Harris Hawks Optimization-Based Clustering Algorithm for Vehicular Ad-Hoc Networks

Ali, Asad; Aadil, Farhan; Khan, Muhammad Fahad; Maqsood, Muazzam; Lim, Sangsoon

doi:10.1109/tits.2023.3257484

Cited by 18 publications

(10 citation statements)

References 48 publications

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“…The experiment is conducted by using the IEEE 802.11p MAC protocol. In addition to AVOCA, this research also implemented several well-renowned algorithms for clustering in VANET, including CAMONET [ 29 ], SAMNET [ 37 ], I-WOA [ 21 ], and HHOCNET [ 36 ]. As shown in Table 12 , all the algorithms were set to have analogous parameter values.…”

Section: Implementation and Results Analysis For Avocamentioning

confidence: 99%

“…In [ 35 ], authors S.Hosmani and B.Mathapati focus shifts to Robust and Reliable Secure Clustering and Data Transmission (R2 SCDT), which is based on trust values, providing secure and reliable communication. The authors A. Ali et al in [ 36 ] introduce the Harris Hawks Optimization (HHO) algorithm to address network fragmentation, scalability, overhead, and packet routing issues, to improve the performance effectively. In [ 19 ], the authors M.Ahmad et al propose the Vehicular Genetic Bee Clustering (VGBC) approach, which minimizes the size of routing tables through clustering, ultimately reducing overhead in the system.…”

Section: Literature Surveymentioning

confidence: 99%

“…These characteristics challenge traditional mathematical optimization paradigms, such as the Quasi-Newton method and Quadratic Programming. Researchers have also demonstrated that such techniques typically yield only a single solution in a single run, which is insufficient for solving MOPs [ 36 ]. Some Evolutionary Algorithms (EAs) based on nature-inspired have been proposed as competitive alternative solvers for addressing real-world MOPs.…”

Section: Problem Statementmentioning

confidence: 99%

“…When |V sr |>1, vultures enter into the exploration phase and it is mathematically represented by using Eq (36). Finding food in the natural environment will be very difficult, so vultures search for new food at different locations through two different tactics based on the condition.…”

Section: Third Phase: Exploration Stagementioning

confidence: 99%

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Enhancing network stability in VANETs using nature inspired algorithm for intelligent transportation system

Yerrathi,

Pakala

2024

PLoS ONE

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The Internet of Vehicles (IoV) is one of the developing paradigms that integrates the automotive industry with the Internet of Things (IoT). The evolution of traditional Vehicular Ad-hoc Networks (VANETs), which are a layered framework for Intelligent Transportation Systems (ITS), is employed to provide Quality of Service (QoS) to end users in hazardous situations. VANETs can set up ad-hoc networks and share information among themselves using Peer-to-Peer (P2P) communication. Dynamic properties in VANETs such as dynamic topology, node mobility, sparse vehicle distribution, and bandwidth constraints can have an impact on scalability, routing, and security. This can result in frequent link failures, instability, reliability, and QOS concerns, as well as the inherent complexity of NP-hard problems. Researchers have proposed several techniques to achieve stability; the most prominent one is clustering, which relies on mobility metrics. However, existing clustering techniques generate overwhelming clusters, resulting in greater resource consumption, communication overhead, and hop count, which may lead to increased latency. Therefore, the primary objective is to achieve stability by increasing cluster lifetime, which is accomplished by generating optimal clusters. A nature-inspired meta-heuristic algorithm titled African Vulture Optimization Based Clustering Algorithm (AVOCA) is implemented to achieve it. The proposed algorithm can achieve load optimization with efficient resource utilization by mitigating hidden node challenges and ensuring communication proficiency. By maintaining an equilibrium state between the exploration and exploitation phases, AVOCA avoids local optima. The paper explores a taxonomy of the techniques used in Cluster Head (CH) selection, coordination, and maintenance to achieve stability with lower communication costs. We evaluated the effectiveness of AVOCA using various network grid sizes, transmission ranges, and network nodes. The results show that AVOCA generates 40% less clusters when compared to the Clustering Algorithm Based on Moth-Flame Optimization for VANETs (CAMONET). AVOCA generates 45% less clusters when compared to Self-Adaptive Multi-Kernel Clustering for Urban VANETs (SAMNET), AVOCA generates 43% less clusters when compared to Intelligent Whale Optimization Algorithm (i-WOA) and AVOCA generates 38% less clusters when compared to Harris Hawks Optimization (HHO). The results show that AVOCA outperforms state-of-the-art algorithms in generating optimal clusters.

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Section: Implementation and Results Analysis For Avocamentioning

confidence: 99%

Section: Literature Surveymentioning

confidence: 99%

Section: Problem Statementmentioning

confidence: 99%

Section: Third Phase: Exploration Stagementioning

confidence: 99%

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Enhancing network stability in VANETs using nature inspired algorithm for intelligent transportation system

Yerrathi,

Pakala

2024

PLoS ONE

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“…Network sharding and transaction sharding are common choices for most blockchain scaling. Network sharding or Node Sharding (NS) packs nodes into groups, allowing autonomous management within the group to reduce communication complexity [11]. Transaction sharding or Content Sharding (CS) groups data into various network shards, allowing different network shards to store only the content they are interested in [12].…”

Section: Introductionmentioning

confidence: 99%

Cache Optimization Methods Involving Node and Content Sharding of Blockchain in Internet of Vehicles

Zhao,

Ding

2024

Electronics

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Blockchain stands out in addressing the data security requirements of the Internet of Vehicles. However, blockchain has storage pressure that cannot be met by most existing nodes. The emergence of Mobile Edge Computing allows nodes closer to the users to undertake the caching and computation process. Although sharding can alleviate the storage pressure on blockchain nodes, frequent cross-shard communication can affect the overall performance of the blockchain. In this paper, combining the features of traffic flow with strong regional similarity as well as inter-node correlation, we propose two sharding methods based on the current Vehicle–Infrastructure–Clouds three-tier service model. The proposed Content Sharding method can optimize node caching and improve the cache-hitting ratio. The proposed node sharding method can effectively reduce the system service delay by assisting nodes to cache the whole blockchain together across the network.

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VANET cluster-based routing protocol with link breakage handling: introduction to hybrid optimization algorithm

Mahesh,

Jawaligi

2024

SIViP

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Harris Hawks Optimization-Based Clustering Algorithm for Vehicular Ad-Hoc Networks

Cited by 18 publications

References 48 publications

Enhancing network stability in VANETs using nature inspired algorithm for intelligent transportation system

Enhancing network stability in VANETs using nature inspired algorithm for intelligent transportation system

Cache Optimization Methods Involving Node and Content Sharding of Blockchain in Internet of Vehicles

VANET cluster-based routing protocol with link breakage handling: introduction to hybrid optimization algorithm

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