Nodes In Mobile Ad Hoc Networks Research Articles

Hybrid Tasmanian Devil and Elephant Herding Model-Based Optimal Cluster Head Selection and Routing in MANET

MANETs (Mobile AdHoc Networks) have major problems due to the resource-constrained nature of mobile nodes. MANET topology is highly uncertain due to the mobility of MANET nodes that affect the stability of interconnected links. This scenario results in an increased traffic overhead which affects the routing protocol performance and results in increased energy consumption. A routing scheme designed for MANET should be able to handle energy depletion issues and nodes’ mobility. This paper designs two novel schemes to enhance energy efficiency and network lifetime by performing clustering and routing in MANET. The Hybrid Tasmanian devil and Elephant herding optimization (HTDEHO) is used for clustering the MANET nodes to minimize the overhead, enhance the stability of the network topology, and reduce collision. The HTDEHO selects the optimal cluster head (CH) from a set of nodes based on their fitness value calculated by various parameters such as mobility-based node ranking, residual energy, distance, node degree, and optimal next hop CH selection. Dwarf mongoose optimization algorithm with Fuzzy variable (FDMO) algorithm selects optimal routing cost from CH to the base station based on various parameters such as throughput, delay, and distance. The efficiency of the proposed model is evaluated with different performance metrics such as energy consumption, throughput, end-to-end delay, and packet-dropping analysis. The performance of the proposed HTDEHO-FDMO classifier is compared with different techniques such as RDOAICRP, BFOA, MARP-HO, and FEKHO-QBA. Even after 170 iterations, the HTDEHO model retains a total of 10 alive nodes.

Detection of sequence number attacks using enhanced AODV protocol in MANETs

A Mobile Adhoc NETwork (MANET) operates without dedicated routing hardware, relying instead on dynamic wireless connections among nodes that can join or leave the network at any time. This dynamic nature demands a flexible routing protocol to manage variable number of nodes effectively. However, the absence of centralized infrastructure in MANETs poses security challenges, leaving nodes vulnerable to attacks. While several security solutions have been proposed, many face practical limitations. This paper introduces a novel approach to detect attacks on the Ad Hoc On-Demand Distance Vector (AODV) routing protocol within MANETs, specifically those involving malicious nodes masquerading as best routing paths by manipulating AODV's sequence numbers. An extension to the AODV protocol is introduced to ensure secure communication between different nodes in MANET. The proposed security mechanism includes a signature verification mechanism based on the Edwards digital signature curve (Ed25519), which is demonstrated on the Objective Modular Network Testbed in C++ (OMNet++) simulator. Our solution employs an extension to AODV protocol where asymmetric cryptography is introduced to generate and authenticate digital signatures, ensuring a high level of security. Additionally, a novel detection mechanism is introduced to identify malicious nodes within the network as a supplementary security layer. Simulation results demonstrate a high detection rate, accurately identifying between 83 % and 100 % of malicious nodes based on their presence in the network.

Adaptive radio propagation model for maximizing performance efficiency in smart city disaster management application

Climate change poses several environmental threats like floods to urban environment; thus, effective and reliable communication of emergency information is needed during massive breakdown of network infrastructure. This paper presents a mobile adhoc network (MANETs) based effective information such as calls, image, and videos communication system that is compatible with current 3GPP and 5G communication network. Here in maintaining connectivity the information is communicated between different MANET nodes in a multi-hop manner. However, designing radio propagation is challenging considering higher local emergency request congestion at different terrain with varying speed of users. The current radio propagation model is designed without considering the effect of line-of-sight between communicating device and are not adaptive to different environment considering urban disaster management environment. This paper develops an adaptive radio propagation (ARP) model namely expressway, city and semiurban. Then, in reducing congestion and improving network performance efficiency the work introduced an adaptive medium access control (AMAC) protocol. The MAC incorporates a dynamic network controller (DNC) to optimize the contention window size in dynamic manner according to current traffic demands. The AMAC protocol achieves much improved throughput with lesser packet loss in comparison with existing MAC (EMAC) model considering different radio propagation model introduced in this work.

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.

