Improving bandwidth utilization by compressing small-payload traffic for vehicular networks
Jianan Sun,
Ping Dong,
Yajuan Qin,
Tao Zheng,
Xiaoyun Yan and
Yuyang Zhang
International Journal of Distributed Sensor Networks, 2019, vol. 15, issue 4, 1550147719843050
Abstract:
The low bandwidth utilization is a serious problem for mobile services over vehicular networks. This is mainly resulted from the high-rate transmission of packets carrying small payloads. Some solutions are proposed to forward packets by context identifier, instead of IP address, based on header compression and software-defined networking technology. However, these solutions cannot be deployed in vehicular networks successfully, due to the limitations on processing capacity and routing scalability. In this article, we propose a scalable end-to-end header compression scheme, which takes advantage of the locator/identifier separation concept and some characteristics of software-defined networking. We propose to utilize a forwarding identifier to indicate the compressor’s location, separating the header compression process from the packet forwarding process. In this way, context identifiers with an identical value are allowed to coexist in the same network, and flow table entries matching the compressed flows can be aggregated. Extensive simulations have been conducted and the results demonstrate that scalable end-to-end header compression experiences outstanding performances in bandwidth utilization and delay, showing its greater suitability for vehicular network transmission optimization.
Keywords: Vehicular networks; bandwidth utilization; header compression; software-defined networking; scalability (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1550147719843050 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:15:y:2019:i:4:p:1550147719843050
DOI: 10.1177/1550147719843050
Access Statistics for this article
More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().