Remora optimization algorithm-based optimized node clustering technique for reliable data delivery in VANETs

Konduru, Swathi; Ibrahim, S. Jafar Ali

doi:10.1016/j.ijin.2022.07.002

Cited by 8 publications

(8 citation statements)

References 8 publications

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“…The QMFO algorithm derives a fitness function for the optimum cluster creation procedure [27]. The fitness function used in the BQMFO-CSSTS is introduced as a multiobjective fitness function, as given in Equation (9).…”

Section: Design Of Qmfo-based Clustering Processmentioning

confidence: 99%

Blockchain with Quantum Mayfly Optimization-Based Clustering Scheme for Secure and Smart Transport Systems

Alamro,

Alqahtani,

Alruwaili

et al. 2023

Sustainability

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Blockchain (BC) with a clustering scheme can be used to build secure and smart Vehicular Ad-Hoc Networks (VANETs), which provide improved data integrity, enhanced security, efficient resource allocation, and streamlined processes. This technology has revolutionized the transport industry by enabling safer, more efficient, and transparent transportation networks. Therefore, this paper concentrates on the design of a new Blockchain with a Quantum Mayfly Optimization-based Clustering Scheme for Secure and Smart Transport Systems (BQMFO-CSSTS) technique. The objective of the presented BQMFO-CSSTS technique is to build a secure VANET via a BC-based technology and clustering process. Moreover, the BQMFO-CSSTS technique initially uses a Quantum Mayfly Optimization (QMFO) system with a fitness function for the selection of cluster heads (CHs) and the cluster construction process. In addition, BC technology is used as trust infrastructure to provide trustworthy services to the user and protect the privacy of the CHs and cluster members (CMs). The proposed scheme leverages the decentralized and immutable nature of BC to establish trust and ensure the integrity of cluster formation in VANETs. Finally, the BQMFO-CSSTS technique uses trajectory similarity metrics to protect the integrity of the CMs against attacks. The simulation results of the BQMFO-CSSTS technique are validated using a series of measures. The comprehensive results reported the superior outcomes of the BQMFO-CSSTS method over other recent approaches, with the maximum throughput being 1644.52 kbps. Therefore, integration of BC technology provides a transparent and secure framework through which to manage cluster membership, data sharing, and trust establishment among vehicles.

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Section: Design Of Qmfo-based Clustering Processmentioning

confidence: 99%

Blockchain with Quantum Mayfly Optimization-Based Clustering Scheme for Secure and Smart Transport Systems

Alamro,

Alqahtani,

Alruwaili

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…If there is no requirement to change the host, they will perform host feeding. In this case, the normal ROA is transformed into MIRO to reduce the WSN's energy consumption [22].…”

Section: Ch Selection Using Miroamentioning

confidence: 99%

“…Whenever the remora is bound on the sailfish, its looks like as though the remora moves together with the sailfish. The formulas of the solvent freeze out (SFO) technique are enhanced depending on the elite approach, then the following equations are given, where 𝑐𝑡 represents prevalent iteration number, 𝑍 𝐵𝑒𝑠𝑡 𝑐𝑡 defines prevalent best position, 𝑍 𝑟𝑎𝑛𝑑 𝑐𝑡 is the remora's prevalent random posture [22].…”

Section: Iterative Process a Sfo Strategymentioning

confidence: 99%

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Energy efficient data transmission using multiobjective improved remora optimization algorithm for wireless sensor network with mobile sink

Jemla Naik,

Parameswarappa,

Ramachandra

2023

IJECE

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<span lang="EN-US">A wireless sensor network (WSN) is a collection of nodes fitted with small sensors and transceiver elements. Energy consumption, data loss, and transmission delays are the major drawback of creating mobile sinks. For instance, battery life and data latency might result in node isolation, which breaks the link between nodes in the network. These issues have been avoided by means of mobile data sinks, which move between nodes with connection issues. Therefore, energy aware multiobjective improved remora optimization algorithm and multiobjective ant colony optimization (EA-MIROA-MACO) is proposed in this research to improve the WSN’s energy efficiency by eliminating node isolation issue. MIRO is utilized to pick the optimal cluster heads (CHs), while multiobjective ant colony optimization (MACO) is employed to find the path through the CHs. The EA-MIROA-MACO aims to optimize energy consumption in nodes and enhance data transmission within a WSN. The analysis of EA-MIROA-MACO’s performance is conducted by considering the number of alive along with dead nodes, average residual energy, and network lifespan. The EA-MIROA-MACO is compared with traditional approaches such as mobile sink and fuzzy based relay node routing (MSFBRR) protocol as well as hybrid neural network (HNN). The EA-MIROA-MACO demonstrates a higher number of alive nodes, specifically 192, over the MSFBRR and HNN for 2,000 rounds.</span>

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“…VANET is a discrete type of mobile ad hoc network in that vehicles are considered nodes and an entire communication usually occurs between vehicles [1,2]. VANET doesn't require any fixed architecture, but the fixed network nodes i.e., Road Side Unit (RSU) are deployed in the network.…”

Section: Introductionmentioning

confidence: 99%

Traffic Aware Routing using Multi-Objective Delay Centric Enhanced Artificial Ecosystem-Based Optimization for VANET

2023

IJIES

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A vehicular Ad hoc Network (VANET) is generally a heterogeneous wireless network generated between vehicles. The vehicles of the VANET have wireless transceivers and computerized control for allowing the vehicles to operate as network nodes, hence the vehicles can communicate in a VANET environment. However, the communication of VANET is affected because of the higher network congestion and energy usage caused by the dynamic topology of VANET. Therefore, an effective Traffic-Aware Routing (TAR) approach is required to be developed to enhance communication. In this paper, the Multi-Objective Delay Centric Enhanced Artificial Ecosystem-based Optimization (MDCEAEO) is proposed to develop a TAR in VANET. The End to End Delay (EED) is considered as primary cost in the MDCEAEO to develop the TAR where a vehicle's average predicted speed is utilized for identifying the traffic in VANET. The developed MDCEAEO-TAR method is used to improve data transmission by avoiding collisions. The performances of MDCEAEO-TAR are evaluated using EED, energy consumption, Packet Delivery Ratio (PDR), and the routing overhead. The existing research such as LARgeoOPT, DREAMgeoOPT, ZRPgeoOPT, Improved Harmony Search (IHS) and Enhanced Distance, Residual energy based Congestion Aware Ant Colony Optimization (EDR-CAACO), Artificial Ecosystem-based Optimization (AEO), FixedStep Average and Subtraction Based Optimizer (FS-ASBO) and Three Influential Members Based Optimizer (TIMBO) are used to evaluate the MDCEAEO-TAR. The PDR of the MDCEAEO-TAR is 0.9836 at 1000s, which is high when compared to the IHS.

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Remora optimization algorithm-based optimized node clustering technique for reliable data delivery in VANETs

Cited by 8 publications

References 8 publications

Blockchain with Quantum Mayfly Optimization-Based Clustering Scheme for Secure and Smart Transport Systems

Blockchain with Quantum Mayfly Optimization-Based Clustering Scheme for Secure and Smart Transport Systems

Energy efficient data transmission using multiobjective improved remora optimization algorithm for wireless sensor network with mobile sink

Traffic Aware Routing using Multi-Objective Delay Centric Enhanced Artificial Ecosystem-Based Optimization for VANET

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