An artificial immune system‐based algorithm for selfish node detection in Mobile Ad Hoc Networks (MANETs)

AbstractThe Mobile Ad Hoc Network (MANET) depending on dynamic distributed topology presents several challenges such as decentralized infrastructure. In MANET, each node act as a host as well as a router to exchange packet. From Source to destination, the MANET nodes offer the ability of transmission to send, receive, and route traffic. Moreover, the presence of selfish nodes or malicious nodes in MANETs significantly degrades network performance. Identifying and isolating such nodes poses a formidable challenge. Consequently, this research introduces a security model founded on the principles of an Artificial Immune System (AIS) to detect and defend against Selfish Node (SN) attacks. This research work employs the principles of AIS to categorize a node's behavioral state based on the Mature Context Immune Antigen Rate (MCIAR). Subsequently, a hybrid protocol named Reliable History‐dependent Resource Conscious Clustered and Defensive AODV (RRCC‐DAODV) is introduced to detect Selfish Nodes (SNs) and counteract their attacks. Within the RRCC algorithm, the identification of selfish nodes relies on both Trust Value (TV) and Residual Energy (RE). Additionally, the proposed DAODV protocol incorporates the V‐detector algorithm to enhance defense mechanisms against potential attacks. The simulation of the proposed model is carried out in NS3. The proposed mechanism achieves a detection ratio of 94.05%. The simulation outcomes demonstrate the excellence of the implemented system. This superiority is observed when compared to other standard protocols, as indicated by the parameters of throughput, residual energy, packet delivery ratio, and delay.

Optimizing Path Selection in Dynamic Autonomous Mobile Ad Hoc Networks: A Clustering Approach for Variable Nodes

The dynamic autonomous mobile ad hoc networks (MANETs) allow nodes to move everywhere quickly and communicate without the support of a network infrastructure. The movement of mobile nodes in MANETs leads to several issues, such as changeable topology, energy limitations, path conservation, and bandwidth ineffectiveness. This would negatively impact the network’s QoS. The primary aim of the present study is to select the optimal path in MANETs using the clustering technique for variable nodes (i.e., 100–1000). The network performance characteristic and energy efficiency of the present ORSMAN protocol are simulated in the ns3 simulator. The research results demonstrate that compared to the current OPSTSA, EAAORS, EERS, and OEERS techniques, the suggested ORSMAN has a higher packet delivery ratio, the lowest latency, the lowest jitters, and superior throughput. The maximum improvement in throughput is 29.81%, and in energy efficiency, it is 9.67% compared to current techniques. Additionally, a trade‐off study between energy efficiency and QoS reveals that the performance characteristics enhance QoS while reducing energy efficiency. This reduction may be attributed to variations in throughput, jitter, and latency. The total QoS performance was improved by 22.16% for the present study compared to the current techniques.

Secure and efficient intelligent transport system based on cryptographic authentication mechanism for vehicular ad hoc networks

Vehicular Adhoc Networks (VANETs) are two of the future’s most commonly used communication systems. VANETs are designed to protect vehicle drivers by establishing autonomous contacts with nearby vehicles. Vehicles operate as intelligent mobile nodes in adhoc networks characterized by mobility and complexity. Cybersecurity in VANET is affected by malicious attacks, which must be detected and prevented. The overall performance of the proposed GPCR-MA with blackhole and Sybil attack is average latency, packet transmission ratio, energy consumption and throughput. It is predicted because the Blackhole attack vehicle sends answers instantly without checking its routing table. These changes in the metrics used contribute to the network efficiency deteriorating primarily in the face of an attack. Compared with other related schemes, our proposal provides privacy and security guarantees for VANETs while improving efficiency.

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.

