Wireless Mobile Ad-hoc Networks Research Articles

Machine Learning-assisted Distance Based Residual Energy Aware Clustering Algorithm for Energy Efficient Information Dissemination in Urban VANETs

A Vehicular Ad-hoc Network (VANET) is an essential component of intelligent transportation systems in the building of smart cities. A VANET is a self-configure high mobile and dynamic potential wireless ad-hoc network that joins all vehicle nodes in a smart city to provide in-vehicle infotainment services to city administrators and residents. In the smart city, the On-board Unit (OBU) of each vehicle has multiple onboard sensors that are used for data collection from the surrounding environment. One of the main issues in VANET is energy efficiency and balance because the small onboard sensors can’t be quickly recharged once installed on On-board Units (OBUs). Moreover, conserving energy stands out as a crucial challenge in VANET which is primarily contingent on the selection of Cluster Heads (CH) and the adopted packet routing strategy. To address this issue, this paper proposes distance and energy-aware clustering algorithms named SOMNNDP, which use a Self-Organizing Map Neural Network (SOMNN) machine learning technique to perform faster multi-hop data dissemination. Individual Euclidean distances and residual node energy are considered as mobility parameters throughout the cluster routing process to improve and balance the energy consumption among the participating vehicle nodes. This maximizes the lifetime of VANET by ensuring that all intermediate vehicle nodes use energy at approximately the same rate. Simulation findings demonstrate that SOMNNDP improves Quality of Service (QoS) better and consumes 17% and 14% less energy during cluster routing than distance and energy-aware variation of K-Means (KM) and Fuzzy C-Means (FCM) called KMDP and FCMDP respectively.

A novel DAG-blockchain structure for trusted routing in secure MANET-IoT environment

Different physical objects can be employed in the modern technological environment to facilitate human activity. In order to connect physical objects with the universe of digital using a variety of networks and communication technologies, an IoT, the cutting edges technological and effective solution, is deployed. Mobile ad hoc networks (MANET) interact with the IoTin smart settings, enhancing its user appeal and boosting its commercial viability. The new system of MANET based IoT and IT-network may be created by integrating wireless sensor and MANET with the Internet of Things. A solution like this increases user mobility while lowering network deployment costs. However, it also raises new, difficult problems in terms of networking considerations. In this, we presented a novel DAG (Directed Acyclic Graph)-Blockchain structure for MANET-IoT security. The network is secured through Multi-Factor PUF (MF-PUF) authentication scheme. With all authorized nodes, the network is segregated into cluster topology. For trusted data transmission, we proposed Jelly Fish Optimization (JFO) algorithm with the consideration of multiple criteria. For deep packet inspection, we proposed a Fully Connected Recurrent Neural Network (FCRNN). Through deep packet inspection, the intrusions are detected and mitigated through blocking system.With help of merged algorithm, the suggested method obtained improved ability in the PDR (Packet Delivery Ratio), production, analysis of time, detection accuracy also security levels. The comparison results clearly indicate that the proposed study outperforms all previous studies in various aspects. Particularly, the suggested methods for cluster creation, data aggregation, routing, encryption, and authentication significantly improve the system of DAG-IDS. Additionally, the planned task exhibits an exceptionally low standard deviation, making the suggested approach highly suitable for a WSN-IoT environment.

