Enhancement in Quality of Routing Service Using Metaheuristic PSO Algorithm in VANET Networks

Javadpour, Amir; Rezaei, Samira; Sangaiah, Arun Kumar; Słowik, Adam; Khaniabadi, Shadi Mahmoodi

doi:10.1007/s00500-021-06188-0

Cited by 21 publications

(4 citation statements)

References 28 publications

(22 reference statements)

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“…In [ 8 ], the authors X.Bao et al employ Particle Swarm Optimization (PSO) not only for defining CH but also for route optimization within VANETs. In [ 34 ] the authors S.A.Javadpour et al strengthens road protection in VANETs by detecting unpredictable problems and replacing broken paths with immediate effect based on Quality of Service Routing (QoSR) and Particle Swarm Optimization (QoSR-PSO) information.…”

Section: Literature Surveymentioning

confidence: 99%

“…Where V sr denotes that the W th vultures' starvation rate at the i th iteration. rand i w1 is a random number between [0, 1], Z i is a random number between [-1, 1] that changes at each iteration, the value gives the vultures hunger state based on the condition given in Eq (34). itr i denotes the current iteration number, mitr i denote the total number of iterations, k is a parameter with a fixed number set which indicates the optimization operation based on the condition given in Eq (35).…”

Section: Second Phase: Computing Vultures Starvation Ratementioning

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: Literature Surveymentioning

confidence: 99%

Section: Second Phase: Computing Vultures Starvation Ratementioning

confidence: 99%

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

Yerrathi,

Pakala

2024

PLoS ONE

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“…This protocol indicates a dependable and standard cluster and rises the durability and connectedness at the time of transmissions. Javadpour et al [14] decrease the impacts of unexpected issues on the best track for replacing the broken link or path. A QoSR having Particle Swarm Optimization (QoSR-PSO) is utilized in this work to enhance QoSs in vehicular ad hoc network systems.…”

Section: Related Workmentioning

confidence: 99%

Metaheuristics-based Clustering with Routing Technique for Lifetime Maximization in Vehicular Networks

Muthukrishnan¹,

Kannan²

2023

Computers, Materials &Amp; Continua

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Recently, vehicular ad hoc networks (VANETs) finds applicability in different domains such as security, rescue operations, intelligent transportation systems (ITS), etc. VANET has unique features like high mobility, limited mobility patterns, adequate topology modifications, and wireless communication. Despite the benefits of VANET, scalability is a challenging issue which could be addressed by the use of cluster-based routing techniques. It enables the vehicles to perform intercluster communication via chosen CHs and optimal routes. The main drawback of VANET network is the network unsteadiness that results in minimum lifetime. In order to avoid reduced network lifetime in VANET, this paper presents an enhanced metaheuristics based clustering with multihop routing technique for lifetime maximization (EMCMHR-LM) in VANET. The presented EMCMHR-LM model involves the procedure of arranging clusters, cluster head (CH) selection, and route selection appropriate for VANETs. The presented EMCMHR-LM model uses slime mold optimization based clustering (SMO-C) technique to group the vehicles into clusters. Besides, an enhanced wild horse optimization based multihop routing (EWHO-MHR) protocol by the optimization of network parameters. The presented EMCMHR-LM model is simulated using Network Simulator (NS3) tool and the simulation outcomes reported the enhanced performance of the proposed EMCMHR-LM technique over the other models.

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“…They did not use a fault tolerance mechanism for data offloading and fog for data processing to reduce delay as compared with the proposed model. Similarly, in [ 30 ] the author proposed QoS aware vehicle communication model using the clustering technique. They reduced packet drop ratio and messages delay.…”

Section: Literature Reviewmentioning

confidence: 99%

QoS Aware and Fault Tolerance Based Software-Defined Vehicular Networks Using Cloud-Fog Computing

Syed

Rashid

Amir

et al. 2022

Sensors

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Software-defined network (SDN) and vehicular ad-hoc network (VANET) combined provided a software-defined vehicular network (SDVN). To increase the quality of service (QoS) of vehicle communication and to make the overall process efficient, researchers are working on VANET communication systems. Current research work has made many strides, but due to the following limitations, it needs further investigation and research: Cloud computing is used for messages/tasks execution instead of fog computing, which increases response time. Furthermore, a fault tolerance mechanism is used to reduce the tasks/messages failure ratio. We proposed QoS aware and fault tolerance-based software-defined V vehicular networks using Cloud-fog computing (QAFT-SDVN) to address the above issues. We provided heuristic algorithms to solve the above limitations. The proposed model gets vehicle messages through SDN nodes which are placed on fog nodes. SDN controllers receive messages from nearby SDN units and prioritize the messages in two different ways. One is the message nature way, while the other one is deadline and size way of messages prioritization. SDN controller categorized in safety and non-safety messages and forward to the destination. After sending messages to their destination, we check their acknowledgment; if the destination receives the messages, then no action is taken; otherwise, we use a fault tolerance mechanism. We send the messages again. The proposed model is implemented in CloudSIm and iFogSim, and compared with the latest models. The results show that our proposed model decreased response time by 50% of the safety and non-safety messages by using fog nodes for the SDN controller. Furthermore, we reduced the execution time of the safety and non-safety messages by up to 4%. Similarly, compared with the latest model, we reduced the task failure ratio by 20%, 15%, 23.3%, and 22.5%.

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Enhancement in Quality of Routing Service Using Metaheuristic PSO Algorithm in VANET Networks

Cited by 21 publications

References 28 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

Metaheuristics-based Clustering with Routing Technique for Lifetime Maximization in Vehicular Networks

QoS Aware and Fault Tolerance Based Software-Defined Vehicular Networks Using Cloud-Fog Computing

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