Status | 已发表Published |
Title | Towards 5G-Enabled Self Adaptive Green and Reliable Communication in Intelligent Transportation System |
Creator | |
Date Issued | 2021-08-01 |
Source Publication | IEEE Transactions on Intelligent Transportation Systems
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ISSN | 1524-9050 |
Volume | 22Issue:8Pages:1558-0016 |
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. |
Keyword | 5G cross layer green and reliable communication ITS mobility self-adaptive |
DOI | 10.1109/TITS.2020.3019227 |
URL | View source |
Indexed By | SCIE |
Language | 英语English |
WOS Research Area | Engineering ; Transportation |
WOS Subject | Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology |
WOS ID | WOS:000684003100044 |
Scopus ID | 2-s2.0-85106993981 |
Citation statistics | |
Document Type | Journal article |
Identifier | http://repository.uic.edu.cn/handle/39GCC9TT/5982 |
Collection | Faculty of Science and Technology |
Corresponding Author | Luo, Zongwei |
Affiliation | 1.Department of Computer Science Electrical and Space Engineering,Luleå University of Technology,Lulea,97187,Sweden 2.Department of Computer Science,University of Beira Interior,Covilhã,6201-001,Portugal 3.Department of Physics,Shah Abdul Latif University,Khairpur,66111,Pakistan 4.Department of Computer Science,Bahria University,Islamabad,44000,Pakistan 5.Division of Science and Technology,United International College,BNU-HKBU,Zhuihai,519085,China 6.Computer and Information Science Department,Linkoping University,Linkoping,58183,Sweden 7.Department of Computer Science,University of Fortaleza,Fortaleza,60811-905,Brazil 8.Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,Shenzhen,518055,China 9.Instituto de Telecomunicações,University of Beira Interior,Covilhã,6201-001,Portugal |
Corresponding Author Affilication | Beijing Normal-Hong Kong Baptist University |
Recommended Citation GB/T 7714 | Sodhro,Ali Hassan,Pirbhulal,Sandeep,Sodhro,Gul Hassanet al. Towards 5G-Enabled Self Adaptive Green and Reliable Communication in Intelligent Transportation System[J]. IEEE Transactions on Intelligent Transportation Systems, 2021, 22(8): 1558-0016. |
APA | Sodhro,Ali Hassan., Pirbhulal,Sandeep., Sodhro,Gul Hassan., Muzammal,Muhammad., Luo, Zongwei., .. & De Albuquerque,Victor Hugo C. (2021). Towards 5G-Enabled Self Adaptive Green and Reliable Communication in Intelligent Transportation System. IEEE Transactions on Intelligent Transportation Systems, 22(8), 1558-0016. |
MLA | Sodhro,Ali Hassan,et al."Towards 5G-Enabled Self Adaptive Green and Reliable Communication in Intelligent Transportation System". IEEE Transactions on Intelligent Transportation Systems 22.8(2021): 1558-0016. |
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