Title: Target node selection for data offloading in partially connected vehicular ad hoc networks

Authors: Shailendra Shukla

Addresses: Computer Science and Engineering Department, MNNIT Allahabad, India

Abstract: VANET generates large data, which can be addressed as the problem of data offloading. A naive approach would utilise infrastructure like road side unit (RSU), femtocell, or Wi-Fi access point (AP). However, increasing the number of cellular towers, Wi-Fi, or femtocell is costlier, requires high maintenance, and has low RoI. This paper proposes a data offloading approach for effective data delivery. The significant contribution of this paper is threefold: 1) a hybrid approach for data offloading where both V2I and V2V are explored to detect an optimised target-set selection; 2) a selection encounter index methodology for the articulation point detection is proposed; 3) a novel policy-based relay selection and storage selection methodology is proposed. The result shows that the proposed algorithm requires 10% to 30% less energy for target set selection, 50% times less load delay, and a 40% high delivery ratio compared to the community and epidemic approach.

Keywords: vehicular ad hoc networks; VANET; data offloading; K-means; cut-vertex; target set selection.

DOI: 10.1504/IJAHUC.2023.128491

International Journal of Ad Hoc and Ubiquitous Computing, 2023 Vol.42 No.2, pp.113 - 123

Received: 07 Jul 2021
Accepted: 07 Mar 2022
Published online: 24 Jan 2023 *

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