Evidence map›Paper›PMID 36429833›Full record

ArticleInternational journal of environmental research and public health2022

An Environmentally Sustainable Software-Defined Networking Data Dissemination Method for Mixed Traffic Flows in RSU Clouds with Energy Restriction.

Hongming Li, Dongxiu Ou, Yuqing Ji

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Hongming LiKey Laboratory of Road and Traffic Engineering, Ministry of Education, School of Transportation Engineering, Tongji University, Shanghai 201804, China.ORCID 0000-0003-0290-7645
Dongxiu OuKey Laboratory of Railway Industry of Proactive Safety and Risk Control, School of Transportation Engineering, Tongji University, Shanghai 201804, China.
Yuqing JiKey Laboratory of Road and Traffic Engineering, Ministry of Education, School of Transportation Engineering, Tongji University, Shanghai 201804, China.ORCID 0000-0002-3442-3349

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The connected multi road side unit (RSU) environment can be envisioned as the RSU cloud. In this paper, the Software-Defined Networking (SDN) framework is utilized to dynamically reconfigure the RSU clouds for the mixed traffic flows with energy restrictions, which are composed of five categories of vehicles with distinctive communication demands. An environmentally sustainable SDN data dissemination method for safer and greener transportation solutions is thus proposed, aiming to achieve the lowest overall SDN cloud delay with the least working hosts and minimum energy consumption, which is a mixed integer linear programming problem (MILP). To solve the problem, Joint optimization algorithms with Finite resources (JF) in three hyperparameters versions, JF (DW = 0.3, HW = 0.7), JF (DW = 0.5, HW = 0.5) and JF (DW = 0.7, HW = 0.3), were proposed, which are in contrast with single-objective optimization algorithms, the Host Optimization (H) algorithm, and the Delay optimization (D) algorithm. Results show that JF (DW = 0.3, HW = 0.7) and JF (DW = 0.5, HW = 0.5), when compared with the D algorithm, usually had slightly larger cloud delays, but fewer working hosts and energy consumptions, which has vital significance for enhancing energy efficiency and environmental protection, and shows the superiority of JFs over the D algorithm. Meanwhile, the H algorithm had the least working hosts and fewest energy consumptions under the same conditions, but completely ignored the explosive surge of delay, which is not desirable for most cases of the SDN RSU cloud. Further analysis showed that the larger the network topology of the SDN cloud, the harder it was to find a feasible network configuration. Therefore, when designing an environmentally sustainable SDN RSU cloud for the greener future mobility of intelligent transportation systems, its size should be limited or partitioned into a relatively small topology.

Indexed as

Computer Communication NetworksSoftwareAlgorithmsPhysical PhenomenaProgramming, Linearcloud resource management (CRM)energy consumptionsenergy restrictionenvironmental sustainabilityintelligent transportation systems (ITS)mobile edge computing (MEC)software-defined networks (SDN)

Identifiers

PMID36429833
PMCPMC9690847

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.