Performance Of Mobile Ad Hoc Networks Research Articles

IoT-based MANET performance improvement against jamming attackers in different mobile applications

Internet of Things (IoT) is a cutting-edge technology and effective solution that enables real-time communication between physical objects. In order to manage the mobility of nodes in the IoT, mobile ad hoc networks (MANETs) are crucial. It enables IoT-based systems to construct and connect networks autonomously. IoT based MANET is more vulnerable to Jamming attacks (Jammers) due to the decentralized nature of the ad hoc network. Therefore, secure communication is a crucial requirement for nodes. In this paper, jammers interfere with the IoT MANET communication resulting in order to degrade network performance in terms of delay, throughput and PDR (Packet Delivery Rate) which are the important QoS (Quality of Service) parameters to measure the network performance. The IoT ad hoc system's networking is based on MANET routing protocols so that (GRP, AODV and OLSR) routing protocols had been examined in this paper to improve the QoS (Packet Delivery rate, throughput and delay) of the IoT-MANET system using Riverbed Modeler (17.5) simulation program for different mobile applications. The outcomes showed that the selection of a suitable routing protocol would improve the degradation in delay, throughput and PDR of the ad hoc network.

Enhancing MANET Performance: A Novel Approach Through Nature-Inspired Scheduling Algorithms

In the rapidly evolving landscape of Mobile Ad Hoc Networks (MANETs), the quest for optimal performance through efficient scheduling remains paramount. This paper, titled "Enhancing MANET Performance: A Novel Approach Through Nature-Inspired Scheduling Algorithms," introduces an innovative methodology that leverages the intricate mechanisms of nature to address the complex challenges inherent in MANET scheduling. Drawing inspiration from the adaptive behaviors observed in natural systems, we have developed a suite of nature-inspired algorithms—encompassing the genetic algorithm, particle swarm optimization, and ant colony optimization—tailored specifically to enhance the scheduling efficiency within the dynamic and decentralized context of MANETs.
 Our research undertakes a comprehensive evaluation of these algorithms against traditional scheduling methods, showcasing a notable improvement in key performance metrics such as network throughput, latency, and energy consumption. The novel contribution of this study lies in the adaptation and optimization of these bio-inspired algorithms for the unique demands of MANET scheduling, culminating in the development of a proprietary analytical model that significantly outperforms existing strategies. Through a rigorous comparative analysis, our results illuminate the superiority of our approach, demonstrating not only enhanced network efficiency but also improved scalability and reliability under varying conditions.
 The implications of this research extend beyond the immediate enhancements to MANET performance, proposing a paradigm shift in how scheduling challenges are approached within ad hoc networks. By bridging the gap between biological principles and technological applications, this study paves the way for future innovations in network management, offering a blueprint for the development of more adaptive, robust, and efficient networking solutions.

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.

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.

ADAPTIVE SECURE AND EFFICIENT ROUTING PROTOCOL FOR ENHANCE THE PERFORMANCE OF MOBILE AD HOC NETWORK

Nowadays Mobile Ad Hoc Network (MANET) is an emerging area of research to provide various communication services to end users. Mobile Ad Hoc Networks (MANETs) are self-organizing wireless networks where nodes communicate with each other without a fixed infrastructure. Due to their unique characteristics, such as mobility, autonomy, and ad hoc connectivity, MANETs have become increasingly popular in various applications, including military, emergency response, and disaster management. However, the lack of infrastructure and dynamic topology of MANETs pose significant challenges to designing a secure and efficient routing protocol. This paper proposes an adaptive, secure, and efficient routing protocol that can enhance the performance of MANET. The proposed protocol incorporates various security mechanisms, including authentication, encryption, key management, and intrusion detection, to ensure secure routing. Additionally, the protocol considers energy consumption, network load, packet delivery fraction, route acquisition latency, packets dropped and Quality of Service (QoS) requirements of the applications to optimize network performance. Overall, the secure routing protocol for MANET should provide a reliable and secure communication environment that can adapt to the dynamic nature of the network. The protocol should ensure that messages are delivered securely and efficiently to the intended destination, while minimizing the risk of attacks and preserving the network resources Simulation results demonstrate that the proposed protocol outperforms existing routing protocols in terms of network performance and security. The proposed protocol can facilitate the deployment of various applications in MANET while maintaining security and efficiency.

