Robust MPR: A Novel Algorithm for Secure and Efficient Data Transmission in VANET

Usha, M.; Ramakrishnan, B.

doi:10.1007/s11277-019-06732-0

Cited by 14 publications

(8 citation statements)

References 23 publications

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“…OpenStreetMap mobility generator is used in this simulation. [50][51][52][53][54][55] Evaluation parameters such as the delivery rate of warning message, mean processing rate of request verification, rate of awareness, end-to-end delay, channel utilization, rate of localization and percentage of localization error are determined for different vehicle densities, number of NLOS and reference nodes and elapsed time for quantifying the potential of the proposed scheme as a significant NLOS positioning scheme as suggested in previous studies. [23][24][25]45,46 Enhanced weight-based clustering algorithms are used for pointing the region in the network.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

A Hybrid Crow Search and Gray Wolf Optimization Algorithm‐based Reliable Non‐Line‐of‐Sight Node Positioning Scheme for Vehicular Ad hoc Networks

Malar¹,

Priya²,

Janakiraman³

2020

Int J Communication

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Summary Vehicular Ad hoc NETwork (VANET) facilitates ubiquitous connectivity for establishing Vehicle‐to‐Vehicle (V2V) communication and supporting Intelligent Transportation Systems (ITSs). This vehicle communication requires complete coverage within the target range for ensuring reliable message dissemination. High density of vehicles in the intersections introduces challenges due to obstacles such as buildings, foliage, and other moving vehicles, preventing exchange of information about location and message update between vehicles. Non‐Line‐of‐Sight (NLOS) nodes also introduce broadcasting storm problem leading to congestion that prevents emergency messages from reaching the target vehicular nodes. Integration of meta‐heuristic Crow Search Algorithm (CSA) and Gray Wolf Optimization Algorithm (GWOA) minimizes the objective function of NLOS localization problem without the solution being trapped into local optima. In this paper, a Hybrid Crow Search and GWOA‐based NLOS Positioning Scheme (HCSGWOA‐NLOS‐PS) is proposed to handle the issue of broadcast storm and facilitate reliability in emergency message delivery. The proposed HCSGWOA‐NLOS‐PS utilizes the benefits of Time of Arrival (ToA) and geographical information‐based cooperative localization agent for attaining efficient NLOS node positioning in the network. It uses the benefits of CSA and GWOA for positioning the NLOS nodes based on the intelligence derived from the crows' conduit and the social attacking behavior of gray wolves that are ideal for balancing the tradeoff between exploration and exploitation. The simulation results of the proposed HCSGWOA‐NLOS‐PS confirm a mean emergency message delivery of 11.82%, neighborhood awareness of 12.38% with reduced localization error rate of 2.36% and minimized delay of 8.64% when compared to the baseline approaches.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

A Hybrid Crow Search and Gray Wolf Optimization Algorithm‐based Reliable Non‐Line‐of‐Sight Node Positioning Scheme for Vehicular Ad hoc Networks

Malar¹,

Priya²,

Janakiraman³

2020

Int J Communication

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“…The RSUs and OBUs direct all DSRC connected vehicles to provide on-demand information about the ongoing network traffic such as speed, position, acceleration, braking status, etc. of the neighboring vehicles [109][110][111][112]. Centralized approaches are easier to implement because they incur less overhead in routing connectivity.…”

Section: Topology-based Congestion Controlmentioning

confidence: 99%

“…If any of the RSUs are overloaded with more messages, the congestion control center in CLB applies a load balancing technique to redistribute the loads to nearby RSUs to minimize the congestion and packet loss. This results in higher end-to-end delay and overhead at high vehicle densities compared to robust congestion control [67,111] and dynamic bandwidth sharing [113] techniques. v) MOTabu: MOTabu is one of the most commonly used dynamic and topology-based decentralized congestion control techniques in VANETs.…”

Section: Topology-based Congestion Controlmentioning

confidence: 99%

“…Centralized approaches are easier to implement because they incur less overhead in routing connectivity. Common examples of centralized approaches for congestion control include robust congestion control scheme [67,111], dynamic sharing of bandwidth approach [113], dynamic congestion control approach [100], and CLB approach [101].…”

Section: Topology-based Congestion Controlmentioning

confidence: 99%

“…In this approach, there is a set of local controllers distributed in the entire network and each local controller can extract only limited information of beacon message such as speed, concentration, and travel time MOTabu [47,112], Improvised AODV [114], LBV_AODV [115], and CABS [97] are examples of decentralized approaches for congestion control that have been proposed for VANETs. i) Robust congestion control: Robust congestion control scheme is one of the topology-based centralized congestion control approaches that minimizes congestion in the VANETs environment [67,111]. The congestion detection center detects congestion in the network based on the priority level and the number of hops the messages have traveled with using metrics such as average message waiting time, collision rate, and message reception rate.…”

Section: Topology-based Congestion Controlmentioning

confidence: 99%

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A survey on congestion detection and control in connected vehicles

2020

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The dynamic nature of vehicular ad hoc network (VANET) induced by frequent topology changes and node mobility, imposes critical challenges for vehicular communications. Aggravated by the high volume of information dissemination among vehicles over limited bandwidth, the topological dynamics of VANET causes congestion in the communication channel, which is the primary cause of problems such as message drop, delay, and degraded quality of service. To mitigate these problems, congestion detection, and control techniques are needed to be incorporated in a vehicular network. Congestion control approaches can be either open-loop or closed loop based on pre-congestion or post congestion strategies. We present a general architecture of vehicular communication in urban and highway environment as well as a state-of-the-art survey of recent congestion detection and control techniques. We also identify the drawbacks of existing approaches and classify them according to different hierarchical schemes. Through an extensive literature review, we recommend solution approaches and future directions for handling congestion in vehicular communications.

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The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

Dong‐liang

Bei

Wang

2023

Int J Communication

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Summary Over the last decade, the Internet of Things (IoT) has become ever more popular, as is evident from its role in changing the human lifestyle and conferring remarkable privileges for them. It has a significant presence in various crucial areas, including smart cities, smart factories, manufacturing, transportation, and healthcare. Massive amounts of data generated by IoT devices have the potential to endanger the lifetime of nodes in IoT‐based networks due to increased communication power consumption. It has become crucial to propose solutions for network‐based issues, such as quality of service, security, network heterogeneity, congestion avoidance, reliable routing, and energy conservation. To address the mentioned problems, routing protocols play a critical role in data transmission among heterogeneous items. In such environments, routing refers to constructing routes between mobile nodes. Since identifying optimal routes among IoT nodes and establishing an effective routing protocol in an IoT network are an NP‐hard issue, employing metaheuristic algorithms may be a viable solution to overcome this problem. Various IoT routing protocols based on metaheuristic algorithms have been presented in recent years, but there is still a lack of systematic study for reviewing the existing works. The current study emphasizes the impact of metaheuristic algorithms in the IoT routing problem, discusses the optimization models, presents a comprehensive comparison of protocols based on critical parameters, and eventually suggests some hints for future studies.

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Robust MPR: A Novel Algorithm for Secure and Efficient Data Transmission in VANET

Cited by 14 publications

References 23 publications

A Hybrid Crow Search and Gray Wolf Optimization Algorithm‐based Reliable Non‐Line‐of‐Sight Node Positioning Scheme for Vehicular Ad hoc Networks

A Hybrid Crow Search and Gray Wolf Optimization Algorithm‐based Reliable Non‐Line‐of‐Sight Node Positioning Scheme for Vehicular Ad hoc Networks

A survey on congestion detection and control in connected vehicles

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

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