Performance Of Ad-hoc Networks Research Articles

INVESTIGATION OF THE MANET NETWORK PERFORMANCE CONCERNING DIFFERENT ROUTING PROTOCOLS

Mobile Ad-Hoc Network is a decentralized organization that operates without a foundation. Due to the Mobile Ad-Hoc Network's self-configurable and simple organizational component, many applications may be run. Because of this, various applications are available. If helpful guidelines are established, Mobile Ad-Hoc Network will become dependable. We shall research the organization's competent steering convention for hypertext transfer protocol traffic. We must reach this conclusion with accuracy since this will be the main focus of our inquiry. Latency and throughput were employed to achieve show research goals. For this work reenactment inquiry, your expectations must be based on the conventions it chose since they performed better on all four perspectives. After analyzing its needs, an organization may improve its operations by choosing better conventions. This may boost an organization's efficiency. This research examined AODV, DSR, and OLSR routing methods. This study used OPNET Modeler 14.5 to enhance ad-hoc network performance.

Enhancing Security and Performance in Vehicular Adhoc Networks: A Machine Learning Approach to Combat Adversarial Attacks

Integrating Machine Learning (ML) techniques into Vehicular Adhoc Networks (VANETs) provides promising features in autonomous driving and ITS applications. In this paper, DSRC data is used to evaluate the effectiveness of different ML models, including Naive Bayes, Random Forest, KNN, and Gradient Boosting, in normal and adversarial scenarios. Since the dataset is relatively imbalanced, the Synthetic Minority Over-sampling Technique (SMOTE) is employed for sampling, and defensive distillation for improving model resilience to adversarial perturbations. From the results, it is clear that models such as Gradient Boosting and Random Forest show high accuracy in both cases, thus showing the potential of using Machine Learning to improve VANET security and reliability when new threats appear. Through this research, the significance of the application of ML in the protection of vehicular communication in order to enhance both traffic safety and flow has been articulated.

Exploiting Conventional MANET Routing in UAV’s Based Environment

Nowadays, Unmanned Aerial Vehicles (UAVs), have indeed revolutionized various industries and opened up new possibilities. Additionally, a Flying Ad hoc Network (FANET), a group of UAVs can perform specific functions like delivering goods, assisting people after a disaster, monitoring the weather and environment, among others. FANET is another kind of ad-hoc mobile network. It is capable of connecting with its environment and other nodes to obtain critical information. It is particularly difficult to route across FANETs because of how mobility they are and how fast they may change layouts. Therefore, routing algorithms are crucial for improving the performance of ad-hoc networks. This article will analyse the performance of the AODV, DSDV, and TORA routing protocols in the FANET environment. The NS-2 simulator has been used for testing parameters such as jitter, throughput, End-to-End delay, and packet delivery ratio (PDR). The simulation results indicate that TORA outperforms AODV and DSDV routing protocols across all performance metrics except End-to-End Delay.

Smart AODV Routing Protocol Strategies Based on Learning Automata to Improve V2V Communication Quality of Services in VANET

The Adhoc On-Demand Distance Vector (AODV) protocol faces challenges in selecting the best relay nodes, which requires optimization to improve performance in Vehicular ad-hoc networks (VANETs). This study aims to enhance Vehicle-to-Vehicle (V2V) communication in VANETs by implementing the Learning Automata-Driven Ad-hoc On-Demand Distance Vector (LA-AODV) routing protocol. LA-AODV is designed to achieve higher packet delivery ratios and optimize data transfer rates, even under congested network conditions, by dynamically adjusting to changing network scenarios. The performance evaluation includes six key metrics analyzed under varying node densities and time intervals, comparing LA-AODV against the standard AODV protocol. Results indicate that LA-AODV consistently outperforms AODV, demonstrating improved efficiency in flood identifier management, reduced data loss, higher packet delivery ratios, better throughput, and reduced end-to-end delay and jitter. Specifically, under a 20-node scenario, LA-AODV exhibits lower flood ID scores (54 vs. 88), reduced packet loss (11% vs. 12%), higher PDR (88.0% vs. 87.0%), and superior throughput (85.34 Kbps vs. 47.26 Kbps). Additionally, LA-AODV achieves lower end-to-end delay (6.84E+09 ns vs. 3.76E+10 ns) and jitter (2.52E+09 ns vs. 2.15E+10 ns). These findings suggest that LA-AODV significantly enhances Quality of Service (QoS) in vehicular ad-hoc networks, positioning it as a promising solution for optimizing V2V communication performance.