MANET Congestion Control Mechanism - Challenges and Survey

The transport layer plays a crucial role in the Mobile Adhoc Network (MANET) protocol stack by controlling traffic flow, managing congestion, and enabling end-to-end delivery. With the help of congestion control mechanisms, numerous protocols are formed to enhance MANET performance. This paper focuses on a thorough analysis of the challenges the MANET protocol stack is facing as a result of congestion control issues such high overload, long delays, and increased packet loss. Finally, note that in order to increase MANET performance, research needs to concentrate on specific congestion control mechanisms.

Design of NULLMAC Protocol for Mobile Ad Hoc Network Using Adaptive Antenna Array

Usually, omnidirectional radiation pattern antenna is used in the mobile ad hoc network (MANET) which causes neighbor node interference, consumes more power, and supports only limited range of transmission. To overcome these problems, smart antennas are used. A lot of medium access control (MAC) protocols are proposed using smart antennas. Existing works addressed various problems such as hidden terminal problem, hidden beam problem, deafness of nodes, and head of line blocking problem. However, certain factors including determination of weight vector and conveying it to the neighbor nodes for distortion-free transmission are not considered. In this study, nullifying MAC (NULLMAC) framework is proposed using an adaptive antenna array (AAA) for improving network performance in MANET. NULLMAC framework uses channel information for achieving high throughput and spatial reuse through integrated physical and MAC layer. Before the transfer of data packets, the receiver initially determines its weight vector and conveys it to the transmitter through control packets. Then, the transmitter computes its weight to nullify the dynamic receivers present in the neighborhood region to find the desired receiver. Beamformer weights are determined through channel coefficients between a transmitter-receiver pair to establish distortion-free transmission. Extensive simulations are performed using OPNET integrated with MATLAB. NULLMAC framework achieves 27.22% more throughput and 40.46% increase in signal-to-noise ratio.

Improved QoS-Secure Routing in MANET Using Real-Time Regional ME Feature Approximation

Mobile Ad-hoc Network (MANET) routing problems are thoroughly studied several approaches are identified in support of MANET. Improve the Quality of Service (QoS) performance of MANET is achieving higher performance. To reduce this drawback, this paper proposes a new secure routing algorithm based on real-time partial ME (Mobility, energy) approximation. The routing method RRME (Real-time Regional Mobility Energy) divides the whole network into several parts, and each node’s various characteristics like mobility and energy are randomly selected neighbors accordingly. It is done in the path discovery phase, estimated to identify and remove malicious nodes. In addition, Trusted Forwarding Factor (TFF) calculates the various nodes based on historical records and other characteristics of multiple nodes. Similarly, the calculated QoS Support Factor (QoSSF) calculating by the Data Forwarding Support (DFS), Throughput Support (TS), and Lifetime Maximization Support (LMS) to any given path. One route was found to implement the path of maximizing MANET QoS based on QoSSF value. Hence the proposed technique produces the QoS based on real-time regional ME feature approximation. The proposed simulation implementation is done by the Network Simulator version 2 (NS2) tool to produce better performance than other methods. It achieved a throughput performance had 98.5% and a routing performance had 98.2%.

Swarm Intelligence Based Routing with Black Hole Attack Detection in MANET

Mobile Ad hoc Network (MANET) possesses unique characteristics which makes it vulnerable to security threats. In MANET, it is highly challenging to protect the nodes from cyberattacks. Power conservation improves both life time of nodes as well as the network. Computational capabilities and memory constraints are critical issues in the implementation of cryptographic techniques. Energy and security are two important factors that need to be considered for improving the performance of MANET. So, the incorporation of an energy efficient secure routing protocol becomes inevitable to ensure appropriate action upon the network. The nodes present in a network are limited due to energy constraints and secure communication protocols. Hence, the current study proposed an energy-efficient defense scheme using swarm intelligence approach. The functioning of the proposed method was validated under NS2 simulation. The experimental results confirmed that the proposed work outperformed existing methods in terms of packet delivery ratio, average end-to-end delay and throughput.

