Virtual Vertex Routing (VVR) for Course-Based Vehicular Ad Hoc Networks

Lee, Ho-Jin; Lee, Youndo; Kwon, Taekyoung; Choi, Yanghee

doi:10.1109/wcnc.2007.803

Cited by 15 publications

(7 citation statements)

References 15 publications

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“…Apart from the above macroscopic models which adopted static data and traffic statistics, some other studies focused on applying the real-time control information exchanged with neighboring vehicles to estimate network connectivity or delivery delay in the street. In the landmark overlays for urban vehicular routing environments (LOURE) [27] and the virtual vertex routing (VVR) [28], similarly, a node obtains the number of its current neighbors by received beacon messages and adds this new information into its next beacon to broadcast. Thus, all vehicle nodes including that located at the intersection can collect the density and topology information in the street to calculate the network connectivity for routing selection in real time.…”

Section: Related Workmentioning

confidence: 99%

MMIR: a microscopic mechanism for street selection based on intersection records in urban VANET routing

Cai

Liang

Sun

2019

J Wireless Com Network

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In urban vehicular ad hoc networks (VANETs), the intersection-based routing scheme has represented its greater applicability and better efficiency to adapt to high and constrained mobility. How to make an accurate decision for street selection is a challenging issue due to the rapid topology changes in VANETs. In this paper, we propose a microscopic mechanism based on intersection records (MMIR) in which the intersection vehicle nodes maintain and update a records table with every passing vehicle's individual information. By analyzing and processing these entries, we evaluate these vehicles' current positions so as to compute the connectivity probability or estimated delivery delay for all candidate streets to support street selection. In contrast to the statistical and macroscopic information for the common condition, we firstly make use of the individual and microscopic data to enhance the accuracy of estimated results. Furthermore, according to the quantity and the running interval, we classify vehicles into two categories: individual and queue vehicles, in order to effectively decrease the complexity of position estimation. Lastly, since there are no dedicated control packets generated in MMIR, the network overhead is low. The simulation results show that the proposed MMIR outperforms existing approaches of street selection in terms of the accuracy of computed connectivity probability and estimated delay.

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Section: Related Workmentioning

confidence: 99%

MMIR: a microscopic mechanism for street selection based on intersection records in urban VANET routing

Cai

Liang

Sun

2019

J Wireless Com Network

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“…The signals of traffic lights on the intersection and traffic patterns are used together to determine how packets should be forwarded. STAR achieves shorter average delay, higher delivery ratio and higher TCP throughput for urban VANET communications than Virtual Vertex Routing [36], Greedy Traffic Aware Routing [37] and Green-Light-First-based [35] protocols. 4) Path-Based Routing: Vehicle-Assisted Data Delivery (VADD) protocols adopting a carry and forward mechanism are proposed in [38].…”

Section: A Transmission Strategy 1) Unicast Routing Protocolsmentioning

confidence: 99%

Routing in Internet of Vehicles: A Review

Cheng

Zhou

et al. 2015

IEEE Trans. Intell. Transport. Syst.

370

137

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This work aims to provide a review of the routing protocols in the Internet of Vehicles (IoV) from routing algorithms to their evaluation approaches. We provide five different taxonomies of routing protocols. First, we classify them based on their transmission strategy into three categories: unicast, geocast, and broadcast ones. Second, we classify them into four categories based on information required to perform routing: topology-, position-, map-, and path-based ones. Third, we identify them in delaysensitive and delay-tolerant ones. Fourth, we discuss them according to their applicability in different dimensions, i.e., 1-D, 2-D, and 3-D. Finally, we discuss their target networks, i.e., homogeneous and heterogeneous ones. As the evaluation is also a vital part in IoV routing protocol studies, we examine the evaluation approaches, i.e., simulation and real-world experiments. IoV includes not only the traditional vehicular ad hoc networks, which usually involve a small-scale and homogeneous network, but also a much larger scale and heterogeneous one. The composition of classical routing protocols and latest heterogeneous network approaches is a promising topic in the future. This work should motivate IoV researchers, practitioners, and new comers to develop IoV routing protocols and technologies.

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“…The delivery ratio of GPSR is worst among three routing protocols. This is because GPSR suffers from frequent routing holes at the node placement only on courses [11]. The delivery ratio of AODV decreases as the maximum speed increases.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…In VANETs, nodes are placed only on roads. In this situation, GPSR frequently falls into a routing hole, where no neighbor nodes are closer to the destination than the node itself [11]. The frequent occurrence of routing holes will degrade the routing performance severely.…”

Section: Introductionmentioning

confidence: 99%

Macro-Level and Micro-Level Routing (MMR) for Urban Vehicular Ad Hoc Networks

Lee

Choi

et al. 2007

IEEE GLOBECOM 2007-2007 IEEE Global Telecommunications Conference

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Abstract-Finding a reliable and efficient routing path in vehicular ad hoc networks (VANETs) is a challenging issue due to high mobility of vehicles and frequent link breakage. Motivated by this, we propose a robust and efficient routing protocol, called MMR. The contribution of this paper is two-fold: two-level routing and a new routing metric. A routing process of MMR consists of the macro level and the micro level. MMR forwards a packet to an approximate location of the destination at the macro level and then forwards a packet to the exact location of the destination at the micro level. This two-level routing reduces the protocol overhead and improves scalability in terms of the number of nodes. MMR also introduces a new routing metric that reduces the protocol overhead and path breakage by considering velocities of vehicles. Through simulations, we show that MMR improves the routing performance by about 30∼40% in highly mobile environments, compared to the existing ad hoc routing protocols such as AODV and GPSR

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Virtual Vertex Routing (VVR) for Course-Based Vehicular Ad Hoc Networks

Cited by 15 publications

References 15 publications

MMIR: a microscopic mechanism for street selection based on intersection records in urban VANET routing

MMIR: a microscopic mechanism for street selection based on intersection records in urban VANET routing

Routing in Internet of Vehicles: A Review

Macro-Level and Micro-Level Routing (MMR) for Urban Vehicular Ad Hoc Networks

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