Towards 5G-Enabled Self Adaptive Green and Reliable Communication in Intelligent Transportation System

Ali Hassan Sodhro, Sandeep Pirbhulal, Gul Hassan Sodhro, Muhammad Muzammal, Luo Zongwei*, Andrei Gurtov, Antônio Roberto L. de Macêdo, Lei Wang, Nuno M. Garcia, Victor Hugo C. de Albuquerque

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)

Abstract

Fifth generation (5G) technologies have become the center of attention in managing and monitoring high-speed transportation system effectively with the intelligent and self-adaptive sensing capabilities. Besides, the boom in portable devices has witnessed a huge breakthrough in the data driven vehicular platform. However, sensor-based Internet of Things (IoT) devices are playing the major role as edge nodes in the intelligent transportation system (ITS). Thus, due to high mobility/speed of vehicles and resource-constrained nature of edge nodes more data packets will be lost with high power drain and shorter battery life. Thus, this research significantly contributes in three ways. First, 5G-based self-adaptive green (i.e., energy efficient) algorithm is proposed. Second, a novel 5G-driven reliable algorithm is proposed. Proposed joint energy efficient and reliable approach contains four layers, i.e., application, physical, networks, and medium access control. Third, a novel joint energy efficient and reliable framework is proposed for ITS. Moreover, the energy and reliability in terms of received signal strength (RSSI) and hence packet loss ratio (PLR) optimization is performed under the constraint that all transmitted packets must utilize minimum transmission power with high reliability under particular active time slot. Experimental results reveal that the proposed approach (with Cross Layer) significantly obtains the green (55%) and reliable (41%) ITS platform unlike the Baseline (without Cross Layer) for aging society.

Original languageEnglish
Pages (from-to)5223-5231
Number of pages9
JournalIEEE Transactions on Intelligent Transportation Systems
Volume22
Issue number8
Early online date18 Sept 2020
DOIs
Publication statusPublished - Aug 2021
Externally publishedYes

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