Performance Analysis of Ad Hoc on-Demand Distance Vector Routing Protocol for Mobile Ad Hoc Networks

Taterh, Swapnesh; Meena, Yogesh Kumar; Paliwal, Girish

doi:10.1007/978-981-32-9585-8_20

Cited by 8 publications

(6 citation statements)

References 12 publications

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“…The AODV routing protocol avoids the routing loop issue in ad-hoc networks ( Yan & Chung, 2020 ; Abbas et al, 2020 ). Because of their self-starting behavior, they do not require any stimulation and operate in an environment with several mobile nodes capable of withstanding various networking etiquette such as packet loss, link failure, and nodal mobility ( Taterh, Meena & Paliwal, 2020 ).…”

Section: Conceptual Designmentioning

confidence: 99%

Systematic review on modification to the ad-hoc on-demand distance vector routing discovery mechanics

Alameri

Komárková

Al-Hadhrami

et al. 2022

PeerJ Computer Science

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Mobile ad-hoc networks (MANETs) and wireless mesh networks (WMNs) are used in a variety of research areas, including the military, industry, healthcare, agriculture, the Internet of Things (IoT), transportation, and smart cities. The swift advancement in MANET technology is the driving force behind this rising adoption rate. Routing over MANET is a critical problem due to the dynamic nature of the link qualities, even when nodes are static. A key challenge in MANETs is the need for an efficient routing protocol that establishes a route according to certain performance metrics related to the link quality. The routing protocols utilised by the nodes in WMNs and MANETs are distinct. Nodes in both types of networks exchange data packets through the routing protocols. For this highly mobile network, the ad-hoc On-Demand Distance Vector (AODV) routing protocol has been suggested as a possible solution. Recent years have attracted researchers’ attention to AODV since it is a routing technique for ad-hoc networks that prevents looping. The architecture of this routing protocol considers several factors, including the mobility of nodes, the failure of connection links, and the loss of packets. In this systematic review, one of the key focuses is bringing attention to the classic AODV, which was developed after discussing the recent development of several versions of AODV. The AODV routing protocol performs a path strength check to generate a more reliable and secure route between the source and destination nodes. In AODV, investigations demonstrate advances in both the format protocol approach and the network simulation-2 (NS-2), and these improvements were made in the same scenario used to revitalise AODV. It has been discovered that the AODV is more effective in several aspects, such as throughput, end-to-end delay, packet delivery ratio (PDR), energy consumption, jitter, packet loss ratio, and network overhead. Furthermore, this paper presents this systematic review based on AODV modifications in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). It also provides a methodological framework for the papers’ selection.

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Section: Conceptual Designmentioning

confidence: 99%

Systematic review on modification to the ad-hoc on-demand distance vector routing discovery mechanics

Alameri

Komárková

Al-Hadhrami

et al. 2022

PeerJ Computer Science

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“…The quality of channels in wireless sensor networks may be enhanced by encrypting the data using various keys. As described in [33][34][35][36][37], several authors suggested securing ad hoc on-demand distance vector, a secure routing protocol based on initial encryption that can withstand certain routing assaults while ensuring the integrity and acknowledgment of identification.…”

Section: Related Workmentioning

confidence: 99%

Wireless Sensor Networks Routing Attacks Prevention with Blockchain and Deep Neural Network

Ali¹,

El-Moghith²,

El-Derini³

et al. 2022

Computers, Materials &Amp; Continua

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Routing is a key function in Wireless Sensor Networks (WSNs) since it facilitates data transfer to base stations. Routing attacks have the potential to destroy and degrade the functionality of WSNs. A trustworthy routing system is essential for routing security and WSN efficiency. Numerous methods have been implemented to build trust between routing nodes, including the use of cryptographic methods and centralized routing. Nonetheless, the majority of routing techniques are unworkable in reality due to the difficulty of properly identifying untrusted routing node activities. At the moment, there is no effective way to avoid malicious node attacks. As a consequence of these concerns, this paper proposes a trusted routing technique that combines blockchain infrastructure, deep neural networks, and Markov Decision Processes (MDPs) to improve the security and efficiency of WSN routing. To authenticate the transmission process, the suggested methodology makes use of a Proof of Authority (PoA) mechanism inside the blockchain network. The validation group required for proofing is chosen using a deep learning approach that prioritizes each node's characteristics. MDPs are then utilized to determine the suitable next-hop as a forwarding node capable of securely transmitting messages. According to testing data, our routing system outperforms current routing algorithms in a 50% malicious node routing scenario.

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“…As described in [32][33][34][35][36], several authors suggested securing ad hoc on-demand distance vector, a secure routing protocol based on initial encryption that can withstand certain routing assaults while ensuring the integrity and acknowledgement of identification. Other authors introduced an energy-aware secure routing architecture that preserves a trusted environment, isolates misbehaving nodes, and has a minimal control cost.…”

Section: B Related Workmentioning

confidence: 99%

Towards Designing a Trusted Routing Scheme in Wireless Sensor Networks: A New Deep Blockchain Approach

And

Darwish

2021

IEEE Access

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Routing is a critical process in Wireless Sensor Networks (WSNs) since it is responsible for data transmission to base stations. Routing attacks are capable of completely destroying and degrading the function of WSNs. A trustworthy routing system is critical for ensuring routing security and WSN efficiency. Numerous studies have been conducted to increase trust between routing nodes, including cryptographic techniques, and centralized routing decisions. Nonetheless, the majority of routing methods are impractical in practice, since it is difficult to identify untrusted activities of routing nodes effectively. Meanwhile, there is no efficient method of preventing malicious node attacks. As a result of these issues, this article offers a trusted routing method that combines deep-chain and Markov Decision Processes (MDPs) in order to enhance the routing security and efficiency of WSNs. To authenticate the process of transmitting the node, the proposed approach utilizes a Proof of Authority (PoA) method inside the blockchain network. The validation group necessary for proofing is selected using a deep learning methodology that focuses on the properties of each node. MDPs are then used to choose the appropriate next hop as a forwarding node capable of transferring messages simply and securely. According to testing data, our routing system still performs well in a 50% malicious node routing environment when compared to existing routing algorithms.

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Performance Analysis of Ad Hoc on-Demand Distance Vector Routing Protocol for Mobile Ad Hoc Networks

Cited by 8 publications

References 12 publications

Systematic review on modification to the ad-hoc on-demand distance vector routing discovery mechanics

Systematic review on modification to the ad-hoc on-demand distance vector routing discovery mechanics

Wireless Sensor Networks Routing Attacks Prevention with Blockchain and Deep Neural Network

Towards Designing a Trusted Routing Scheme in Wireless Sensor Networks: A New Deep Blockchain Approach

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