A Comprehensive Analysis of Deep Learning and Swarm Intelligence Techniques to Enhance Vehicular Ad-hoc NETwork Performance

A Comprehensive Analysis of Deep Learning and Swarm Intelligence Techniques to Enhance Vehicular Ad-hoc NETwork Performance

Improving Routing Performance in Mobile Ad Hoc Networks Using Artificial Neural Networks for Mobility Prediction using deep learning

In this study, a research was done to examine the effectiveness of deep learning models, such as the Artificial Neural Networks, Convolutional Neural Networks, Gated Recurrent Units and Generative Adversarial Networks, to boost routing’s efficiency and performance in the Mobile Ad Hoc Networks through mobility prediction. In total, 10 experiments were conducted, and ANNs demonstrated an average prediction accuracy of 0.86, MAE of 0.10, RMSE of 0.16, and correlation coefficient of 0.93. CNNs showed the most impressive performance, featuring the following indicators: the average prediction accuracy of 0.87, MAE of 0.09, RMSE of 0.15, and the correlation coefficient of 0.94. GRUs, in their turn, displayed quite decent performance, with an average prediction accuracy of 0.87, MAE of 0.10, RMSE of 0.16, and the correlation coefficient of 0.94; in the meanwhile, GANs can be also seen as offering a decent performance, with the average prediction accuracy of 0.87, MAE of 0.10, RMSE of 0.16, and the correlation coefficient of 0.94. In the end, the identified findings imply that deep learning models can be used to enhance the routing efficiency in MANETs, since they can predict the node movement with the high level of accuracy. The identified changes are possible to lead to the creation of effective wireless communication networks.

A Comprehensive Approach with Trust-Based Routing, Energy Optimization, and Multi-Routing Protocol for Enhancing Security and Performance in Mobile Ad Hoc Network

In this paper, we propose an aggregate solution to boost the security, performance, and resilience of disaster-based comms networks. This involves trust-based routing, energy optimization, and more than one routing protocol to meet the unique requirements of the ever-changing and unpredictable environments facing disasters in this world. The evaluation brings 4.3 Mbps for the average throughput, 34 ms delay with a packet delivery ratio of 96.9%. Also, energy consumption was optimized and the average consumption of 2458 Joules makes sharing power resources an easy exercise even when you are in a disaster-prone zone. Security analysis of the experiments showed on average 2.7 vulnerabilities across different trials with a range from 2 to 5 in severity level. Therefore, robust security mechanisms guard against potential threats, a reminder that disaster situations can befall any person or community. Overall, disaster response performance was good despite the difficult conditions. Further research and development in this area will continue to refine and improve communication systems for disaster preparedness and response efforts.

Mobile Ad-Hoc network, Mobile application, aircraft performance, software development

In the past decade, a steady increase has been noticed in the number of mobile users and the use of mobile communication. In wireless communication links are stable. Duration of the link is the most important design by which the performance of the mobile Ad Hoc network (MANET) can be determined. In this research article, a derivative metric of graph theory attained from mobility model technique in Ad Hoc network of casually moving object, link duration of probability density function (PDF)been examined by using three mobility models namely random waypoint, random direction, and freeway model. The performance is based on the node speed, transmission range, the density of node, area of simulation, and computational complexity with time. By using Monte Carlo simulations, the reliability and robustness of models have been analyzed. The main advantage of the proposed scheme is implemented is an easy hardware platform because of the concept in mobility models and the easiness of code.

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.

Estimation of the Achievable Performance of Mobile Ad Hoc Networks with Optimal Link State Routing

The paper explores the challenges of constructing self-organizing wireless mobile ad hoc networks (MANETs) utilizing Optimal Link State Routing (OLSR) with MPR (MultiPoint Relay) optimization and quality control through the RSVP (Resource Reservation Protocol). Analytical expressions are presented for calculating the achievable network characteristics, including route acquisition time, network efficiency (routing overhead), packet transmission delay (end-to-end delay), and signal propagation losses between nodes assuming no packet collisions within the network nodes. The possibility of network scalability is analyzed depending on the scenarios of operation and the number of network nodes. Recommendations for the construction and scalability of self-organizing wireless networks are formulated based on the conducted evaluations and calculations.

