Mobile Ad Hoc Network Routing Research Articles

ENHANCING QUALITY OF SERVICE IN MANET ENVIRONMENTS WITH CRYPTOGRAPHIC SECURE MECHANISMS TO SECURE SUSTAINABLE SMART CITIES

The utilization of wireless sensor networks to gather, process, and act upon data may be a powerful tool in the development of a city-wide communication network that can accommodate many applications, ultimately leading to smart city solutions. Several challenges might be encountered by a smart city network. These include the need to adapt the network's coverage area to suit various applications, uneven distribution of nodes, a rise in message volume, the use of several communication technologies, and heterogeneity in both nodes and messages. There are many different facets of smart cities that are being studied, and certain applications are being created in each of them. Several options for smart city sensor networks are outlined in this article, which uses a survey format. Applications like ridesharing, emergency medical services, and others that depend on real-time traffic data supplied by the smart traffic domain are used to examine message transmission problems in this study. The versatility and speed with which Mobile Ad Hoc Networks (MANETs) may set up networks have led to their widespread use. Because mobile nodes function best in tandem and have faith in one another, we take a look at MANET routing algorithms and how they handle message transmission for this service.

Hybrid optimization-based Effective Path Selection and Multipath routing in MANETs

Mobile Adhoc Networks (MANETs) have emerged as a popular technology because of their wide application and independent mobility. Nevertheless, communication through MANETs can be effective because of their inherent nature of high mobility, which in turn results in a higher rate of data loss and delay. Therefore, for effective communication to be achieved, the MANETs’ routing performance must be enhanced. Some extant routing protocols like AOMDV can yield moderate Routing Overhead (RO) during communication. The review of previous studies shows that there is a need for improvement in the following areas: Computational E2E delay: the proposed Genetic Algorithm- Ant Colony Optimization (GA-ACO) was unable to reduce the computational E2E delay that occurs during communication. RO: The schemes that were proposed failed to minimize the RO in the network. Energy consumption: the reduction energy consumed by the network was reduced, however, high throughput and PDR could not be achieved by the method. On the contrary, the EHO-based AOMDV routing protocol achieved low E2E delay and RO but was unable to decrease the energy consumed by the network. Throughput and PDR: The protocol proposed failed to achieve high Quality of Services (QoS). Consequently, this paper aims to provide a solution to this communication problem by proposing a Hybrid Optimization-based Effective Path Selection and Multipath routing (HOEPSM) approach for MANETs. The proposed approach, which is HOEPSM is made up of two parts: Elephant Herding Optimization (EHO)-based AOMDV routing protocol, which makes use of EHO for the identification of the shortest path from the source to the destination. The second part which is the Hybrid optimization using Genetic Ant Optimization (GAO) algorithm, involves finding the best solution through the use of a GAO-based hybrid optimization algorithm. The results of the study revealed that the use of the HOEPSM causes a significant decrease in routing RO while enhancing the network’s Quality of Forwarding (QoF) of the network. Also, the simulation of the proposed approach was carried out in NS2, and afterward, compared with earlier proposed methods like DRARP and MDRARP. Based on the simulation results, the HOEPSM outperformed the other methods, with high Energy Efficiency (EE) (91%), Packet Delivery Ratio (PDR) (95%), RO (155), and End to End (E2E delay) (102ms). These results can be attributed to the HOEPSM’s choice of the best and steady route from the source nodes and destination nodes.

