Vehicular delay tolerant network routing algorithm based on trajectory clustering and dynamic Bayesian network

Wu, Jiagao; Cai, Shenlei; Jin, Hui‐Zi; Liu, Linfeng

doi:10.1007/s11276-023-03239-2

Cited by 4 publications

(4 citation statements)

References 24 publications

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“…The former regards each trajectory sample as a cluster and gradually merges into larger clusters by defining the similarity between clusters; the latter gradually divides the trajectory data set into smaller groups by using the idea of divide and conquer until it meets the requirements of clustering. Supervised trajectory clustering algorithm is represented by the K-NN algorithm [ 38 ] and statistical model method [ 39 ]. The K-NN algorithm uses the average nearest distance as the evaluation criterion to realize trajectory clustering.…”

Section: Related Workmentioning

confidence: 99%

Hierarchical Clustering Algorithm for Multi-Camera Vehicle Trajectories Based on Spatio-Temporal Grouping under Intelligent Transportation and Smart City

Wang

Xie

Tang

2023

Sensors

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With the emergence of intelligent transportation and smart city system, the issue of how to perform an efficient and reasonable clustering analysis of the mass vehicle trajectories on multi-camera monitoring videos through computer vision has become a significant area of research. The traditional trajectory clustering algorithm does not consider camera position and field of view and neglects the hierarchical relation of the video object motion between the camera and the scenario, leading to poor multi-camera video object trajectory clustering. To address this challenge, this paper proposed a hierarchical clustering algorithm for multi-camera vehicle trajectories based on spatio-temporal grouping. First, we supervised clustered vehicle trajectories in the camera group according to the optimal point correspondence rule for unequal-length trajectories. Then, we extracted the starting and ending points of the video object under each group, hierarchized the trajectory according to the number of cross-camera groups, and supervised clustered the subsegment sets of different hierarchies. This method takes into account the spatial relationship between the camera and video scenario, which is not considered by traditional algorithms. The effectiveness of this approach has been proved through experiments comparing silhouette coefficient and CPU time.

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Section: Related Workmentioning

confidence: 99%

Hierarchical Clustering Algorithm for Multi-Camera Vehicle Trajectories Based on Spatio-Temporal Grouping under Intelligent Transportation and Smart City

Wang

Xie

Tang

2023

Sensors

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“…Authors in Reference 34, proposed a DTN routing protocol by using multistep double Q‐learning approach called K‐DQLR. The authors addressed the next hope selection issue of DTN networks due to sparse node distribution, frequent nodes movement and limited communication range.…”

Section: Related Workmentioning

confidence: 99%

Congestion aware reward based scheme based on delay tolerant networks for emergency evacuation in 6G‐based internet of things networks

Awan

Tariq

Qureshi

et al. 2023

Trans Emerging Tel Tech

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Internet of Things (IoT) networks are based on advanced augmented reality‐based applications for better services. These advanced networks are always at threat due to different disasters in an urban congested environment. Delay tolerant networks is one of the well‐known solutions with various features. However, due to heavy data traffic, it suffered from congestion and selfish behavior issues. The existing solutions endeavored to mitigate selfishness and enforce nodes to cooperate which leads to congestion. The information concerning other nodes in the network is needed and to be maintained, stored, and shared. In this article, the issue of the occurrence of congestion while mitigating the selfish behavior of nodes is taken into account, especially for augmented reality (AR) and 6 G‐based IoT networks. This article proposes a credit‐based congestion aware reward‐based scheme for enforcing nodes to cooperate to refrain from selfishness. The load‐sharing technique handles the congestion in 6G/AR‐based IoT networks where the messages are shifted to low or non‐congested nodes rather than dropping them. Simulation results affirm the efficacy of the proposed scheme in terms of data delivery ratio, network overhead, energy consumption, and latency and outperform compare to the state‐of‐the‐art schemes.

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“…GR-PDR [31] solves the local maxima issue by using the delegation replication approach for both single and multiple copy forwarding, considering a buffer delivery priority. [32] proposes an improved VDTN routing based on K-means clustering.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Glowworm Swarm Optimization (GSO) GSO is a swarm-inspired metaheuristic suggested by [32] to model the collective movement of lightning flies called glowworms. This movement is controlled by the changing quantity of a luminescent substance called luciferin.…”

Section: ) Local Search Scf Selection Using Glowworm Swarmmentioning

confidence: 99%

Bio-inspired Probabilistic Opportunistic Routing for Vehicular Delay-Tolerant Networks Using A Hybrid Swarm Approach

Azzoug,

Boukra

2023

JTEC

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Vehicular Delay Tolerant Network (VDTN) routing has been improved using probabilistic routing to improve the coverage of intermittent vehicular networks. VDTNs are characterized by large transmission ranges of vehicles, rapid vehicular speeds, and restricted mobility movements, particularly in urban areas. As a result, the probabilistic Sore-Carry-and-Forward (SCF) relay vehicle selection can be inaccurate when considering remote vehicles, leading to high overheads. To address this issue, a new bio-inspired VDTN routing protocol is proposed to better estimate the SCF capabilities of remote vehicles so that the duplicated generated bundles’ copies are reduced without altering the bundles’ delivery ratio and average delivery delay. This solution sequentially employs the Ant Colony Optimizer (ACO) and Glowworm Swarm Optimization (GSO) to adaptively control the replication of bundle copies at each bundle forwarding stage based on predefined probabilistic forwarding parameters. Simulation results from a sparse urban mobility scenario show reduced bundle replication rates compared to several probabilistic VDTN routing protocols.

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Vehicular delay tolerant network routing algorithm based on trajectory clustering and dynamic Bayesian network

Cited by 4 publications

References 24 publications

Hierarchical Clustering Algorithm for Multi-Camera Vehicle Trajectories Based on Spatio-Temporal Grouping under Intelligent Transportation and Smart City

Hierarchical Clustering Algorithm for Multi-Camera Vehicle Trajectories Based on Spatio-Temporal Grouping under Intelligent Transportation and Smart City

Congestion aware reward based scheme based on delay tolerant networks for emergency evacuation in 6G‐based internet of things networks

Bio-inspired Probabilistic Opportunistic Routing for Vehicular Delay-Tolerant Networks Using A Hybrid Swarm Approach

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