Krill Herd and Feed Forward Optimization System-Based Routing Protocol for IoT-MANET Environment

The Internet of Things (IoT) is a developing technology in the world of communication and embedded systems. The IoT consists of a wireless sensor network with Internet service. The data size of the sensor node is small, but the routing of the data and energy consumption are important issues that need to be advocated. The Mobile Adhoc Network (MANET) plays a very important role in IoT services. In MANET, nodes are moving within the network. So, routes are created dynamically on demand and do not have any centralized units. The route optimization method addresses issues like selecting the best routes in terms of overhead, loop free, traffic control, balancing, throughput, route maintenance, and so on. In this paper, IoT routes are created between sensors to sink through MANET nodes with WSN routing ideology. The Krill Herd and Feed Forward Optimization (KH-FFO)-based method discovers the routes. The Krill herd algorithm clusters the network. This method increases network speed and reduces energy waste. Feed-forward optimization involves learning all the nodes in the network and identifying the shortest and most energy-efficient route from source to sink. The overall performance of the KH-FFO protocol has improved the network’s capacity, reduced packet loss, and increased the energy utilization of the nodes in the network. The ns-3 simulation for KH-FFO is tested in different node densities and observed energy utilization is increased by 28%, network life is increased by 7%, Packet delivery ratio improved by 7.5%, the End-to-End delay improved by 31% and the Throughput is 3%. These metrices are better than the existing works in the network.

MANET Hidden and Exposed Terminal - Challenges and Survey

Mobile Adhoc Network (MANET)is a self organized wireless Network which was created to communicate among the nodes without support of the any Infrastructure. While transmission of the packets between the nodes, many challenges the every nodes faces. One of the Major challenges is Hidden and Exposed nodes issues in the MANET. This causes the packet drop or packet failure while the transmitting the packets. Also which reflects in degrades the throughput of the MANET and performance of the MANET nodes when the heavy traffic ,retransmission of the dropped packets delayed the communication. This article discussed about hidden and Exposed terminal problem and challenges in MANET and also dissimilar survey in MANET.

Analysis of Behavioral Characteristics of Jammers to Detect Malicious Nodes in Mobile ADHOC Networks

Wireless ADHOC Networks are used to establish a wireless connection between two computing devices without the need for a Wi-Fi access point or router. This network is decentralized and uses omnidirectional communication media, which makes it more vulnerable to certain types of attacks compared to wired networks. Jamming attacks, a subset of denial-of-service (DoS) attacks, involve malicious nodes that intentionally interfere with the network, blocking legitimate communication. To address this issue, the proposed method analyzes various characteristics of nodes, such as packets sent, received, and dropped, at each node. Using the packet delivery ratio and packet drop ratio, the method detects jamming nodes from normal nodes, improving network performance. The network is simulated in NS2 environment.

Integrating interval type‐2 fuzzy logic and modified dingo optimization for node ranking and energy efficient MANET

AbstractIn mobile ad hoc networks (MANET), the mobility of the node changes dynamically, thus affecting the stability of the connection and increasing energy consumption. The heterogeneity of the MANET nodes in terms of mobility, battery capacity, and processing capabilities often complicates the routing process and results in increased energy consumption and traffic overhead. To overcome the challenges associated with diverse MANET nodes, this article presents a hybrid interval type‐2 fuzzy logic controller and modified dingo optimization (IT2FLC‐MDO) algorithm‐based optimized link‐state routing protocol. In our proposed IT2FLC‐MDO algorithm, multiple Quality of Service (QoS) parameters (node distance, lifetime, residual energy, speed, queue length, etc) are integrated into a single multicriteria node metric to improve the multipath route analysis and topology formation. In this way, the need to broadcast multiple parameters for each session is reduced thus minimizing the control overhead. The proposed routing protocol mainly aims to achieve a tradeoff between the QoS metrics and energy consumption during data transmission, addresses the QoS and energy issues associated with multipath routing, and uses a multicriteria node metric. The proposed IT2FLC‐MDO protocol takes both the energy consumption and QoS parameters into account, thus achieving a balance between the energy consumption and QoS. The cluster head primarily chooses the path with the highest link quality to ensure reliable data transmission. The proposed IT2FLC‐MDO protocol's efficiency is demonstrated using several performance measures such as packet delivery ratio, average end‐to‐end delay, and normalized control overhead. The simulation results indicate that the proposed algorithm can handle MANET uncertainty while minimizing control overhead. The results show that the proposed algorithm offers a packet delivery rate nearly equal to 96% and improves the MANET's lifetime by up to 59%.