Hybrid optimization-based secured routing in mobile ad-hoc network

Mobile Ad hoc Networks (MANETs) pose significant routing challenges due to their decentralized and dynamic nature. Node mobility results in frequent changes in network topology, leading to unsFIG connectivity and link quality. Traditional RPs designed for static networks are inadequate for MANETs. To deal with these issues, a secure routing approach is proposed using the Red Panda-Lyrebrid Optimization (RePLO) algorithm, which combines the advantages of the Red Panda Optimization (RPO) and Lyrebird Optimization Algorithm (LOA) algorithms. The proposed approach consists of five steps: (i) configuring the system model, (ii) developing the energy model, (iii) creating the mobility model, (iv) selecting cluster heads using the RePLO algorithm, and (v) routing using the RePLO algorithm. The RePLO algorithm optimizes cluster head selection and routing while considering specific constraints such as delay, distance, energy, & security for Cluster Head (CH) selection, and link quality and enhanced trust for routing optimization. The effectiveness of the proposed approach is evaluated using various metrics to demonstrate its efficiency in MANET routing. By integrating multiple optimization techniques and considering critical constraints, the RePLO algorithm offers a systematic and secure solution for MANET routing. The evaluation results confirm the efficacy of the proposed approach in improving network performance, reliability, and security. Overall, the RePLO algorithm presents a promising approach to tackle the routing issues inherent in MANETs, paving the way for more robust and efficient communication in mobile ad hoc networks.

Evaluating the quality of service of Opportunistic Mobile Ad Hoc Network routing algorithms on real devices: A software-driven approach

Opportunistic Mobile Ad Hoc Networks (MANETs) offer versatile solutions in contexts where the Internet is unavailable. These networks facilitate the transmission between endpoints using a store-carry-forward strategy, thereby allowing information to be stored during periods of disconnection. Consequently, selecting the next hop in the routing process becomes a significant challenge for nodes, particularly because of its impact on Quality of Service (QoS). Therefore, routing strategies are crucial in opportunistic MANETs; however, their deployment and evaluation in real scenarios can be challenging. In response to this context, this paper introduces a monitoring software-driven tool designed to evaluate the QoS of routing algorithms in physical opportunistic MANETs. The implementation and its components are detailed, along with a case study and the outcomes provided by an implementation of the proposed solution. The results demonstrate the effectiveness of the implementation in enabling the analysis of routing protocols in real scenarios, highlighting significant differences with simulation results: mobility patterns in simulations tend to be inaccurate and overly optimistic, leading to a higher delivery probability and lower latency than what is observed in the real testbed.

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.

Secure Routing and Reliable Packets Transmission In MANET Using Fast Recursive Transfer Algorithm

Mobile Ad-hoc Network (MANET) autonomous operation can be multi-hop it is the infrastructure-less wireless network. Security is one of the biggest challenges in Mobile Adhoc Network. The MANETs security there are considerations must be so that the routing protocol in order to protect the secure data transmission. In the routing and security that is an important aspect for in a MANETs, existing method routing protocol, however, is not enough to security requirements. The proposed method using Fast Recursive Transmission Algorithm (FRTA) used designed to maximize the data security, routing optimization, minimizing the impact of malicious attack using Collision Detection Avoid Algorithm (CDAA) activity over the MANET and select the best path. Table-driven routing protocols, also known as proactive routing protocols, mandate that every node on the network keep up-to-date routing data. To maintain consistent routing information for network nodes, these protocols propagate frequent updates to the routing table throughout the network, necessitating changes to the network topology. There's a lot of overhead from these upgrades. The suggested FRTA algorithm lowers node data loss rates and increases network energy efficiency. Table-driven routing protocols, also known as proactive routing protocols, mandate that every node on the network keep up-to-date routing data. To maintain consistent routing information for network nodes, these protocols propagate frequent updates to the routing table throughout the network, necessitating changes to the network topology. There's a lot of overhead from these upgrades. The suggested FRTA algorithm lowers node data loss rates and increases network energy efficiency. The proposed method shows high performance than other existing evaluations of the most advanced security and routing energy, end-to-end delay, packet transfer rate, packet loss

Secure MANET routing with blockchain-enhanced latent encoder coupled GANs and BEPO optimization