Improvisation of Node Mobility Using Cluster Routing-based Group Adaptive in MANET

In today's Internet routing infrastructure, designers have addressed scaling concerns in routing constrained multiobjective optimization problems examining latency and mobility concerns as a secondary constrain. In tactical Mobile Ad-hoc Network (MANET), hubs can function based on the work plan in various social affairs and the internally connected hubs are almost having the related moving standards where the topology between one and the other are tightly coupled in steady support by considering the touchstone of hubs such as a self-sorted out, self-mending and self-administration. Clustering in the routing process is one of the key aspects to increase MANET performance by coordinating the pathways using multiple criteria and analytics. We present a Group Adaptive Hybrid Routing Algorithm (GAHRA) for gathering portability, which pursues table-driven directing methodology in stable accumulations and on-request steering strategy for versatile situations. Based on this aspect, the research demonstrates an adjustable framework for commuting between the table-driven approach and the on-request approach, with the objectives of enhancing the output of MANET routing computation in each hub. Simulation analysis and replication results reveal that the proposed method is promising than a single well-known existing routing approach and is well-suited for sensitive MANET applications.

Enhancement of the performance of MANET using machine learning approach based on SDNs

Deep learning (DL) is a subdivision of machine learning (ML) that employs numerous algorithms, each of which provides various explanations of the data it consumes; mobile ad-hoc networks (MANET) are growing in prominence. For reasons including node mobility, due to the potential wireless sensor network (WSN) to provide a small-cost solution to real-world contact challenges. But the lifespan in this network is restricted lifespan. Therefore, the wireless sensor network (WSN) is more vulnerable to battery consumption. On the other hand, routing packets in a Wireless Sensor Network (WSN) is a challenging task, according to the limited resources available on the nodes of these networks, especially their energy sources. The use of Machine Learning (ML) techniques in a Software-Defined Network (SDN) topology has shown good potential for solving such a complex task. However, existing techniques emphasize finding the shortest paths to deliver the packets, which can overload certain nodes in the network, depending on their positioning. In this study, a new method is proposed to extend the lifetime of the WSN by balancing the loading on the nodes, using a Deep Reinforcement Learning (DRL) approach. By emphasizing the lifetime of the network, the proposed method has been able to discover and use alternative routes to deliver the packets, avoiding the use of nodes with low energy. Hence, the average number of hops the packets travel through has been increased, but the time required for the first node to exhaust its energy has been significantly increased.

A Neighbor Trust Weight Based Cryptography for Multi Key Distribution for Improving Quality of Service in MANETS

A Mobile Ad-Hoc Network (MANET) is a self-configuring network that provides temporary connections to several wireless nodes. Trust mechanisms are employed in routing protocols to quickly locate a safe path. Because of its openness and complexity, MANET can be attacked in a number of ways. To begin mitigating potential security risks, a number of different cryptographic key generation strategies are explored. A key management system for MANET security is available with different encryption techniques. Identity with Trust Level based Cryptography Model (ITLCM) is used to generate multiple keys and distribute these to particular targets. At this stage, key management protocols are essential to any secure group architecture of communication. Because of its dynamic topology which extensively affects its application, the multi key management is an essential task. When compared to more conventional methods of protecting a network, MANET security is entirely novel. Security routing protocol implementation is difficult since it requires the production and distribution of multiple keys. To provide both connection and message protection without relying on third parties, the Neighbor Trust Weight based Routing Model (NTWRM) is designed. In the proposed model, a trusted node is selected to monitor all of the nodes in the routing process to create a stable multi-key distribution environment that enhances MANET performance. In comparison with traditional methods, the proposed model shows that its findings are better than the existing ones.

Sustainable Multipath Routing for Improving Cross-Layer Performance in MANET Using an Energy Centric Tunicate Swarm Algorithm

