Energy efficiency plays an important role in the Internet of vehicles, but it is very difficult to fit the need of QoS (Quality of Service) and energy efficiency at the same time. Here a QoS order is proposed for the Internet of vehicles. First, the multi attribute decision making of QoS in the Internet of vehicles is illustrated here. Then a QoS optimization with energy efficiency is set up to seek prior choice. Second, regarding uncertain attributes to the QoS optimization, a fuzzy QoS tool is introduced to optimize its performance. Third, a comprehensive experimental analysis of fuzzy QoS results is presented to verify its effectiveness and compare with other references. Last, some interesting conclusions and future research work are indicated at the end of the paper.
Published in | Advances in Networks (Volume 4, Issue 2) |
DOI | 10.11648/j.net.20160402.13 |
Page(s) | 34-44 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2016. Published by Science Publishing Group |
The Internet of Vehicles, Fuzzy QoS, Energy Efficiency, Decision Analysis
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APA Style
Shaoqi Hu, Hongmei Fan, Zhende Wang, Zhengying Cai. (2016). A Fuzzy QoS Optimization Method with Energy Efficiency for the Internet of Vehicles. Advances in Networks, 4(2), 34-44. https://doi.org/10.11648/j.net.20160402.13
ACS Style
Shaoqi Hu; Hongmei Fan; Zhende Wang; Zhengying Cai. A Fuzzy QoS Optimization Method with Energy Efficiency for the Internet of Vehicles. Adv. Netw. 2016, 4(2), 34-44. doi: 10.11648/j.net.20160402.13
@article{10.11648/j.net.20160402.13, author = {Shaoqi Hu and Hongmei Fan and Zhende Wang and Zhengying Cai}, title = {A Fuzzy QoS Optimization Method with Energy Efficiency for the Internet of Vehicles}, journal = {Advances in Networks}, volume = {4}, number = {2}, pages = {34-44}, doi = {10.11648/j.net.20160402.13}, url = {https://doi.org/10.11648/j.net.20160402.13}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.net.20160402.13}, abstract = {Energy efficiency plays an important role in the Internet of vehicles, but it is very difficult to fit the need of QoS (Quality of Service) and energy efficiency at the same time. Here a QoS order is proposed for the Internet of vehicles. First, the multi attribute decision making of QoS in the Internet of vehicles is illustrated here. Then a QoS optimization with energy efficiency is set up to seek prior choice. Second, regarding uncertain attributes to the QoS optimization, a fuzzy QoS tool is introduced to optimize its performance. Third, a comprehensive experimental analysis of fuzzy QoS results is presented to verify its effectiveness and compare with other references. Last, some interesting conclusions and future research work are indicated at the end of the paper.}, year = {2016} }
TY - JOUR T1 - A Fuzzy QoS Optimization Method with Energy Efficiency for the Internet of Vehicles AU - Shaoqi Hu AU - Hongmei Fan AU - Zhende Wang AU - Zhengying Cai Y1 - 2016/12/26 PY - 2016 N1 - https://doi.org/10.11648/j.net.20160402.13 DO - 10.11648/j.net.20160402.13 T2 - Advances in Networks JF - Advances in Networks JO - Advances in Networks SP - 34 EP - 44 PB - Science Publishing Group SN - 2326-9782 UR - https://doi.org/10.11648/j.net.20160402.13 AB - Energy efficiency plays an important role in the Internet of vehicles, but it is very difficult to fit the need of QoS (Quality of Service) and energy efficiency at the same time. Here a QoS order is proposed for the Internet of vehicles. First, the multi attribute decision making of QoS in the Internet of vehicles is illustrated here. Then a QoS optimization with energy efficiency is set up to seek prior choice. Second, regarding uncertain attributes to the QoS optimization, a fuzzy QoS tool is introduced to optimize its performance. Third, a comprehensive experimental analysis of fuzzy QoS results is presented to verify its effectiveness and compare with other references. Last, some interesting conclusions and future research work are indicated at the end of the paper. VL - 4 IS - 2 ER -