ABSTRACT Mobile ad hoc networks (MANETs) facilitate rapid deployment due to independence from established infrastructure, relying instead on wireless technology where each node functions as a source, destination, or intermediary router. However, existing techniques fail to adequately address security and privacy concerns inherent in MANETs, rendering them impractical for real-world deployment. To tackle these challenges, this paper proposes the Blockchain Based Trusted Distributed Routing Scheme for MANET using Latent Encoder Coupled Generative Adversarial Network Optimized with Binary Emperor Penguin Optimizer (LEGAN-BEPO-BCMANET). This scheme leverages blockchain technology to establish a fair proof-of-reputation system, ensuring trusted and decentralized routing based on authenticated blockchain token transactions. By integrating Latent Encoder Coupled Generative Adversarial Network (LEGAN) optimized with Binary Emperor Penguin optimizer (BEPO), the scheme enhances routing efficiency and security. A comprehensive security analysis is performed focusing on aspects such as double-spending prevention, transaction distinguishability, routing information integrity, and self-modification resilience. The proposed approach is implemented in NS3 software, with evaluation metrics including throughput of blockchain token transactions and average energy consumption recorded. Overall, the LEGAN-BEPO-BCMANET scheme offers a robust solution to the security and efficiency challenges faced by MANETs, paving the way for practical deployment in real-world scenarios. The performance of the proposed LEGAN-BEPO-BCMANET technique attains 29.786%, 19.25%, 22.93%, 27.21%, 31.02%, 26.91%, and 25.61% greater throughput, compared to existing methods like Blockchain-based BATMAN protocol utilizing MANET with an ensemble algorithm (BATMAN-MANET), Block chain-based trusted distributed routing scheme with optimized dropout ensemble extreme learning neural network in MANET (DEELNN-MANET), A secured trusted routing utilizing structure of a new directed acyclic graph-blockchain in MANET internet of things environment (DAG-MANET), An Optimized Link State Routing Protocol with Blockchain Framework for Efficient Video-Packet Transmission and Security over MANET (OLSRP-MANET), Auto-metric Graph Neural Network based Blockchain Technology for Protected Dynamic Optimum Routing in MANET (AGNN-MANET) and Data security-based routing in MANETs under key management process (DSR-MANET) respectively.

Hybrid Clustering Approach (SG-MFOA) using Multipath Cross-Layer Design in MANET Network

Mobile Ad-hoc Networks (MANETs) are used in a wide range of applications because of their unique capabilities. The routing in MANET is regarded as a main challenge on account of its permanent movement and nodes' randomness that can cause a continual change of network topology, thus finding correct paths among the nodes is the fundamental task of routing protocols. There is a rise in protocols that depend on cross-layer communication across several layers to increase the MANET performance. In this manuscript, a Hybrid Clustering Approach (SG-MFOA) using a Multipath Cross-Layer Design in a MANET Network is proposed. Here, multiple routes are selected for data packet transmission with the help of hybrid routing. Furthermore, a cross-layer metric is acquired depending upon Expected Transmission Time (ETT), Residual Energy and Load Balancing Factor. It is necessary to select a Cluster Head (CH) depending on this trade for proficient routing. So, the cluster head is optimally chosen to utilize SG-MFOA. Thus, the multipath route selection is performed by the multi-objective functions containing bandwidth, congestion delay, transmission delay and to ensure the prolonging of network lifetime, queue delay at each connection Access Category from the available routes to a destination. When compared with the existing methods, like a proficient self-attention-based conditional variational auto-encoder generative adversarial networks-based multipath cross-layer design routing paradigm for MANET (SCVAGAN-MCDR-MANET), Energy Aware Cross Layer Routing Protocol to Increase Route Reliability in MANETs (EACLRP-RR-MANET), Cross-layer Adaptive Fuzzy-based Ad hoc On-Demand Distance Vector Routing Protocol for MANET (CLAF-DVRP-MANET), respectively.

A Deep Learning-Based Reliable Link Prediction Model for Achieving Traffic-Aware Routing in Mobile Ad-hoc Networks

