Cache Agent Based Location Aided Routing Protocol Using Direction for Performance Enhancement in VANET

Gurumoorthi, E.; Ayyasamy, A.

doi:10.1007/s11277-019-06610-9

Cited by 14 publications

(7 citation statements)

References 24 publications

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“…The authors of [123] propose direction-based cache agent location-aided routing, which is a hybrid routing protocol. In that work, geocast and position-based routing are combined, which significantly improves the routing performance of VANETs.…”

Section: J Hybrid Protocolmentioning

confidence: 99%

A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches

Chatterjee¹,

Karmakar

Kaddoum

et al. 2022

IEEE Access

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Intelligent transportation systems (ITSs) have become increasingly popular because they support effective coordination in connected vehicles. ITSs present an integrated approach for exchanging relevant information in order to improve the safety, efficiency, and reliability of road transportation systems. A variant of mobile ad-hoc networks (MANETs) called vehicular ad-hoc networks (VANETs) are an integral component of ITSs. VANETs consist of interconnected vehicles with sensing abilities that exchange information related to traffic, positioning, weather, and emergency services. In general, vehicle-to-everything (V2X) refers to communications between any entity and a vehicle, where the entity may be a vehicle, a cloud-based network, a pedestrian, or equipment installed along a road. One of the crucial challenges in V2X is the reliable and timely circulation of information among vehicular nodes to allow drivers to make decisions that increase road safety. In this context, efficient V2X routing protocols play a key role in supporting reliability and safety, and enhancing the overall quality of service (QoS) in VANETs. However, VANETs have distinct characteristics, such as high vehicular node mobility, unsteady connectivity, rapid changes in network topology, and unbounded network size, that can significantly affect routing in the network. Various routing protocols for V2X communication exist in the open technical literature. In this survey, we categorize the routing mechanisms as non-learning-and learning-based approaches, and discuss existing V2X routing protocols and their contributions to and impacts on VANET performance. Here, the learning-based approach implies the use of machine learning algorithms. This survey also summarizes open challenges in designing effective V2X routing protocols and future research directions to consider when developing smart routing mechanisms for next-generation intelligent VANET technologies.INDEX TERMS VANET, V2X, routing protocol, non-learning-based routing, learning-based routing.

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Section: J Hybrid Protocolmentioning

confidence: 99%

A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches

Chatterjee¹,

Karmakar

Kaddoum

et al. 2022

IEEE Access

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“…The RWCP is framed by taking the direction of vehicles, position, velocity, number of nearby vehicles, lane ID, and the reputation of each node into consideration for stabilizing the VANET topology. Gurumoorthi et al 28 proposed a hybrid routing protocol called Directional‐Cache Agent‐based Location Aided Routing (D‐CALAR). D‐CALAR is a combination of position‐based and geocast routing.…”

Section: Related Workmentioning

confidence: 99%

An adaptive and secure traffic information forwarding mechanism in Internet of Vehicles

Fan

Duan

et al. 2020

Int J Communication

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SummaryTraffic information of disparate types in Internet of Vehicles (IoV) is the basis for supporting various IoV applications. Since traffic flows vary in real time, it is challenging to carry out efficient and reliable transfer of such information. Moreover, IoV is vulnerable to security threats due to its inherent properties such as dynamically changing topology and high‐speed motion of vehicles. Attacks, once launched successfully, would also disrupt message transmission between vehicles. We propose an adaptive traffic information forwarding mechanism, which divides traffic information in two categories, that is, early warning information and service information. The former is handled by selecting a relay node based on node connection stability evaluation, while the latter is handled by adopting an appropriate forwarding method according to the identified traffic flow density. Specifically, in a low‐density environment, we employ a broadcast method; while in a high‐density environment, we evaluate the cognitive interaction values of vehicle nodes and employ a cognitive interaction‐based method to select a relay node. Simulation results show that the proposed mechanism improves the forwarding efficiency of traffic information and yields satisfactory performance in mitigating black hole attacks.

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“…They have evaluated the performance of AODV routing protocol in terms of Delivery ratio, Packet loss and Router dropfor the above scenario. In paper [1] the performance of AODV, DSR and DSDV is evaluated for the highway scenario of China. Routing metrics such as: delivery of packet quotient, end to end delay and routing load has been measured.…”

Section: Related Workmentioning

confidence: 99%

“…Vehicular Ad-hoc network (VANET) is an extension of Mobile ad-hoc network (MANET) wherein vehicular nodes communicate with each other as opposed to mobile devices communicating with each other in MANETs. In VANETs vehicles communicate in either of the two modes: vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) [1]. These networks are characterized by high vehicular density and highly dynamic nature of vehicles wherein vehicles keep moving in and out of the network.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of LAR under Highway and City Scenarios

Saggu¹,

Agarwal

2019

IJMLNCE

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ehicular ad-hoc networks have gained immense popularity as a research domain as more and more vehicles interact with each other to communicate information. This paper is aimed at evaluating the performance of Location Aided routing protocol (LAR) for Vehicular Ad-hoc networks (VANETs) using NS2 and SUMO. This protocol is evaluated under highway and city scenarios obtained from Open Street Map (OSM) and Bologna Ringway dataset respectively. The performance metrics considered for these scenarios are throughput, packet delivery ratio (PDR), routing overhead. The above mentioned parameters are calculated by varying the simulation time and number of vehicles. The results obtained are graphically plotted and analyzed.

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Cache Agent Based Location Aided Routing Protocol Using Direction for Performance Enhancement in VANET

Cited by 14 publications

References 24 publications

A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches

A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches

An adaptive and secure traffic information forwarding mechanism in Internet of Vehicles

Performance Evaluation of LAR under Highway and City Scenarios

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