Analysis of a Fuzzy Based Intrusion Detection System in Wireless Ad Hoc Networks

Technology and its growth is considerably enormous. This massive growth allows the opening of new fields of application in the domain of wireless networking and mobile ad-hoc networks (MANET) is one of its kinds. Mobile ad hoc network is widely used from collaborative computing to time critical applications in indoor and outdoor environment. Mobility of ad hoc network makes very attractive in all areas of mobile applications. Nodes participating in mobile ad hoc networks are autonomous, self-configurable and act as a router as well. These types of networks are dynamic in nature and have sort life time. Dynamic nature and limitations of the wireless transmission medium make MANET unsecured and vulnerable to various attacks. It is very tough to implement security for this networks and it opens up doors for further research work on this area. There is a great scope for designing a system to identify attacks and take countermeasures to minimize it and keep the performance of the network within acceptable limits. Intrusion detection system is one of its kinds and considered as security mechanism for MANET. This thesis explores different types of intrusion detection system like misuse detection and anomaly detection for mobile ad hoc networks. Anomaly detection techniques for ad hoc networks depend on the characterization of normal behavior pattern of wireless nodes. This research work focuses on wireless node behavior based detection technique. Most of anomaly intrusion detection systems are focusing on upper layer traffic to a profile normal behavior of wireless node. This research work focus on media access control (MAC) layer and network layer of wireless node. It is inefficient to use a large feature set of MAC layer and network layer due to energy limitation in ad-hoc network. A minimal feature set from MAC layer and network layer were proposed. This research work proposed an anomaly intrusion detection system for mobile ad hoc network using fuzzy logic and weighted average method. The network performance of mobile ad hoc network with intrusion detection system was analyzed using various network parameters. Further the performance of the performance of the intrusion detection system was analyzed using detection rate and false alarms. Results show good improvement in detection rate and other performance metrics

An Improved Selfish Node Detection Algorithm for Cognitive Radio Mobile Ad Hoc Networks

An Improved Selfish Node Detection Algorithm for Cognitive Radio Mobile Ad Hoc Networks

Role of Manet and Artificial Bee Colony Algorithm to Make Smart Campus Model, With Smart Sensors

In the decade of Internet of Thing, Machine Learning and Big data we are ready to accumulate lot of sensors and intelligent devices for making our real world environment more accessible, open, transparent and its records are manageable for future purpose i.e. either just for fetching or analyze for future perspective. In contrast, an institutional campus is also ready for fully automation where all the major participants like students, academician, management and others, should be observed as an entity with their different attributes. Meanwhile those campuses are not functioning in isolation, it depends and Intercorelated to some other organizations and modules also, so that they have to synchronized and update their data accordingly. Here the whole scenario views from computer network perspective, where all the participating members observed like node and in whole it creates wireless mobile ad-hoc network i.e. MANET. First will understand the campus functioning in short then look at flow of data in this system, then observes the components and their responsibility to categorized and placing them in MANET based architecture. Finally we will select and design algorithm for the whole digital campus system. This is a concept of implementing intelligent technologies to transform any existing environment into smart, here not only institutional campus but many other also can be upgraded or transform into smart like villages, cities, sports or working flow like census, PDS, Disaster Management system etc.

Mobile wireless ad-hoc network routing protocols comparison for real-time military application

Mobile wireless Ad-hoc has become more popular because it forms quickly, has an easy setup, and has easy extensibility. The mobile ad-hoc wireless networks can be further classified according to their applications as follows: Regular user ad-hoc networks are commercial communication that applies to vehicles to help avoid collisions and accidents and live connections to transfer data from car to car. Another application is disaster rescue ad-hoc networking, usually used when a normal infrastructure network is destroyed by storms, earthquakes, tsunamis, etc. Nowadays, a lot of applications, particularly those related to the military and emergency situations, rely on mobile ad hoc wireless networks, where security needs are more challenging to provide than in regular networks. We present the tactical network needs for the military. This platform attempts to assess the possible advantages of mobile ad hoc networks in tactical military applications. This work proposes route discovery using reactive (on-demand) routing protocols where nodes need to just transfer data. This eliminates the requirement for each node to store and maintain any routing tables. This study presents and contrasts the benefits and drawbacks of two fundamental mobile ad hoc routing systems (AODV and DSR). Both protocols are On-Demand routing techniques, and when data needs to be sent, the discovery phase begins. The results of the simulation, the AODV routing approach outperforms the DSV routing method under identical simulated conditions.