One of the most promising wireless network architectures is the mobile ad-hoc network (MANET). Researchers have introduced enormous protocols for efficient routing, but it does not provide a reliable communication link for data transmission. Therefore, this research proposes a reliable link prediction-based traffic-aware deep learning routing protocol in MANET to maintain path stability and reliability to construct efficient routing. The reliable traffic-aware link prediction model used in this research is Fuzzy-based Deep Extreme [Formula: see text]-Learning (FDEQL) model. The fuzzy logic rule is used to compute the status of a wireless link to build stable and faster paths toward destinations. Traffic patterns can affect the efficiency of a node. So, to cope with the traffic pattern in MANET, the point-to-point (P2P) and end-to-end (E2E) traffic matrices are initially constructed. To evaluate whether the wireless link is reliable or not, the proposed approach utilizes fuzzy rules by considering essential parameters such as neighborhood overlap (NOVER), bipartivity index (BI), node mobility (NM), data rate (DR), received signal strength indicator (RSSI) and buffer occupancy (BO). The output is the [Formula: see text]-value for reliable link prediction. The performance of a proposed model is validated with other baseline methods based on various measures such as energy consumption, route failure, throughput, delay, packet delivery ratio (PDR), normalized routing load (NRL) and buffer occupancy by varying the mobility speed from 5 to 30[Formula: see text]m/sec, number of nodes and simulation time, respectively. At the mobility speed of 10[Formula: see text]m/sec, the proposed model has a delay of 0.08 sec, PDR of 99% and throughput of 1903.4[Formula: see text]kbps. The proposed model achieves a delay of 19.37[Formula: see text]msec, PDR of 96.22%, and throughput of 132.95[Formula: see text]kbps, respectively, for 30 nodes. If the simulation runs for 300 sec, the suggested model achieves a delay of 2.98 sec and a PDR of 0.946, respectively.

Impact of Propagation Environment on the Performance of Direction Oriented Forwarding through Minimum Number of Edge Nodes (DOF-MEN) Routing Protocol In Ad Hoc Networks

One sort of wireless ad-hoc network is called MANET (Mobile Ad-hoc Network), which is an autonomous network made up of wireless nodes and routers connected by wireless connections. Transmission of data in effective way is important. The DOF-MEN (Direction Oriented Forwarding through Minimum Number of Edge Nodes) protocol is the protocol which lessens the amount of messages for route discovery. It attempts to choose just single node as the next following hop. The node's address is added by the sender. Therefore, only the chosen node will receive and subsequently transmit the data. This protocol increases the throughput, Packet Delivery Ratio, and cuts down on the Routing Overhead. Several aspects affect the routing protocol's execution accuracy in mobile ad hoc networks (MANET). The propagation model is a crucial thing to be considered among many. MANET experiences an enormous loss in performance due to blockage between transmission devices and fluctuation in the receiver's signal intensity. Therefore, it's crucial to determine how Radio Propagation Model and study of performance of routing protocol in MANET. Here we do simulation and analysis using NS2 (Network Simulator 2). The outcome demonstrates that the MANET routing protocol's performance is more influenced by the propagation model.

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.

Optimal Node Routing Layouts in Mobile Adhoc Network

Mobile Adhoc Network (MANET) is a self-organizing network of various network devices responsible for communication. In MANET, new layouts are adopted for energy optimization, security implementation, traffic minimization and overhead reduction. MANET are aggressive in nature. This requires modification in network routing protocols for performance enhancement. This paper presents the detailed survey of different layouts involved in the implementation of network routing protocols in MANET. The survey is classified into four phases involved in MANET routing applications namely- routing protocols, neighborhood discovery, distributed or centralized hash tables, and bloom filter. Firstly, the classification of routing protocols based on various traffic models presents the MANET configuration. Secondly, a neighborhood discovery mechanism conveys the enhancement in the routing configurations. Thirdly, application of hash table operation (distributed/ centralized) to MANET to improve the matching efficiencies and computational speed. Finally, the application of bloom filter concept to improve service discovery rate and reduce the fake identities. Traditionally, the unpredictability occurs during the prediction of optimal node routing due to the dynamic nature of the MANET. Moreover, the presence of ejected malicious node in another cluster disgraced the link stability. This survey conveys the problems such as storage overhead, mobility nature, malicious nodes, and false positive rates in the traditional methods. The detailed survey leads to the stone of integration of Distributed Hash Table (DHT) with a bloom filter to reduce the problems in traditional research works. Index Terms – Performance Optimization, Bloom Filter, Centralized Hash Table (CHT), Distributed Hash Table (DHT), Energy Consumption, Mobile Ad- hoc Network (MANET), Quality of Service (QoS), Routing.

