An Optimized Proactive Caching Scheme Based on Mobility Prediction for Vehicular Networks

IEEE Commun. Surv. Tutorials

et al. 2020

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242

121

Information-Centric Networking (ICN) has been proposed as one of the future Internet architectures. It is poised to address the challenges faced by today's Internet that include, but not limited to, scalability, addressing, security, and privacy. Furthermore, it also aims at meeting the requirements for new emerging Internet applications. To realize ICN, Named Data Networking (NDN) is one of the recent implementations of ICN that provides a suitable communication approach due to its clean slate design and simple communication model. There are a plethora of applications realized through ICN in different domains where data is the focal point of communication. One such domain is Intelligent Transportation System (ITS) realized through Vehicular Ad hoc NETwork (VANET) where vehicles exchange information and content with each other and with the infrastructure. To date, excellent research results have been yielded in the VANET domain aiming at safe, reliable, and infotainment-rich driving experience. However, due to the dynamic topologies, host-centric model, and ephemeral nature of vehicular communication, various challenges are faced by VANET that hinder the realization of successful vehicular networks and adversely affect the data dissemination, content delivery, and user experiences. To fill these gaps, NDN has been extensively used as underlying communication paradigm for VANET. Inspired by the extensive research results in NDN-based VANET, in this paper, we provide a detailed and systematic review of NDN-driven VANET. More precisely, we investigate the role of NDN in VANET and discuss the feasibility of NDN architecture in VANET environment. Subsequently, we cover in detail, NDN-based naming, routing and forwarding, caching, mobility, and security mechanism for VANET. Furthermore, we discuss the existing standards, solutions, and simulation tools used in NDN-based VANET. Finally, we also identify open challenges and issues faced by NDN-driven VANET and highlight future research directions that should be addressed by the research community.

Section: Alternative Caching Schemesmentioning

confidence: 99%

“…In the following, we present an overview of the existing standards, solutions, and simulation tools. [78], [82], [88], [93], [97], [98], [103], [115], [116], [118], [120], [127], [129], [130], [132], [134], [139], [142], [143], [149], [150], [159]- [161], [163], [164], [181], [186] • Open source package.…”

Section: Standards Solutions and Simulation Toolsmentioning

confidence: 99%

Named Data Networking in Vehicular Ad Hoc Networks: State-of-the-Art and Challenges

IEEE Commun. Surv. Tutorials

et al. 2020

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242

121

“…e time and location decoupling concept in NDN enhances the data availability and improves the overall network performance [28][29][30]. Data producers are not required to be connected all time to satisfy consumer requests, where the network layer can fulfill different demands especially the hot ones, by retrieving the content from the most closer cache stores.…”

Section: In-network Cachingmentioning

confidence: 99%

Security and Privacy Issues in Vehicular Named Data Networks: An Overview

Mobile Information Systems

et al. 2018

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A tremendous amount of content and information are exchanging in a vehicular environment between vehicles, roadside units, and the Internet. This information aims to improve the driving experience and human safety. Due to the VANET’s properties and application characteristics, the security becomes an essential aspect and a more challenging task. On the contrary, named data networking has been proposed as a future Internet architecture that may improve the network performance, enhance content access and dissemination, and decrease the communication delay. NDN uses a clean design based on content names and Interest-Data exchange model. In this paper, we focus on the vehicular named data networking environment, targeting the security attacks and privacy issues. We present a state of the art of existing VANET attacks and how NDN can deal with them. We classified these attacks based on the NDN perspective. Furthermore, we define various challenges and issues faced by NDN-based VANET and highlight future research directions that should be addressed by the research community.

“…Hence, the network becomes aware on content delivery; and therefore, improve the content availability, reduce the overall network load, eliminate single point of failure, and decrease the network delay. The caching in NDN may involve two different aspects: cache placement strategy [7], and cache replacement policy [8]. The former deals with where to cache the content, the latter deals what which content to cache and which content to remove in case the cache store is full.…”

Section: Introductionmentioning

confidence: 99%

A QoS-Aware Cache Replacement Policy for Vehicular Named Data Networks

2019 IEEE Global Communications Conference (GLOBECOM)

et al. 2019

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Vehicular Named Data Network (VNDN) uses Named Data Network (NDN) as a communication enabler. The communication is achieved using the content name instead of the host address. NDN integrates content caching at the network level rather than the application level. Hence, the network becomes aware of content caching and delivering. The content caching is a fundamental element in VNDN communication. However, due to the limitations of the cache store, only the most used content should be cached while the less used should be evicted. Traditional caching replacement policies may not work efficiently in VNDN due to the large and diverse exchanged content. To solve this issue, we propose an efficient cache replacement policy that takes the quality of service into consideration. The idea consists of classifying the traffic into different classes, and split the cache store into a set of sub-cache stores according to the defined traffic classes with different storage capacities according to the network requirements. Each content is assigned a popularity-density value that balances the content popularity with its size. Content with the highest popularity-density value is cached while the lowest is evicted. Simulation results prove the efficiency of the proposed solution to enhance the overall network quality of service.