Journal
COMPUTER COMMUNICATIONS
Volume 111, Issue -, Pages 176-186Publisher
ELSEVIER
DOI: 10.1016/j.comcom.2017.08.010
Keywords
Internet of vehicles; Video streaming; Latency model; Traffic density
Categories
Funding
- National Natural Science Foundation of China [61201133, 61571338, 61672131]
- key research and development plan of Shaanxi province [2017ZDCXL-GY-05-01]
- National Key Research and Development Program of China [2016YFE0123000]
- National Science and Technology Major Project of the Ministry of Science and Technology of China [2015zx03002006-003, MJ-2014-S-37]
- Natural Science Foundation of Shaanxi Province [2014JM2-6089]
- National High-tech R&D Program of China (863 Program) [2015AA015701]
- Ningbo Huimin projects of science and technology [2015C50047]
- Research collaboration innovation program of Xi'an [CXY1522-3]
- 111 Project of China [B08038]
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Many applications, such as intelligent transportation systems and mobile multimedia, use Internet of Vehicles (IoV). In boy, users often access multimedia content from anywhere using Internet connectivity to remote video streaming servers. Due to the high mobility of the nodes in IoV, however, maintaining quality of service (QoS) for these video streaming applications with respect to parameters such as jitter, throughput, buffering, and transmission delays is a challenging task. Especially in the urban environment, the performance of a video streaming protocol is significantly affected by the variation of the traffic density. As a result, how to effectively analyze the impact of traffic density as well as vehicular mobility on the QoS of video streaming is the key for the routing protocol design in IoV. In this paper, based on the relationship between the traffic density and the latency characteristics in urban environment, two models are proposed to accurately estimate the video streaming latency according to the average inter-vehicle distance and radio range. After that, an optimal routing strategy is given by selecting the path from all available paths to minimize the experienced latency for video streaming. Numerical results show that in urban environments, our proposed model has high accuracy under different configurations. (C) 2017 Elsevier B.V. All rights reserved.
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