Performance of Vehicle Ad-Hoc Networks (VANETs) Operating in a Hostile Environment

Performance of Vehicle Ad-Hoc Networks (VANETs) Operating in a Hostile Environment

Performance Enhancement of MANET based on Cross-layered Reconfigurable Hierarchical Routing Protocol

High speed data communication is the demanding factor in both commercial and defence applications. Several algorithms are proposed to support the high-speed data exchange while ensuring the quality, performance and reliability. However, there is still a gap, citing various compatibility issues with variety of transceiver technologies. This paper proposes a novel algorithm for enhancing the performance of mobile ad-hoc networks using Free-Space Optics (FSO). The FSO has the natural ability to the interference while capable of large bandwidth and excellent compatibility. Low power and adaptability are the features with which it has contributed to the latest technologies like storage area network, wireless area network etc. The proposed work uses optical spheres with a multi-transceiver system and a cross-layered reconfigurable routing mechanism. Parameters such as delay, residual energy, throughput, and drop are verified for the Crosslayered Reconfigurable Hierarchical Routing Optical Sphere (CRHROS) protocol for varying numbers of optical transceivers. The proposed work also compares the performance of two traffic sources, Constant Bit Rate (CBR) and Variable Bit Rate (VBR), for the proposed algorithm.

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.

Connectivity Enhancement of E-VANET Based on QL-mRSU Self-Learning Energy-Saving Algorithm

With the development of smart cities and smart electric vehicles (EVs), the problem of improving the performance of Vehicular Ad-hoc Networks (VANETs) is gradually being emphasized. To improve the network performance of VANETs, some scholars have considered parked vehicles as roadside units, but have not paid attention to the energy consumption characteristics of vehicles, especially electric vehicles. Therefore, in this paper, we propose a QL-mRSU series artificial intelligence energy saving method to optimize the energy consumption of parked electric vehicles during communication. The method is based on electric vehicle self-organizing networks (E-VANETs), which dynamically cluster electric vehicles parked in parking lots by parameters such as traffic flow, number of service demands, and charging index in reinforcement learning, select the most suitable vehicles as mobile roadside units (mRSUs), and adjust the working mode according to environmental changes such as the number of service demands to achieve the effects of self-learning and energy saving. The simulation experimental results show that compared with other energy-based routing algorithms, the method is able to make optimal choices through self-learning with guaranteed communication quality and is more adaptable to traffic flow changes on the road, thus ensuring the stability of energy-saving efficiency. In addition, the method significantly improves the energy structure of electric vehicle parking clusters.

On the Weighted Cluster S-UAV Scheme Using Latency-Oriented Trust

Drones, also known as unmanned aerial vehicles (UAVs), have become increasingly popular in the military and civil sectors. A swarm of UAVs (S-UAVs) is a group of UAVs that work together to complete a task. Because of the dynamic network topology of S-UAVs, routing schemes are complicated. Clustering is one of the most effective routing schemes for improving the performance of ad-hoc networks. The clustering scheme divides the network into groups known as clusters, each consisting of a cluster head (CH) and cluster members (CMs). The CH is a valuable element in the clustering scheme because it handles all inter- and intra-cluster communications. Proper selection of the CH is the key to enhancing the performance. Our study proposed a new clustering scheme for S-UAVs. Our scheme selects the CH and CMs based on a new weighted formula that consists of the following parameters: distance, speed, and reward index. The reward index is a newly calculated parameter based on latency. The weighted formula calculates the clustering index based on which CH and CMs are selected. This scheme was simulated using MATLAB to demonstrate its performance as a routing scheme. The simulation analyzed the latency due to the variation of the network’s parameters. In addition, the rewarding index and cluster index were analyzed. Finally, the proposed scheme was compared with an existing scheme known as the adaptive enhanced weighted clustering algorithm for UAV swarm. The comparison demonstrates that the proposed protocol is promising due to its lower-generated delays. The obtained results are displayed and analyzed towards the end of this paper, along with some ideas for future work.

Improving AODV Performance by Software Defined Networking Using NS3

Abstract Nowadays, vehicular networks attract car manufacturers, network researchers, and governments as well. They represent one of the building blocks, for the intelligent transportation systems. Our task is to study the employment of SDN advantages to facilitate and improve the performance of vehicular ad-hoc networks. The goal of the research is to evaluate AODV routing protocol performance improved with SDN technology applied on VANET network in specified environment of a city. We have evaluated three parameters: packet delivery ratio, end-to-end delay and throughput using SUMO and NS3 simulators. The implemented evaluation protocol shows the importance of the adopted approach.