A Blockchain-Enabled Trust Management Framework for Energy-Efficient and Secure Routing in Mobile Ad-Hoc Networks

This study principally addresses the challenges associated with streaming videos in wireless Mobile ad hoc networks (MANETs), primarily constrained by wireless channels and node mobility. This study proposes a novel routing protocol incorporating a feedback mechanism and cross-layer architecture, supported by three key enhancements. First, it incorporates a route recovery strategy for detecting link failures and re-establishing connections based on predefined Quality of Service (QoS) metrics. Second, a novel algorithm estimates the available bandwidth, enabling dynamic adaptation of bitrate at the application layer concerning the source video. This novel rate-adaptive approach utilizes a scalable layered structure of the video coding, thereby removing layers that the network cannot efficiently support due to bandwidth limitations. Third, a gateway discovery procedure enhances the connectivity among MANETs and other infrastructure networks. This method employs available bandwidth as a parameter while selecting appropriate gateways and dynamically adjusts operational parameters like proactive area size and advertisement message frequency. The performances of the proposed Enhanced OLSR (E-OLSR) protocol are compared with the state-of-the-art routing procedures such as Adhoc on-demand distance vector (AODV), destination sequenced distance vector (DSDV), and optimized link state routing (OLSR), in terms of metrics like packet delivery ratio (PDR), end-to-end (E2E) delay, throughput, as well as energy consumption. The simulation results demonstrated notable improvements, including reduced packet delay, fewer dropped packets, and decreased link failures, indicating effective utilization of available bandwidth. The overall performance of the proposed E-OLSR protocol exceeds other traditional protocols and its security is enhanced through the integration of Blockchain Technology.

Enhanced Hybrid Routing Protocol for Energy-Efficient Multipath Routing in Manets

Mobile Ad Hoc Networks (MANETs) pose challenges in managing dynamic energy consumption and optimizing network lifetime. This study proposes an improved hybrid routing protocol by integrating situation-adaptive routing and energy-efficient multipath routing strategies. We identified two promising routing protocols, FF-AOMDV and STFDR. While FF-AOMDV minimizes energy consumption, it ignores loss of power, resulting in link failures and reduced MANET lifetime. To address this, we introduce PLA-AOMDV, which efficiently manages power loss and outperforms FF-AOMDV in experimental results. However, PLA-AOMDV needs enhancements in addressing link breakage and utilization. Thus, we propose ELA-AOMDV to maximize energy efficiency and load balancing, refining route selection for better outcomes. Experimental findings demonstrate ELA-AOMDV's superiority over PLA-AOMDV in throughput, packet dropping rate, energy consumption, and network lifetime. Additionally, we present an Improved Hybrid Routing Protocol (IHRP), which combines DMR, AOMDV, OLSR, and AODV. Leveraging the strengths of these protocols, IHRP exhibits superior performance compared to AOMDV, ZRP, AODV, and OLSR. It proposed enhanced hybrid routing protocol effectively addresses the challenges of dynamic energy consumption and efficient multipath routing in MANETs, improving network performance and lifetime.

Performance Analysis of Non-Realistic Routing Protocol using Random Waypoint Model in MANET

A mobile ad hoc network (MANET) is a collection of wireless nodes connected via wireless networks and has no set structure. MANETs feature a self-organized routing topology in which mobile nodes are free to move, making it difficult and crucial to construct a stable and reliable network. Thus, failure of the route is also regarded as a prime factor affecting the efficiency of any MANET routing protocol. The breaking of the connection between two routes or more nodes will cause the failure of the route specifically in the non-realistic routing protocol. In a network of mobile nodes, the link break is mainly based on the mobility of individual nodes. Therefore, the objective of this research is to investigate the performance of proactive DSDV and reactive AODV routing protocol using the Random Waypoint(RWP) mobility model in MANET. NS-2 network simulator is used to simulate the MANET environment and BonnMotion is to create a movement of mobile nodes that integrate with the routing protocol. The network performance metrics used are throughput, packet delivery ratio, and average end-to-end delay. In addition, three simulation scenarios have been conducted to compare AODV and DSDV routing protocols with varying numbers of nodes, a comparison of AODV and DSDV routing protocols with varying pause time, and a comparison of AODV and DSDV routing protocols with varying mobility speed. The result from the three scenarios analysed and concluded that the RWP mobility model with AODV gives a better performance of throughput with 869.69 kbps and Packet Delivery Ratio (PDR) with 83.00% meanwhile, RWP with DSDV is better for the average end-to-end delay(EED) with 212.970 bps.

