Integrating NFV and ICN for advanced driver assistance systems

Jianan Li, Jun Wu, Guangquan Xu, Jianhua Li, Xi Zheng, Alireza Jolfaei

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Advanced driver-assistance systems (ADASs) have been proposed as an alternative to driverless vehicles to provide support for automotive vehicle decisions. As a significant driving force for ADASs, the augmented reality (AR) provides comprehensive location-based content services for in-vehicle consumers. With the increase in request for information sharing, the current standalone mode of ADASs needs a shift to the multiuser sharing mode. In this article, to address the high mobility and real time requirements of ADASs in 5G environments, and also to address the resource orchestration and service management of big data in intelligent transportation systems, we integrate the information-centric network (ICN) and the network function virtualization (NFV) with ADASs to support an efficient AR-assisted content sharing and distribution. This integration eliminates the imbalance between the content requests and the resource limitation by splitting the virtual resources and providing an on-demand network and resource slicing in ADASs. We propose an incentive trading model for assistance content caching services and also propose a novel mechanism for optimal content cache allocation. Our extensive evaluation confirms that our proposed mechanism outperforms the past literature in terms of the cache hit ratio and latency.

Original languageEnglish
Pages (from-to)5861-5873
Number of pages13
JournalIEEE Internet of Things Journal
Volume7
Issue number7
Early online date18 Sep 2019
DOIs
Publication statusPublished - Jul 2020

Keywords

  • Augmented reality (AR)
  • driver assistance
  • information-centric network (ICN)
  • Internet of Vehicles (IoV)
  • network function virtualization (NFV)

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