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المؤلفQiao, Wenxuan
المؤلفDong, Ping
المؤلفDu, Xiaojiang
المؤلفZhang, Yuyang
المؤلفZhang, Hongke
المؤلفGuizani, Mohsen
تاريخ الإتاحة2022-10-11T09:04:47Z
تاريخ النشر2022-05-01
اسم المنشورJournal of Parallel and Distributed Computing
المعرّفhttp://dx.doi.org/10.1016/j.jpdc.2022.01.018
الاقتباسQiao, W., Dong, P., Du, X., Zhang, Y., Zhang, H., & Guizani, M. (2022). QoS provision for vehicle big data by parallel transmission based on heterogeneous network characteristics prediction. Journal of Parallel and Distributed Computing, 163, 83-96.‏
الرقم المعياري الدولي للكتاب07437315
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85124297577&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/35006
الملخصMultipath parallel transmission has become an important research direction to improve big data transmission efficiency of connected vehicles. However, due to the heterogeneity and time-varying characteristics of parallel transmission paths, packets transmitted in parallel are usually out-of-order delivered to the destination, which greatly limits the throughput. To Lift the restriction of out-of-order delivery on the efficiency of big data transmission, this paper proposes a packet-granular real-time shortest delay scheduling scheme for multipath transmission based on path characteristics prediction. The scheme first clusters and models the heterogeneous network, which greatly reduces the complexity of the network. Subsequently, a prediction algorithm that can quickly converge to real-time delay is proposed. Then the details of the scheduling scheme are introduced by modules, and the bandwidth aggregation efficiency close to the theoretical upper limit is proved through simulation. Finally, we summarize the applicable scenarios and future work of the scheme.
راعي المشروعThis work was supported by the Fundamental Research Funds for the Central University [grant 2020YJS021 ]; the National Natural Science Foundation of China (NSFC) [grant 61872029 ]; and the Beijing Municipal Natural Science Foundation [grant 4182048 ].
اللغةen
الناشرAcademic Press Inc.
الموضوعBig data
Multipath parallel transmission
Network bottleneck prediction
Quality of service
Vehicular networks
العنوانQoS provision for vehicle big data by parallel transmission based on heterogeneous network characteristics prediction
النوعArticle
الصفحات83-96
رقم المجلد163
dc.accessType Abstract Only


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