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 journalArticle

Abstract

Advanced Driver Assistance Systems (ADAS) have been proposed as an alternative to driverless vehicles to provide support for automotive vehicle decisions. As a significant driving force for ADAS, the Augmented Reality (AR) provides comprehensive location-based content services for in-vehicle consumers. With the increase in request for information sharing, the current stand-alone mode of ADAS needs a shift to the multi-user sharing mode. In this paper, to address the high mobility and real-time requirements of ADAS 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 ADAS 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 on-demand network and resource slicing in ADAS. 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
JournalIEEE Internet of Things Journal
Early online date18 Sep 2019
DOIs
Publication statusE-pub ahead of print - 18 Sep 2019

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