Adaptive fuzzy‐based message dissemination and micro‐artificial bee colony algorithm optimised routing scheme for vehicular
            <i>ad hoc</i>
            network

Patil, Saurabh D.; Ragha, Lata

doi:10.1049/iet-com.2019.0388

Cited by 18 publications

(3 citation statements)

References 24 publications

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“…The car's built-in wireless network allows data transfer to its receiver in a multi-hop method through subsequent vehicle nodes [8]. The author builds the backbone in the basic backbone design by selecting speci c nodes and collecting position data about rapidly changing nodes [9]. Another standard model for vehicle communication is the cluster-based approach, which considers groups of nodes to constitute a cluster.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Distance and Connectivity Based Traffic Density Stable Routing Protocol (TDSRP-DC) for Vehicular Ad Hoc Networks

Selvaraj¹,

Ramalingam²,

Mohan

et al. 2023

Preprint

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Vehicle ad-hoc networks (VANETs) have become a prominent research topic in recent years due to rapid dynamic topology, high vehicle mobility, frequent link failures and significant delay constraints. The mobility of the vehicle nodes increases, and the overhead of control traffic due to the high dynamics of the VANET. Efficient routing algorithms are necessary for VANETs to ensure reliable transmission (VANETs). This work proposes a Traffic Density Stable Routing Protocol based on Connection- and Distance (TDSRP-DC) to avoid data packet collisions at intersections and an adaptive routing schedule based on the selection at every instant. Our approach is based on vehicle-to-vehicle communication. Ground vehicles identify the most appropriate next junction and transfer the data packet to the receiver to find the optimal multi-hop route. It relies on transferring the data between all vehicles to estimate real-time traffic fluctuations sporadically. Network formation, neighbor realization, fitness value prediction, and routing methodology are the conceptual process needed in this research. Valid parameters for finding the optimum path in the conceptual model include node distance, node speed, node azimuth, link stability, and link reliability. The suggested solution's simulation was performed in comparison to traditional algorithms. Compared to existing TFOR algorithms on complex traffic, the proposed TDSRP-DC provides tremendous improvements based on packet delivery rate (10%) and performance (35%). The demonstrated results and comparisons illustrate the proposed routing protocol's significance with enhanced quality of service performance.

show abstract

Section: Introductionmentioning

confidence: 99%

An Efficient Distance and Connectivity Based Traffic Density Stable Routing Protocol (TDSRP-DC) for Vehicular Ad Hoc Networks

Selvaraj¹,

Ramalingam²,

Mohan

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…This preference of CHs with dual wireless backbone networks makes the election of suitable CH as a more challenging task in VANETs. Hence, this problem of facilitating optimal clustering in VANETs pertains to the class of non‐polynomial‐hard (NP‐Hard) problems 13 . These NP‐Hard problems of clustering necessitates only an acceptable near‐optimal solutions as the perfect solutions are completely hard to achieve.Many conventional algorithms were proposed for addressing these issues in the similar domain, but they failed to attain an ideal solution in the clustering process.…”

Section: Introductionmentioning

confidence: 99%

Border Collie optimization algorithm‐based node clustering technique in vehicular ad hoc networks

Godi¹,

Janakiraman²

2022

Trans Emerging Tel Tech

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In vehicular ad hoc networks (VANETs), the nodes are vehicles and these vehicles communicate with one another on the road. The vehicular nodes on the road move continuously and it introduces dynamic changes in the topology of the network. When the node density in the vehicular network is high, then it is still more challenging as these situations introduce different challenges for network scalability and hurdles the process of determining an optimal route in the vehicular network. At this juncture, clustering protocols are often utilized for resolving the issue of network scalability and the factors that hinders process of identifying optimal routes in vehicular network. In this article, Border Collie optimization algorithm‐based node clustering technique (BCOA‐NCT) is proposed for achieving optimal cluster head selection that minimizes network overhead in uncertain node density situations. This BCOA‐NCT is proposed for facilitating equal concentration on both exploitation and exploration during the process of clustering. It utilized the strategy of eyeing for preventing the algorithm from being stuck into local optima during the cluster head selection process. The simulation experiments of the proposed BCOA‐NCT and the benchmarked schemes confirmed better throughput of 6.19%, minimized end‐to‐end delay of 7.24%, reduced mean energy consumptions of 6.89%, and reduction in the number of beacon messages utilized by 8.26% under the impact of different density of vehicular node. The outcome of the results indicated that the proposed BCOA‐NCT on par with the baseline approaches is capable enough in handling the issue of scalability and better estimation of optimal routes under the increase of node density in the vehicular network.

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“…Given the NP‐complete nature of the load‐balancing problem in the SDN [1], we can solve it by a meta‐heuristic method. The artificial bee colony (ABC) algorithm [7] and the genetic algorithm (GA) are two meta‐heuristic algorithms with distributed computing. ABC is encouraged by the foraging conduct of a honey bee swarm.…”

Section: Introductionmentioning

confidence: 99%

Energy‐aware dynamic‐link load balancing method for a software‐defined network using a multi‐objective artificial bee colony algorithm and genetic operators

et al. 2020

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Adaptive fuzzy‐based message dissemination and micro‐artificial bee colony algorithm optimised routing scheme for vehicular ad hoc network

Cited by 18 publications

References 24 publications

An Efficient Distance and Connectivity Based Traffic Density Stable Routing Protocol (TDSRP-DC) for Vehicular Ad Hoc Networks

An Efficient Distance and Connectivity Based Traffic Density Stable Routing Protocol (TDSRP-DC) for Vehicular Ad Hoc Networks

Border Collie optimization algorithm‐based node clustering technique in vehicular ad hoc networks

Energy‐aware dynamic‐link load balancing method for a software‐defined network using a multi‐objective artificial bee colony algorithm and genetic operators

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