Design and Implementation of Mobile Ad-Hoc Network Using Opnet Modeler

Mobile Ad-Hoc Network is a good illustration of a decentralized organization that does not need a foundation to function. The self-configurable and uncomplicated organizational component of this Mobile Ad-Hoc Network have made it feasible to run a wide variety of apps. As a consequence, these applications may now be used. If useful guiding standards are used, Mobile Ad-Hoc Network will develop into a robust system. During our investigation, we will attempt to determine which competent steering convention for directing hypertext transfer protocol traffic is utilized throughout the company. This will be the primary focus of our inquiry, so we must make this determination as accurately as possible. For this inquiry of the exhibition, execution measures such as latency and throughput were used. In this job reenactment research, your expectations should be based on the conventions that it chose since they had shown higher performance on every one of these fourth different viewpoints considerations. In addition to that, one way that an organization may improve the efficiency with which it operates is by picking conventions that are more suited for the business after taking into consideration the needs of the organization. AODV, DSR, and OLSR are the three routing protocols that were studied in this study to enhance the performance of ad-hoc networks via the use of OPNET Modeler version 14.5.

Conceptual Aspects on Mobile Ad-Hoc Network System

A mobile ad hoc network is made up of mobile wireless hosts. When hosts move, the routes change, necessitating the need for a system to find new routes. A crucial aspect of the development of wireless networks is ad-hoc networking. Ad-hoc networks often consist of identical nodes that connect with one another via wireless links without the use of a centralized controller. Ad-hoc wireless networks carry over the standard issues with wireless and mobile communications, like bandwidth optimization, battery management, and improvement of transmission quality. Due to its self-upkeep and self-configuration characteristics or behavior, mobile ad hoc networks (MANET) have achieved great success and attention. Routing attacks are used to quickly alter the network topology of MANETs based on wired and wireless networks. Therefore, securing this network without infrastructure is a big problem. In recent years, experts from all over the worldhave paid particular attention to research on improving the performance of mobile ad-hoc networks (MANETs). Routing methods are especially crucial in a dynamic network environment like MANET for enhancing overall network performance. In addition to discussing the technical difficulties that protocol designers and network engineers must overcome, this paper offers insight into the possible applications of ad hoc networks. Routing, service and resource discovery, Internet access, billing, and security are some of these difficulties.

Investigation of Route Request Retries of AODV Routing Protocol in a Linear Wireless Ad Hoc Network

AODV is a reactive routing protocol that sets up routes between source and destination nodes as and whenneeded. The performance of AODV protocol depends on the choice of certain parameters including route requestretries which is, by default, set as two in the corresponding RFC. In the present work, the effect of Route RequestRetries (RRR) on a set of performance metrics viz. Normalized Routing Load (NRL), Average End-to-End Delay(AEED), Packet Delivery Ratio (PDR) and Throughput has been investigated for a linear ad hoc network of fivenodes. Three different scenarios have been investigated wherein middle node is made to remain stationary, mobilewith low mobility and mobile with high mobility. Mobility of the middle node is found to be having significanteffect on the performance of such linear ad hoc networks. RRR has no influence on the performance of linear adhoc network of stationary nodes. However, RRR is having significant effect on the performance of linear ad hocnetwork if a node is made mobile. Performance of such linear ad hoc network is also affected by the choice ofduration of simulation.

Enhance the performance of AODV routing protocol in mobile ad-hoc networks

Enhancing the quality of service is still facing various challenges due to nature and configuration of mobile ad-hoc network (MANET) such as free movement of nodes, unpredictable changes in network topology as no infrastructure exist in the network. The large usage of mobile ad-hoc network in various applications raises the demand to enhance the performance as well as reduce loss of packets through various factors. The routing protocols play the most important aspect in MANET. There are three kinds of routing protocols that are: reactive, proactive and hybrid that are utilized to optimize the network’s functionality. Ad-hoc on-demand Distance victor (AODV) routing protocol is the popular used to achieve best output result. The most important objectives of this paper are to enhance the performance of mobile ad-hoc network by using AODV protocol. This paper gives some changes in AODV routing protocols that’s assist the performance enhancement of AODV in mobile ad-hoc network. The simulation is carried out on the network simulator NS2 and the output result show the improved AODV has excellent performance in term of packet delivery ratio, secondly throughput, third is the routing overhead and finally is end to end delay.