Generally, battery power is a valuable resource for mobile devices in a Mobile Ad Hoc Network (MANET). Therefore, energy efficiency and network lifetime should be taken into account when developing control strategies. However, designing an energy-efficient routing mechanism necessitates consideration of many nodes from many layers, such as remaining energy, overall traffic load, and channel assumptions. The traditional layered strategy is unsuccessful in dealing with power-related issues that might affect all layers of the stack. In this paper, the Energy Centric Tunicate Swarm Algorithm (ECTSA) is proposed to perform the cross-layer routing over MANET. The fitness metrics considered in the ECTSA to improve the cross-layer routing are residual energy, communication cost, Data Success Rate (DSR), and mobility. Additionally, an Adaptive Competition Window (ACW) adjustment is used for minimizing the energy consumption caused by the contentions. The performance of the proposed ECTSA is analyzed by means of energy consumption, Packet Delivery Ratio (PDR), End-to-End Delay (EED), and routing overhead. Next, the existing techniques, namely, CEELBRP and EECRP-PSO, are used to evaluate the efficiency of the ECTSA method. The energy consumption of the ECTSA is 7.1 joules and prolongs the network lifetime up to 1603 s for 50 nodes, which is better when compared to the existing CEELBRP and EECRP-PSO techniques.

Detection and Isolation of Selfish Nodes in MANET Using Collaborative Contact-Based Watchdog with Chimp-AODV

Mobile Ad-hoc Network (MANET) is one of the most important self-configuring and independent wireless network. Numerous intermediate nodes are used among MANET to interchange the information without the requirement of any centralized infrastructure. But some nodes act selfishly and utilize the resources only for their own purposes and do not share with the neighbors. This selfish nodes might delay or drop the packet and do not perform routing. Though watchdog is a well-known selfish node detection technique, it causes false negatives and false positives that can affect the performance in terms of precision and speed. To eliminate the drawbacks of existing approaches in selfish node detection, this paper integrates both Ad-hoc On-Demand Distance Vector (AODV) protocol incorporated with chimp optimization algorithm and Collaborative Contact based Watchdog to propose a novel technique called Chimp-CoCoWa-AODV in order to improve the performance of MANET. The main role of chimp optimization algorithm in AODV is to undergo optimal route selection process. The performance of the proposed Chimp-CoCoWa-AODV approach is compared with existing approaches in terms of average routing load, Average Packet Delivery Fraction (PDF), Average End-to-end Delay (EED), Average Throughput, Total packet drop in the application layer, and maliciously dropped packet in the routing layer. The simulation results shows that the proposed approach is effective with 82% PDF and 7.4 ms EED at 50 nodes in detection and isolation of selfish nodes in MANET even in the presence of malicious node.

An improved performance routing protocol based on delay for MANETs in smart cities

Mobile ad-hoc networks (MANETs) is a set of mobile devices that can self-configuration, self-established parameters to transmission in-network. Although limited inability, MANETs have been applied in many domains to serve humanity in recent years, such as disaster recovery, forest fire, military, intelligent traffic, or IoT ecosystems. Because of the movement of network devices, the system performance is low. In order to MANETs could more contribution in the future of the Internet, the routing is a significant problem to enhance the performance of MANETs. In this work, we proposed a new delay-based protocol aim enhance the system performance, called performance routing protocol based on delay (PRPD). In order to analyze the efficiency of the proposed solution, we compared the proposed protocol with traditional protocols. Experiment results showed that the PRPD protocol improved packet delivery ratio, throughput, and delay compared to the traditional protocols.

Tuning the Evaporation Parameter in ACO MANET Routing Using a Satisfaction-Form Game-Theoretic Approach

A Mobile Ad Hoc Network (MANET) is a communication network that links communicating devices (nodes) and does not contain permanent infrastructure. There are no dedicated routing devices in MANETs, where the routing task is assigned to a routing algorithm installed on all communicating nodes. In this work, communicating nodes utilize one of the most widely used algorithms: Ant Colony Optimization (ACO) routing algorithms. The ACO algorithms aim to balance between exploring new routes for the communication packets vs. utilizing the best-known routes discovered during the communication session. Achieving the optimality in this tradeoff is traditionally set manually by assigning many values to some parameters and measuring the network performance after the simulation session. This manual optimality tuning approach depends on human intuition and does not cope with MANET’s dynamic topology. In this research, we introduce a novel method to find an optimal balance for the exploration-exploitation tradeoff during the communication session. We formulate weighing the benefits of exploring new routes vs. exploiting known ones upon the MANET performance as a game between the two semantic players. This equilibrium is reflected as an optimal value for the pheromone evaporation parameter of the ACO algorithm during the communication session. Experimental results show a higher performance of this online tuning algorithm than the traditional offline tuning algorithms.