A Modified DSR Protocol Using Deep Reinforced Learning for MANETS

Wireless Networks like Mobile Adhoc Networks (MANETs) have been under extensive research over the past few years with congestion control as one of the most important features to ensure efficient and fair sharing of network resources among users. Machine learning (ML) has achieved a success rate in addressing large-scale and complex problems and researchers have begun to shift their attention from the rule-based method to an ML-based approach to handle the complex needs of future networks where conventional rule-based approaches tend to become inefficient and ineffective. To handle the problems in congestion control, precise notification should be generated as the backpressure transmission process. Although backpressure-based routing algorithms give optimal throughput, they typically have poor delay performance under moderate loads. This may be because packets are being sent over longer routes unnecessarily. Furthermore, the existing backpressure-based optimisation algorithms require every node to compute differential backlogs for every destination queue with the corresponding destination queue at every adjacent node. The proposed algorithm proves to be a cross-layer protocol for wireless MANET that generalises the channel access management and routing process which includes traffic management, connection maintenance and distributed scheduling for concurrent transmission. The joint congestion control method with scheduling algorithm has enhanced active radio communication network by interchanging scheduling schema with adaptation modelling and also the optimum congestion dominance and flow control model is being designed using deep reinforced learning.

Enhancing the security of quality of service-oriented distributed routing protocol for hybrid wireless network

Merging the wireless infrastructure network with the wireless mobile ad-hoc networks constitutes hybrid wireless networks (HWNs). Quality of service (QoS) demands are available with the help of HWNs. However, these networks are subjected to many types of attacks because of their open wireless medium. To enhance the security of HWNs, it is necessary to provide secure routing protocols. Several routing protocols have been proposed for HWNs, one of them is the quality of service-oriented distributed (QOD) routing protocol. In this paper, two security mechanisms have been proposed for the QOD protocol. The first mechanism is used to protect transmitted data in the network using asymmetric and symmetric cryptography. The second mechanism has been proposed to enhance the security of the QOD routing protocol using keyed hash message authentication code (HMAC). The second security mechanism assumed that there is a secret key shared between each pair of neighbor nodes. Also, asymmetric cryptography is used to exchange the secret key. The secret key is used to include the message authentication code (MAC) for each message exchanged between the neighbor nodes. A network simulator NS2 is used to simulate our proposed schemes.

Quality communication using varying parameters for wireless mobile ad hoc networks

Wireless Mobile Ad Hoc Networks (MANETs) present topologies where nodes act as both hosts and routes, necessitating efficient routing protocols to handle frequent route updates and transmission congestion. This paper proposes a novel routing algorithm, Fuzzy Controller Ad hoc On-demand Distance Vector (FC-AODV), to address these challenges. The FCAODV algorithm is designed to improve packet delivery ratio, throughput, end-to-end delay, packet loss, remaining energy, and routing overhead compared to the traditional AODV protocol. Through extensive simulations using NS 2, the proposed algorithm demonstrates superior performance across varying network scenarios. Results indicate an average increase of 12.4% in packet delivery ratio, 10.27% in throughput, and a decrease of 5.37% in end-to-end delay compared to AODV. Additionally, FC-AODV reduces packet loss by 5.57%, increases remaining energy by 6.4%, and decreases routing overhead by 6.37%. Future research directions include applying the FC-AODV concept to satellite networks, exploring the integration of shortest path algorithms, and evaluating FC-AODV in real-time network environments.

Study of Ad- Hoc Networking Technologies and Optimization of The Broadcasting Process

In this paper, we present about Ad-hoc networking technologies and optimization of the broadcasting process. In recent years, mobile computing has enjoyed a tremendous rise in popularity. The continued minimization of mobile computing devices and the extraordinary rise of processing power available in mobile laptop computers combine to put more and better computer-based applications into the hands of a growing segment of the population. At the same time, the markets for wireless telephones and communication devices are experiencing rapid growth. Projections have been made that, in nowadays there are more than billion wireless devices in use. Therefore, the wireless mobile computers or Mobile Ad Hoc Networks (MANET) have become very necessary.

