A Novel Intelligent Cluster-Head (ICH) to Mitigate the Handover Problem of Clustering in VANETs

Abbas, Ali; Habelalmateen, Mohammed I.; Audah, Lukman; Alduais, Nayef Abdulwahab Mohammed

doi:10.14569/ijacsa.2019.0100627

Cited by 47 publications

(12 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, DMA showed an average reduction percentage of 59.42% less than that of W-DMA. According to [30], an increase in N.O.V results in an increase in the number of uplink connections. Figure 4 shows the simulation results for 200 vehicles at an intersection.…”

Section: Results and Analysismentioning

confidence: 99%

Dynamic multiagent method to avoid duplicated information at intersections in VANETs

et al. 2020

Self Cite

View full text Add to dashboard Cite

Vehicular ad hoc networks (VANETs) allow vehicles to contact one another to provide safety and comfort applications. However, mobility is a great challenge in VANETs. High vehicle speed causes topological changes that result in unstable networks. Therefore, most previous studies focused on using clustering techniques in roads to reduce the effect of vehicle mobility and enhance network stability. Vehicles stop moving at intersections, and their mobility does not impact clustering. However, none of previous studies discussed the impact of vehicle stopping at intersections on base stations (BSs). Vehicles that have stopped moving at intersections continue to send the same information to BSs, which causes duplicated information. Hence, this study proposes a new method named dynamic multiagent (DMA) to filter cluster information and prevent duplicated information from being sent to BSs at intersections. The performance of the proposed method was evaluated through simulations during the use of DMA and without-DMA (W-DMA) methods based on real data collected from 10 intersections in Batu Pahat City, Johor, Malaysia. Overall, the proposed DMA method results in a considerable reduction in duplicated information at intersections, with an average percentage of 81% from the W-DMA method.

show abstract

Section: Results and Analysismentioning

confidence: 99%

Dynamic multiagent method to avoid duplicated information at intersections in VANETs

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…In Abbas et al, 70 the authors introduced a novel Intelligent Cluster-Head (ICH) to mitigate the handover problem of clustering in VANETs. ICH approach introduces a new recover mechanism, which is a controller on two clusters that are used to change uplink between clusters to solve the handover problem in the overlapping area.…”

Section: -Hop Clustering Algorithmsmentioning

confidence: 99%

“…This is considered the first algorithm based on multihop clustering for VANETs. The N-hop algorithm selects vehicles with low aggregate Algorithm Density Stability Latency Overhead Convergence MOSIC 66 Low Medium Medium Medium High SOCA 68 Medium Medium Low Low High RMAC 69 Low Medium Medium Medium High ICH 70 Medium Medium Low High High 71 Low Medium Low High Medium DMCNF 33 High Medium Medium Medium Low DHCV 72 Medium Medium Medium High Low VMaSC-LTE 73 High High Low High Low PMC 74 Medium High Low Medium Low 33 proposed a distributed multihop clustering algorithm for VANETs based on neighborhood follow (DMCNF); it selects CHs according to the neighborhood follow relationship among vehicles. In the DMCNF algorithm, a vehicle cannot directly identify the most suitable CH among its multihop neighbors; however, it knows the most stable and similar 1-hop neighbors, and therefore, they probably belong to the same cluster.…”

Section: K-hop Clustering Algorithmsmentioning

confidence: 99%

Survey on vehicular ad hoc networks clustering algorithms: Overview, taxonomy, challenges, and open research issues

Senouci

Harous

Aliouat

2020

Int J Communication

View full text Add to dashboard Cite

Summary Vehicular ad hoc networks (VANETs) have recently attracted considerable attention owing to their wide range of applications. However, there are several challenges, such as mobility, routing, scalability, quality of services, and security. Clustering is an important control mechanism in high‐mobility networks and has been verified to be a promising approach in VANETs as well, as it ensures a basic level of network performance. Accordingly, several clustering algorithms have been proposed for these networks, and different protocols typically focus on various performance metrics. In this study, we provide a thorough review of clustering algorithms in VANETs. First, we present background material regarding the clustering process. Secondly, we propose a new taxonomy that categorizes clustering algorithms in VANETs based on different design aspects and provides a description of the algorithms in each category. Thirdly, an analysis of the algorithms in each category is provided according to various comparison metrics. Fourthly, we highlight the main challenges for each category and discuss some open research issues. Finally, we provide a general comparison of different clustering algorithms according to selected key parameters. Thus, this study provides a more thorough understanding of VANET clustering algorithms and the research trends in this area.

show abstract

“…Thus, it is significant to develop an optimal reliable path for transmission in multiple routes [5], [6]. Currently, passive routing protocols like Ad hoc ondemand distance (AODV), dynamic source routing (DSR), and the destination-sequenced distance vector (DSDV), do not apply to vehicle-to-vehicle communication [7], [8]. To solve the routing problems in VANET, an enhanced genetic algorithm (EGA) and lion optimization routing protocol (LORP) are suggested.…”

Section: Introductionmentioning

confidence: 99%

A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network

Rashid

Hamdi

Audah

et al. 2023

IJ-AI

View full text Add to dashboard Cite

Vehicular ad-hoc network (VANET) is dynamic and it works on various noteworthy applications in intelligent transportation systems (ITS). In general, routing overhead is more in the VANETs due to their properties. Hence, need to handle this issue to improve the performance of the VANETs. Also due to its dynamic nature collision occurs. Up till now, we have had immense complexity in developing the multi-constrained network with high quality of forwarding (QoF). To solve the difficulties especially to control the congestion this paper introduces an enhanced genetic algorithmbased lion optimization for QoF-based routing protocol (EGA-LOQRP) in the VANET network. Lion optimization routing protocol (LORP) is an optimization-based routing protocol that can able to control the network with a huge number of vehicles. An enhanced genetic algorithm (EGA) is employed here to find the best possible path for data transmission which leads to meeting the QoF. This will result in low packet loss, delay, and energy consumption of the network. The exhaustive simulation tests demonstrate that the EGA-LOQRP routing protocol improves performance effectively in the face of congestion and QoS assaults compared to the previous routing protocols like Ad hoc on-demand distance vector (AODV), ant colony optimization-AODV (ACO-AODV) and traffic aware segmentAODV (TAS-AODV).

show abstract

A Novel Intelligent Cluster-Head (ICH) to Mitigate the Handover Problem of Clustering in VANETs

Cited by 47 publications

References 21 publications

Dynamic multiagent method to avoid duplicated information at intersections in VANETs

Dynamic multiagent method to avoid duplicated information at intersections in VANETs

Survey on vehicular ad hoc networks clustering algorithms: Overview, taxonomy, challenges, and open research issues

A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network

Contact Info

Product

Resources

About