ODCRep: Origin–Destination-Based Content Replication for Vehicular Networks

Silva, Fabricio A.; Boukerche, Azzedine; Silva, Thais R. M. Braga; Benevenuto, Fabrí­cio; Ruiz, Linnyer B.; Loureiro, Antônio A. F.

doi:10.1109/tvt.2015.2487679

Cited by 11 publications

(2 citation statements)

References 38 publications

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“…Some methods first tessellate the city with horizontal and vertical guidelines and then estimate the travel times based on the tiles that the origin and destination of a trip fall into. Other similar statistical models have been proposed to estimate the travel times based on the trips that have similar origin/destination pair to the query trip [16,17,18].…”

Section: Origin-destination-based Approachesmentioning

confidence: 99%

Real-time Travel Time Estimation Using Matrix Factorization

Badrestani,

Bahrak,

Elahi

et al. 2019

Preprint

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Estimating the travel time of any route is of great importance for trip planners, traffic operators, online taxi dispatching and ride-sharing platforms, and navigation provider systems. With the advance of technology, many traveling cars, including online taxi dispatch systems' vehicles are equipped with Global Positioning System (GPS) devices that can report the location of the vehicle every few seconds. This paper uses GPS data and the Matrix Factorization techniques to estimate the travel times on all road segments and time intervals simultaneously. We aggregate GPS data into a matrix, where each cell of the original matrix contains the average vehicle speed for a segment and a specific time interval. One of the problems with this matrix is its high sparsity. We use Alternating Least Squares (ALS) method along with a regularization term to factorize the matrix. Since this approach can solve the sparsity problem that arises from the absence of cars in many road segments in a specific time interval, matrix factorization is suitable for estimating the travel time. Our comprehensive evaluation results using real This research is fully supported by Tap30 co, an online taxi-hailing company in Iran

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Section: Origin-destination-based Approachesmentioning

confidence: 99%

Real-time Travel Time Estimation Using Matrix Factorization

Badrestani,

Bahrak,

Elahi

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…Experiments based on real vehicle GPS traces show a high access ratio. In [ 19 , 20 ], two origin-destination-based content replication schemes, i.e., ODCRep and GO-DCR, select appropriate nodes to replicate contents based on the vehicles’ origin and destination points. Specifically, ODCRep controls the number of replicas in the scenario via efficient algorithms, and hence achieves high coverage and saves resources, while GO-DCR, as a geo-localized solution, increases content availability and reduces delivery cost.…”

Section: Related Workmentioning

confidence: 99%

Data Acquisition Based on Stable Matching of Bipartite Graph in Cooperative Vehicle–Infrastructure Systems

Tang

Hong

Chen

2017

Sensors

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Existing studies on data acquisition in vehicular networks often take the mobile vehicular nodes as data carriers. However, their autonomous movements, limited resources and security risks impact the quality of services. In this article, we propose a data acquisition model using stable matching of bipartite graph in cooperative vehicle-infrastructure systems, namely, DAS. Contents are distributed to roadside units, while vehicular nodes support supplementary storage. The original distribution problem is formulated as a stable matching problem of bipartite graph, where the data and the storage cells compose two sides of vertices. Regarding the factors relevant with the access ratio and delay, the preference rankings for contents and roadside units are calculated, respectively. With a multi-replica preprocessing algorithm to handle the potential one-to-many mapping, the matching problem is addressed in polynomial time. In addition, vehicular nodes carry and forward assistant contents to deliver the failed packets because of bandwidth competition. Furthermore, an incentive strategy is put forward to boost the vehicle cooperation and to achieve a fair bandwidth allocation at roadside units. Experiments show that DAS achieves a high access ratio and a small storage cost with an acceptable delay.

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Reputation Based Content Delivery in Information Centric Vehicular Networks

Hui

Luan

et al. 2020

Wireless Networks

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ODCRep: Origin–Destination-Based Content Replication for Vehicular Networks

Cited by 11 publications

References 38 publications

Real-time Travel Time Estimation Using Matrix Factorization

Real-time Travel Time Estimation Using Matrix Factorization

Data Acquisition Based on Stable Matching of Bipartite Graph in Cooperative Vehicle–Infrastructure Systems

Reputation Based Content Delivery in Information Centric Vehicular Networks

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