A Collaborative Approach for Secured Routing in Mobile Ad-Hoc Network

Mobile computing is the most powerful application for network communication and connectivity, given recent breakthroughs in the field of wireless networks or Mobile Ad-hoc networks (MANETs). There are several obstacles that effective networks confront and the networks must be able to transport data from one system to another with adequate precision. For most applications, a framework must ensure that the retrieved data reflects the transmitted data. Before driving to other nodes, if the frame between the two nodes is deformed in the data-link layer, it must be repaired. Most link-layer protocols immediately disregard the frame and enable the high-layer protocols to transmit it down. In other words, because of asset information must be secured from threats, information is a valuable resource. In MANETs, some applications necessitate the use of a network method for detecting and blocking these assaults. Building a secure intrusion detection system in the network, which provides security to the nodes and route paths in the network, is a major difficulty in MANET. Attacks on the network can jeopardize security issues discovered by the intrusion detection system engine, which are then blocked by the network’s intrusion prevention engine. By bringing the Secure Intrusion Detection System (S-IDS) into the network, a new technique for implementing security goals and preventing attacks will be developed. The Secure Energy Routing (SER) protocol for MANETs is introduced in this study. The protocol addresses the issue of network security by detecting and preventing attacks in the network. The data transmission in the MANET is forwarded using Elliptical Curve Cryptography (ECC) with an objective to improve the level of security. Network Simulator – 2 is used to simulate the network and experiments are compared with existing methods.

Comparative analysis of new meta-heuristic-variants for privacy preservation in wireless mobile adhoc networks for IoT applications

“Mobile Ad Hoc Network (MANET)” is a self-configurable, self-repairing, self-maintaining, highly mobile, decentralized, and independent wireless network, which has the liberty to move from one to another place. Such networks do not have any pre-existing infrastructure. The adoption of a smart environment in MANET requires new protocols to connect the gadgets to the internet. A smart environment with routing protocols should assure the following properties like connectivity among the nodes, “Quality of Service (QoS)”, and fairness, both in access points and ad-hoc networks. Combination with the Internet of Things (IoT) and MANET generates a novel MANET-IoT system, which focuses on reducing the implementing costs of the network and providing better mobility for users. The necessity of these integrated networks is increasing in military operations, rescue operations, personal area networks, emergency rooms, and meeting rooms. Routing in MANETs is a not simple job and has projected a huge range of attention from researchers around the world. Thus, the intention of this task is a development of a security protocol in MANET for the IoT platform. For dealing with encryption and decryption strategies to handle MANET and IoT data, a new approach is suggested through the enhanced chaotic map. Here, three improved algorithms are implemented for proposing the optimized key management scheme under a chaotic map, which is the Modified Updating-based Harris Hawks Optimization Algorithm (MU-HHO), Mean Solution-based Averaging Sailfish Optimizer (MS-ASFO), Adaptive Basic Reproduction Rate-based Coronavirus Herd Immunity Optimizer (ABRR-CHIO). In the convergence evaluation, while taking the length of plain text as 40, ABRR-CHIO shows superior performance over other techniques at the 60th iteration, which is 96%, 95%, 93%, 96%, and 80% superior to HHO, SFO, CHIO, SA-SFO, and CHHSO. Finally, the performance evaluation is performed regarding “statistical analysis, convergence analysis, and communication overhead” to reveal the superiority of the designed model.

A Deep Reinforcement Learning-Based QoS Routing Protocol Exploiting Cross-Layer Design in Cognitive Radio Mobile Ad Hoc Networks

In this paper, we propose a novel deep reinforcement learning-based quality-of-service (QoS) routing protocol, namely DRQR, exploiting cross-layer design to establish efficient QoS (EQS) routes in cognitive radio mobile ad hoc networks. An EQS route is a route with minimum end-to-end (E2E) queuing delay subject to QoS constraints such as link stability, residual energy, number of hops and avoiding licensed channels of primary users. Particularly, we propose an NP-complete optimization problem which has a feasible solution as an EQS route. To tackle this problem, we design a new deep reinforcement learning model which supports the DRQR protocol to establish EQS routes in real time by offline training instead of online training like most of literature studies. Moreover, the DRQR protocol guarantees to have high system performance. A mathematical analysis of the E2E queuing delay with random waypoint mobility model also provides to verify simulation results. Numerical results show that the DRQR protocol outperforms state-of-the-art routing protocols in terms of routing delay, queuing delay, control overhead, PDR and energy consumption.

