorithms.

Privacy Aware Post Quantum Secure Ant Colony Optimization Ad Hoc On-Demand Distance Vector Routing in Intent Based Internet of Vehicles for 5G Smart Cities

Privacy Aware Post Quantum Secure Ant Colony Optimization Ad Hoc On-Demand Distance Vector Routing in Intent Based Internet of Vehicles for 5G Smart Cities