Improved Routing Protocols: A First Step Towards Quality of Service in Mobile Ad-hoc Networks

The recent developments in wireless technology have piqued academics' curiosity. Mobile Adhoc Networks (MANET) is a fast-growing networking architecture used in emergency, disaster, and tactical operations applications. It covers a wide range of applications with some degradation due to its flexible and expandable nature. Because routing is the primary function of wireless networks, routing protocol design is critical in Adhoc networks. Various methods have been used to improve the performance of current routing protocols in different categories. Technical advances in routing protocols have recently been achieved, combined with optimization approaches to improve the overall performance of MANETs routing protocols. This research initially looked at several sorts of routing protocols before going through their variations for energy economy and latency reduction. The previous protocols, which were created utilizing optimization methods, will then illustrate the current requirement. Finally, the review analysis delves into many aspects such as commonly used protocols, optimization techniques, QoS parameters, performance metrics, and future paths. Keywords: MANETs, Energy, Delay, Optimized Protocols, QoS.

Analyze the Impact of Mobility and Pause Time on ACO based Manet Routing Protocols - Review

Abstract: Recently, many researchers have studied its performance within Mobile Ad-hoc Networks (MANETs). Every ad hoc network protocol focuses on a different set of measurements and traits. The majority of the currently utilized mobility models are employed to provide realistic movement patterns for MANET scenarios. A crucial element in the creation of MANET protocols is simulation. The future topology of a network can be predicted, which enables Quality of service- aware routing to choose a dependable link for data transmission. Ant algorithms, also known as swarm intelligence, are a wider field of study that deals with algorithmic approaches that are motivated by the behaviour of ant colonies and other insects. Ant Colony Optimization (ACO) is a subset of this larger topic. Based on the pheromone value deposited over the link, we identified two categories for the link quality in the proposed approach. We have demonstrated how the network's performance is enhanced by the suggested technique. The nodes are moving in the specified terrain dimensions through the Enhanced Manhattan Mobility Model (EMMM). The five QoS performance metrics are analyzed over three MANET routing protocols. The comparison is made over two important factors-mobility and pause time with the proposed ACO technique of reliable links. In the first experiment of different speeds, DSR is 25.5% better than AODV and 5.3% better than DSDVin metric packet dropping, 1.15% better than AODV and 1.01% better than DSDV in Packet Delivery Ratio, 1.5% better than AODV and 1.04% better than DSDV in packet overhead, and 62.7% better than AODV and 73.1% better than DSDV in average end-to-end delay. In the second experiment of pause times, DSR is 25.05% better than AODV and 4.5% better than DSDV in packet dropping, 1.18% better than AODV and 1.01% better than DSDV in packet delivery ratio, 1.01% better than DSDV in throughput, 0 to 0.002% in packet overhead, and 0.02% to 0.005% shorter delay.

IoT energy efficiency routing protocol using FHO‐based clustering and improved CSO model‐based routing in MANET

SummaryMany protocols, services, and electrical devices with built‐in sensors have been developed in response to the rapid expansion of the Internet of Things. Mobile ad hoc networks (MANETs) consist of a collection of autonomous mobile nodes that can form an ad hoc network in the absence of any pre‐existing infrastructure. System performance may suffer due to the changeable topology of MANETs. Since most mobile hosts operate on limited battery power, energy consumption poses the biggest challenge for MANETs. Both network lifetime and throughput improve when energy usage is reduced. However, existing approaches perform poorly in terms of energy efficiency. Scalability becomes a significant issue in large‐scale networks as they grow, leading to overhead associated with routing updates and maintenance that can become unmanageable. This article employs a MANET routing protocol combined with an energy conservation strategy. The clustering hierarchy is used in MANETs to maximize the network's lifespan, considering its limited energy resources. In the MANET communication process, the cluster head (CH) is selected using Fire Hawk Optimization (FHO). When choosing nodes to act as a cluster for an extended period, CH election factors in connectivity, mobility, and remaining energy. This process is achieved using an optimized version of the Ad hoc On‐Demand Distance Vector (AODV) routing protocol, utilizing Improved Chicken Swarm Optimization (ICSO). In comparison to existing protocols and optimization techniques, the proposed method offers an extended network lifespan ranging from 90 to 160 h and reduced energy consumption of 80 to 110 J, as indicated by the implementation results.