A Study on Different Deep Learning Algorithms Used in Deep Neural Nets: MLP SOM and DBN.

Deep learning is a wildly popular topic in machine learning and is structured as a series of nonlinear layers that learns various levels of data representations. Deep learning employs numerous layers to represent data abstractions to implement various computer models. Deep learning approaches like generative, discriminative models and model transfer have transformed information processing. This article proposes a comprehensive review of various deep learning algorithms Multi layer perception, Self-organizing map and deep belief networks algorithms. It first briefly introduces historical and recent state-of-the-art reviews with suitable architectures and implementation steps. Moreover, the various applications of those algorithms in various fields such as wireless networks, Adhoc networks, Mobile ad-hoc and vehicular ad-hoc networks, speech recognition engineering, medical applications, natural language processing, material science and remote sensing applications, etc. are classified.

Fitness Sorted Red Deer-Cat Swarm Optimization-based Autonomous QoS-aware Multicast Communication System in MANET

A mobile ad hoc network (MANET) is a set of autonomous mobile devices connected by wireless links in a distributed manner and without a fixed infrastructure. Mobile Ad-Hoc Networks (MANETs) is considered as an infrastructure-less and constant self-configured network of wireless devices. Here, multicast has emerged as an efficient tool for communication. Recently, distinct research works have been studied in wireless MANETs for designing multicast routing protocols. Multicasting is a procedure used for allowing the users to send the same messages simultaneously to a set of users. Though, it suffers from different problems regarding implementation in ad-hoc networks owing to its shorter battery lifetime, and lack of bandwidth dynamic nature of the mobile devices. Hence, the main aim of this paper is to propose a new QoS-aware multi-cast routing protocol in MANET using the hybrid meta-heuristic algorithm. The proposed routing protocol will focus on the development of a hybrid meta-heuristic-based “reliable neighbor nodes selection” scheme over the Multicast Ad-Hoc on Demand Distance Vector routing protocol (MAODV) protocol. The “reliable neighbor nodes selection” is accomplished by Fitness sorted Red Deer-Cat Swarm Optimization (FRD-CSO) algorithm focusing on the constraints like energy model, mobility model, and reliability pair factor. Once the optimal node selection is performed, the proposed QoS-aware protocol is validated by the route discovery mechanism and route reply process. The simulation has been performed to show the efficiency of the designed multicast routing over other multicast routing protocols that demonstrates the noteworthy enhancement in terms of diverse performance measures.

An Authentication and Key Agreement Scheme Based on Roadside Unit Cache for VANET

Vehicular Ad Hoc Network (VANET) is a wireless Mobile Ad Hoc Network that is used for communication between vehicles, vehicles and fixed access points, and vehicles and pedestrians. However, because of the use of open wireless channels, VANET is more vulnerable. Therefore, VANET security is critical for safe driving and user privacy protection. Authentication and key agreement are crucial for ensuring security. Numerous authentication schemes have been proposed between vehicles and roadside units (RSUs). Many solutions are authentication and key negotiation between the vehicle and a single RSU. The vehicle passing through a region needs to complete authentication and key agreement with multiple RSUs separately, which brings a great burden to the vehicle. In order to simplify the authentication process of vehicles and multiple RSUs and improve the efficiency of authentication and key agreement, an efficient authentication and key agreement scheme based on RSU cache is proposed when the vehicle moves from one RSU to another RSU region. In the proposed scheme, RSUs are divided into regions, and each region has a RSU cluster head. When the vehicle enters a certain region and authenticates with a RSU successfully, the RSU submits the authentication information to the RSU cluster head. The RSU cluster head shares the authentication information with other RSUs in the region using the shared key. Other RSUs record the authentication information in the cache. When the vehicle communicates with other RSUs, the authentication is not necessary; the session key can be negotiated by simply exchanging information. After using the cache, the calculation and communication cost of the authentication and key negotiation between the vehicle and other RSU can be significantly saved, the calculation cost is reduced by 37%, and the traffic is reduced by 35%. The random oracle model is used to prove the security of the scheme. The results revealed that the authentication overhead of the proposed scheme is considerably lower than those of other schemes. Compared with the related schemes, the computational cost of the proposed scheme is reduced by 34% on average; the communication cost is close to other related schemes. Moreover, the security analysis shows that the proposed scheme provides better security compared to other related schemes.