Performance analysis of multicast routing using multi agent zone based mechanism in MANET

Mobile Ad-Hoc Network (MANET) is a structure less and emerging technology in recent years. Generally, this structure forms a network with nodes with inherent characteristics, including resource heterogeneity, node reliability, etc. In this manuscript, we proposed a Multi-Agent-Based Zone Routing (MAZR) protocol for enhancing the performance of MANET. Our proposed MAZR is works based on the principle of packet forwarding through intermediate and zone leaders. It consists of multiple agents, which include static and dynamic mobile agents. The proposed implementation is done as follows: Initially discovering the zone leader’s .The discovered zone leaders are connected to the communication nodes. The communication nodes and zone leaders are associated for building the network backbones for achieving multicast routing .To the multicast, zone members are connected .The zone managements, backbone and highly mobile nodes are initiated. The proposed MAZR protocol comprises five types of agents: Path agent, Network control agent, Multicast control agent, Network launch agent, and Multicast control agents. The Path agent, Network control agent, and Multicast control agent are static, and Network launch agents and Multicast control agents are mobile. The future protocol's performance is determined using the experimental work based on the evaluation metrics like delay, power consumption, and network lifetime. The obtained results prove the future MAZR is far improved than the Zone-based Hierarchical Link Protocol and Zone Routing Protocol in all aspects and ensures flexibility with versatile multicast service.

Trust-Based Security: Advancement towards Protection of the Adhoc Network

MANET (mobile ad hoc network) is a collection of mobile nodes that interact without the need for a fixed physical foundation. MANETs have grown in popularity as a result of characteristics like dynamic topology, quick setup, multi-hop data transfer, and so on. MANETs are well-suited to various real-time applications, including environmental monitoring, disaster management, and covert and military operations, because of their distinguishing characteristics. MANETs may also be used in conjunction with new technologies like cloud computing, IoT, and machine learning algorithms to help realize the vision of Industry 4.0. Secure and reliable data transfer is essential for any MANET-based sensitive real-time applications that must achieve the requisite QoS. It is challenging to provide safe and efficient data transfer with MANET. As a result, this article examines different Trust-based Approaches that take a step forward in providing secure transmission while simultaneously improving MANET performance. Furthermore, the study's analysis based on many aspects exposes the inadequacies of existing techniques and provides future directions for improvement.

Data Broker: Dynamic Multi-Hop Routing Protocol in Blockchain Radio Access Network

Mobile ad-hoc network (MANET) is an infrastructure-less extended scenario of blockchain radio access network (B-RAN); meanwhile, the decentralization of B-RAN befits MANETs. In the framework of B-RAN, we propose a blockchain-based multi-hop routing protocol, namely Data Broker, for non-cooperative MANETs. To incentivize the collaboration among selfish peers, we record the identity information of participating brokers on a ledger list. However, blockchain cannot guarantee the integrity of such a routing ledger directly. Therefore, we design a ledger safeguard mechanism, along with reward policies, to avoid the ledger list being tampered with or modified by dishonest brokers. The experimental results show that the proposed Data Broker can significantly improve the network performance of non-cooperative MANETs regarding latency and loss rate.

An adaptive multi-hop routing with IoT abstraction for minimizing delay-node capacity trade-offs in mobile ad-hoc network

<span>Delay and node capacity are incompatible mobile ad hoc constraints because of the network's versatility and self-disciplined design. </span><span>It is a challenging problem to maximize the trade-off between the above mobility correlation factors. </span><span>This manuscript proposes an adaptive multi-hop routing (A.M.R.) for mobile ad-hoc network (MANET) to minimize the trade-off by integrating the internet of things (IoT). IoT nodes' smart computing and offloading abilities are extended to ad-hoc nodes to improve routing and transmission. Dor MANET nodes in route exploration, neighbor selection, and data transmission, the beneficial features of IoT include enhanced decision making. The traditional routing protocols use IoT at the time of the neighbor discovery process in updating the routing table and localization. </span><span>The harmonizing technologies with their extended support improve the performance of MANETs has been estimated. The proposed method achieves better throughput (14.16 Mbps), delay (0.118), packet drop (126), and overhead (36 packets) when compared to existing methods.</span>