Impact of Jellyfish attack on routing protocols in TCP-based MANETs

Mobile ad-hoc networks (MANETs) are self-organized infrastructure-less network of mobile wireless devices that could be deployed for communication. Due to the insecure wireless communication medium, multi-hop routing communication process, and dynamic behavior of the nodes in MANETs, routing protocols are vulnerable to various security attacks, such as Jellyfish attacks. A Jellyfish node targets TCP-based MANET and exploits its working mechanism to degrade the communication performance. This attack is hard to detect since it is a TCP protocol compliant methodology.In this paper, we evaluate the performance of the Ad hoc on-demand vector (AODV), Dynamic source routing (DSR), Temporally ordered routing algorithm (TORA), Geographic routing protocol (GRP), and optimized link state routing (OLSR) routing protocols under the Jellyfish delay variance attacks for TCP-based MANETs. Further, the TAHOE, RENO, and SACK variants of TCP protocol are considered for comparison. These routing protocols are simulated using the OPNET simulator to compare their performance, using specific performance metrics on the network. The experimental results show that the AODV protocol performs better than the DSR, TORA, OLSR, and GRP protocols under the jellyfish delay variance attack. Further, the SACK TCP variant performs better than the other TCP variants under the Jellyfish delay variance attack.

An Intrusion Detection Mechanism for MANETS based on Deep Learning Artificial Neural Networks (ANNS)

Mobile Ad-hoc Network (MANET) is a distributed, decentralized network of wireless portable nodes connecting directly without any fixed communication base station or centralized administration. Nodes in MANET move continuously in random directions and follow an arbitrary manner, which presents numerous challenges to these networks and make them more susceptible to different security threats. Due to this decentralized nature of their overall architecture, combined with the limitation of hardware resources, those infrastructure-less networks are more susceptible to different security attacks such as black hole attack, network partition, node selfishness, and Denial of Service (DoS) attacks. This work aims to present, investigate, and design an intrusion detection predictive technique for Mobile Ad hoc networks using deep learning artificial neural networks (ANNs). A simulation-based evaluation and a deep ANNs modelling for detecting and isolating a Denial of Service (DoS) attack are presented to improve the overall security level of Mobile ad hoc networks.

Trust based Secure and Reliable Routing Protocol of Military Communication on MANETs

An entirely new and trendy peer-to-peer modern communications graph is called a Mobile Ad-hoc Network (MANET). The MANETs form their network without any infrastructure facilities, whenever needed. Military activities frequently need the quick and secure transfer of large quantities of data. The radio spectrum has been used by the military up until now for good communication but might have a chance to impact security problems. The security of data transfer is a major issue given the natural component of wireless networks in real-time situations. The main challenge is confirming trust across MANET nodes, as well as dealing with bandwidth, energy, and changing topology. By degrading the trust level between nodes, the malicious attitude increases poor data transmission, increases energy use, and reduces the duration of the network. To address this issue, we proposed a new protocol, Trust-based Secure and Reliable Routing Protocol (TSRRP), to increase the trust between nodes in MANETs and predict anomalous activity. This is done with the help of certain Quality of Service (QoS) metrics, such as the result analysis phase. NS2 is used to simulate the result. The simulation outcomes demonstrate how the suggested protocol performs better than the existing protocols.

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.

Hybrid Trust Based Reputation Mechanism for Discovering Malevolent Node in MANET

A self-contained connection of wireless links that functions without any infrastructure is known as Mobile Ad Hoc Network (MANET). A MANET’s nodes could engage actively and dynamically with one another. However, MANETs, from the other side, are exposed to severe potential threats that are difficult to counter with present security methods. As a result, several safe communication protocols designed to enhance the secure interaction among MANET nodes. In this research, we offer a reputed optimal routing value among network nodes, secure computations, and misbehavior detection predicated on node’s trust levels with a Hybrid Trust based Reputation Mechanism (HTRM). In addition, the study designs a robust Public Key Infrastructure (PKI) system using the suggested trust evaluation method in terms of “key” generation, which is a crucial component of a PKI cryptosystem. We also concentrate on the solid node authenticating process that relies on pre-authentication. To ensure edge-to-edge security, we assess safe, trustworthy routes to secure computations and authenticate mobile nodes, incorporating uncertainty into the trust management solution. When compared to other protocols, our recommended approach performs better. Finally, we use simulations data and performance evaluation metrics to verify our suggested approach’s validity Our approach outperformed the competing systems in terms of overall end-to-end delay, packet delivery ratio, performance, power consumption, and key-computing time by 3.47%, 3.152%, 2.169%, and 3.527%, 3.762%, significantly.