CoCo Games: Graphical Game-Theoretic Swarm Control for Communication-Aware Coverage

We propose a novel framework for real-time communication-aware coverage control in networked robot swarms. Our framework unifies the robot dynamics with network-level message-routing to reach consensus on swarm formations in the presence of communication uncertainties by leveraging local information. Specifically, we formulate the communication-aware coverage as a cooperative graphical game, and use variational inference to reach mixed strategy Nash equilibria of the stage games. We experimentally validate the proposed approach in a mobile ad-hoc wireless network scenario using teams of aerial vehicles and terrestrial user equipment (UE) operating over a large geographic region of interest. We show that our approach can provide wireless coverage to stationary and mobile UEs under realistic network conditions.

Retraction Note to: QOS distributed routing protocol for mobile ad-hoc wireless networks using intelligent packet carrying systems

Retraction Note to: QOS distributed routing protocol for mobile ad-hoc wireless networks using intelligent packet carrying systems

Fuzzy logic based cross-layer design to improve Quality of Service in Mobile ad-hoc networks for Next-gen Cyber Physical System

5G standard by 3GGP has provision for Device-to-Device (D2D) communication over a Wireless Mobile Ad-hoc Network (MANET) framework. Recent research and development in 6G Networks and beyond has support for integration of MANET to the Mobile communication infrastructure to cater services to many potential future-proof applications like Smart Vehicular Networks using Internet of Vehicles (IoV) and Flying Ad-hoc Networks (FANET) for drone networks and military Ad-hoc networks. MANET being an Ad-hoc and infrastructure-less network poses major deployment challenge in resource allocation and management to facilitate strict Quality of Service (QoS) requirements for future Internet of Things (IoT) based Next-generation Cyber Physical System (NG-CPS). Most of MANETs use Contention-based Distributed Coordination Function (DCF) random Access Media Access Control (MAC) and a generic TCP/IP stack implementation. It is a daunting task to have deterministic model of network parameters for specific QoS requirements of IoT applications hence a soft-computing approach would be most viable solution considering network parameters across all five layers of TCP/IP stack that is a Cross-Layer design approach to improve QoS. In this paper, we have proposed a Fuzzy Logic system based Cross-Layer (FLS-CL) design for MANET to improve Network QoS parameters like Throughput, Packet Delivery ration (PDR) and End-to-End (E2E) delay. The proposed system has been implemented using Fuzzy Logic based parameters modeling using MATLAB and the Network simulation study using QualNet® simulator. The results are promising with average 27.64 % improvement in PDR and 76.04 % less E2E delay for connection-less UDP-based CBR applications and 3.28 % improvement in PDR and 58.81 % less E2E delay for connection-oriented TCP-based FTP applications. The QoS improvements are achieved with proposed FLS-CL as compared to state-of-the-art IEEE 802.11 based MANET without any FLS cross-layer optimization.

Research on the Convergence Application of Satellite Mobile Communication and Wireless Ad Hoc Network

The article analyzes the networking modes and main features of satellite mobile communications and wireless ad hoc networks, and proposes to build a dual-function terminal of satellite mobile communications and wireless ad hoc networks. By merging the respective advantages of the two communication modes, the application range of satellite mobile communication can be further expanded, and finally exemplified typical application scenarios.