期刊
TELECOMMUNICATION SYSTEMS
卷 78, 期 1, 页码 65-83出版社
SPRINGER
DOI: 10.1007/s11235-021-00801-1
关键词
Vehicular delay tolerant networks; Hierarchical routing; Reinforcement learning; Scalable message delivery
This paper introduces an innovative hierarchical VDTNs scheme, called HI-VDTCR, to address scalability and performance balance issues in vehicular network routing methods. HI-VDTCR demonstrates better performance compared to other well-known vehicular routing methods.
Vehicular delay tolerant networks (VDTNs) present an efficient platform for delivering delay tolerant contents in vehicular networks by utilizing vehicle to vehicle or vehicle to road side infrastructure communications. Routing protocols play an essential role in VDTNs environment to provide high routing performance. However, most of existing vehicular network routing methods suffer from scalability issues and cannot make a trade-off between different performance criteria. In this paper we introduce an innovative hierarchical VDTNs scheme, called Hierarchical and Intelligent Vehicular Delay Tolerant Content Routing (HI-VDTCR), to establish a scalable delivery routing mechanism and provide a balance between different performance criteria. HI-VDTCR consists of two layers. An upper layer is responsible for sending messages to the destination vicinities without imposing high overhead to the network and a lower layer is tasked with delivering messages to the destination node by introducing a Markov decision process model, as an efficient reinforcement learning algorithm, for forwarding messages to the destination rendezvous. The proposed hierarchical and intelligent design empowers HI-VDTCR to provide an acceptable scalability in terms of network operation area and number of vehicle nodes. Evaluation results confirm that HI-VDTCR method outperforms other well-known vehicular routing methods.
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