Data aggregation and routing in Mobile Ad hoc network: Introduction to Self-Adaptive Tasmanian Devil Optimization

Mobile Ad-Hoc Network (MANETs) is referred to as the mobile wireless nodes that make up ad hoc networks. The network topology may fluctuate on a regular basis due to node mobility. Each node serves as a router, passing traffic throughout the network, and they construct the network’s infrastructure on their own. MANET routing protocols need to be able to store routing information and adjust to changes in the network topology in order to forward packets to their destinations. While mobile networks are the main application for MANET routing techniques, networks with stationary nodes and no network infrastructure can also benefit from using them. In this paper, we proposed a Self Adaptive Tasmanian Devil Optimization (SATDO) based Routing and Data Aggregation in MANET. The first step in the process is clustering, where the best cluster heads are chosen according to a number of limitations, such as energy, distance, delay, and enhanced risk factor assessment on security conditions. In this study, the SATDO algorithm is proposed for this optimal selection. Subsequent to the clustering process, routing will optimally take place via the same SATDO algorithm introduced in this work. Finally, an improved kernel least mean square-based data aggregation method is carried out to avoid data redundancy. The efficiency of the suggested routing model is contrasted with the conventional algorithms via different performance measures.

Selecting Optimal Path in Multiple-Path Routing for MANETs Using Fuzzy Cost

Background/ Objectives: Mobile Ad Hoc Networks (MANETs) consists of a set of nodes, where the nodes tend to change their positions time to time because of their infrastructure less characteristic. In MANETs, the protocol that is considered to be the appropriate for constructing an efficient route is AODV. Broadcast storm is another approach that can be used for establishing a path between the sender and receiver. Due to the concerns related to contention and collision, broadcast is not considered as an efficient mechanism for path selection. Though the aim of broadcasting is to minimize the flooding other issues like bandwidth consumption, collision and contention cannot be controlled. Since MANETs are associated with inadequate bandwidth, the approach of broadcasting is not efficient. Multipath routing approach permits in constructing multiple paths between the communicating nodes (sender and receiver). This approach is complicated due to the problem of node mobility in MANETs. The other paths available are not reliable because of the ad hoc nature of MANETs. The intention is to design a fuzzy controller that assists in reducing the reconstruction of paths using fuzzy cost assigned to each node in the network. Methods: The concept of this paper is to establish an optimal path from sender node to the receiver node from the available multiple paths in MANETs. The path established in this approach uses fuzzy cost. Fuzzy measure is the criteria used for establishing a path. The concept ImRMR used in this paper has been included with few improvements. The basic functionality of ImRMR is that paths are classified based on rank fitness. The proposal is to classify the paths based on its fuzzy cost. This fuzzy cost classifies the paths fitness. Findings: The proposed fuzzy cost approach discussed in this study is compared with On-Demand Multicast Routing Protocol (ODMRP). The result exhibits that the proposed method works better under differing conditions like traffic load, transmission range between nodes and also considers node mobility. The proposed mechanism with inclusion of fuzzy cost shows 5% energy efficiency, reduces the collisions by about 35% and throughput is enhanced by 30%. There has been a considerable decrease in the number of queries by 23%. The simulation results indicate that ODMRP with fuzzy cost is more useful and significant. Hence, consideration of fuzzy cost as a means for selecting an effective route is assumed to be the best. Novelty: This method contributes in reducing the drawbacks of routing approaches whether it is unipath and multi-path approach. The proposed approach changes the value of the attributes for a given route with fuzzy cost. A threshold value will be considered initially and the route having a cost more than the initialized threshold would be advised as the best route. This route would be considered as the efficient route for transmission between the sender and the receiver. Keywords: Uni­path, multiple paths, Fuzzy cost, Fuzzy fitness, Rank fitness