A Novel Gradient Boosted Energy Optimization Model (GBEOM) for MANET

Mobile Ad Hoc Network (MANET) is an infrastructure-less network that is comprised of a set of nodes that move randomly. In MANET, the overall performance is improved through multipath multicast routing to achieve the quality of service (quality of service). In this, different nodes are involved in the information data collection and transmission to the destination nodes in the network. The different nodes are combined and presented to achieve energy-efficient data transmission and classification of the nodes. The route identification and routing are established based on the data broadcast by the network nodes. In transmitting the data packet, evaluating the data delivery ratio is necessary to achieve optimal data transmission in the network. Furthermore, energy consumption and overhead are considered essential factors for the effective data transmission rate and better data delivery rate. In this paper, a Gradient-Based Energy Optimization model (GBEOM) for the route in MANET is proposed to achieve an improved data delivery rate. Initially, the Weighted Multi-objective Cluster-based Spider Monkey Load Balancing (WMC-SMLB) technique is utilized for obtaining energy efficiency and load balancing routing. The WMC algorithm is applied to perform an efficient node clustering process from the considered mobile nodes in MANET. Load balancing efficiency is improved with a higher data delivery ratio and minimum routing overhead based on the residual energy and bandwidth estimation. Next, the Gradient Boosted Multinomial ID3 Classification algorithm is applied to improve the performance of multipath multicast routing in MANET with minimal energy consumption and higher load balancing efficiency. The proposed GBEOM exhibits ∼4% improved performance in MANET routing.

Timer Entrenched Baited Scheme to Locate and Remove Attacks in MANET

The Mobile Ad-hoc Network (MANET) is a dynamic topology that provides a variety of executions in various disciplines. The most sticky topic in organizational fields was MANET protection. MANET is helpless against various threats that affect its usability and accessibility. The dark opening assault is considered one of the most far-reaching dynamic assaults that deteriorate the organization's execution and reliability by dropping all approaching packages via the noxious node. The Dark Opening Node aims to deceive any node in the company that wishes to connect to another node by pretending to get the most delicate ability to support the target node. Ad-hoc On-demand Distance Vector (AODV) is a responsive steering convention with no corporate techniques to locate and destroy the dark opening center. We improved AODV by incorporating a novel compact method for detecting and isolating lonely and collaborative black-hole threats that utilize clocks and baits. The recommended method allows MANET nodes to discover and segregate black-hole network nodes over dynamic changes in the network topology. We implement the suggested method's performance with the help of Network Simulator (NS)-3 simulation models. Furthermore, the proposed approach comes exceptionally near to the original AODV, absent black holes in terms of bandwidth, end-to-end latency, error rate, and delivery ratio.

Comparative Analysis of TCP, TCP-Vegas, and SCTP in Mobile Ad-Hoc Networks

Mobile Ad hoc Networks (MANET) is a collection of mobiles and smart devices that communicates using wireless links. These types of networks are growing at the lightning speed and are being used at a large scale than ever before because of their high availability and mobility. As the usage of MANET devices increase, the challenges also increase for example the proper delivery of data or information to every mobile node. Traditionally, transmission control protocol (TCP) is used for delivery but it does not fit in all scenarios due to some of its limitations such as network congestion and quick recovery in case of link failure. In this, a comparative analysis of TCP is performed with the stream control transmission protocol (SCTP) and a TCP variant called TCP VEGAS. Several ad hoc scenarios are proposed with varying numbers of mobile nodes, i.e. 11, 21 and 31. The results obtained indicate that SCTP outperforms TCP and VEGAS in throughput. While using SCTP the packet lifetime is also small i.e. 0.19 seconds. The link utilization of SCTP is better than TCP and VEGAS. However, TCP increases its link utilization more than VEGAS for the nodes in MANET of large delay.