Open Access

ARTICLE

Container Based Nomadic Vehicular Cloud Using Cell Transmission Model

Devakirubai Navulkumar^1,*, Menakadevi Thangavelu²

1 Department of Computer Science and Engineering, Jayam College of Engineering and Technology, Dharmapuri, 636813, India
2 Department of Electronics and Communication Engineering, Adhiyaman College of Engineering, Hosur, 635109, India

* Corresponding Author: Devakirubai Navulkumar. Email:

Computer Systems Science and Engineering 2023, 44(1), 423-440. https://doi.org/10.32604/csse.2023.025166

Received 14 November 2021; Accepted 07 January 2022; Issue published 01 June 2022

Abstract

Nomadic Vehicular Cloud (NVC) is envisaged in this work. The predominant aspects of NVC is, it moves along with the vehicle that initiates it and functions only with the resources of moving vehicles on the heavy traffic road without relying on any of the static infrastructure and NVC decides the initiation time of container migration using cell transmission model (CTM). Containers are used in the place of Virtual Machines (VM), as containers’ features are very apt to NVC’s dynamic environment. The specifications of 5G NR V2X PC5 interface are applied to NVC, for the feature of not relying on the network coverage. Nowadays, the peak traffic on the road and the bottlenecks due to it are inevitable, which are seen here as the benefits for VC in terms of resource availability and residual in-network time. The speed range of high-end vehicles poses the issue of dis-connectivity among VC participants, that results the container migration failure. As the entire VC participants are on the move, to maintain proximity of the containers hosted by them, estimating their movements plays a vital role. To infer the vehicle movements on the road stretch and initiate the container migration prior enough to avoid the migration failure due to vehicles dynamicity, this paper proposes to apply the CTM to the container based and 5G NR V2X enabled NVC. The simulation results show that there is a significant increase in the success rate of vehicular cloud in terms of successful container migrations.

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Keywords

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