Abstract
The Internet of Vehicles (IoV) is an Intelligent Transportation System, which in its turn is an application of the Internet of Things. The IoV is a network of connected vehicles that sends/receives messages. However, the moving nature of the vehicles in IoV networks raises a dynamic topology issue. Therefore, establishing effective and dependable communication pathways among vehicular nodes, contingent upon traffic density conditions, presents a growing challenge. As a result, the main contribution of this paper is to propose an efficient network optimization system involving a cluster-based network routing optimizer. The proposed method is a metaheuristic algorithm adapted as a clustering algorithm. For this purpose, the JAYA Algorithm (JAYA) was utilized and integrated with two clustering concepts extracted from K-means Clustering and Automatic Clustering, resulting in proposing JAYA Clustering Algorithm for IoV (JAYACIoV). Subsequently, the performance of the proposed algorithm was investigated utilizing 176 network testing scenarios, and extensive comparative evaluations were conducted against five algorithms from the literature. The results confirmed the superiority of the proposed system with a percentage of 64.82%, where the algorithms were ranked according to the percentage achievement of best results.
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Abbreviations
- ACO:
-
Ant colony optimizer
- Acc:
-
The maximum driving acceleration
- CLPSO:
-
Comprehensive learning particle swarm optimizer
- CH:
-
Cluster head
- CM:
-
Cluster member
- CACONET:
-
ACO-based clustering algorithm for VANETs
- C-DRIVE:
-
Clustering based on direction in vehicular environment
- DA-TRLD:
-
Dynamic aware transmission range on local traffic density
- dim:
-
The dimensionality of the solution
- GA:
-
Genetic algorithm
- GA-ACO:
-
Integration between GA and ACO algorithms
- GWOCNET:
-
Grey Wolf Optimization-Based Clustering Algorithm for vehicular ad-hoc networks
- GS:
-
The size of grid
- GOA:
-
The grasshopper optimization algorithm
- IoV:
-
Internet of Vehicles
- IoV-NRP:
-
IoV network routing problem
- IoT:
-
Internet of Things
- ITS:
-
Intelligent Transportation System
- JAYA:
-
JAYA algorithm
- JAYACIoV:
-
JAYA Clustering Algorithm for IoV
- NoL:
-
Number of lanes
- LW:
-
Lane width
- LB:
-
Lower bound
- MOPSO:
-
Multiobjective particle swarm optimizer
- MFCA-IOV:
-
Moth Flame Clustering Algorithm for Internet of Vehicles
- MA-DTR:
-
Mobility Aware Dynamic Transmission Range algorithm
- MaxItr:
-
The maximum number of iterations
- MNoC:
-
The maximum number of clusters
- MCDRIVE:
-
Modified clustering based on direction in vehicular environment
- NoC:
-
Number of clusters
- NoV:
-
Number of distributed vehicles
- NoCH:
-
The total number of cluster heads in the network
- PA-JAYA:
-
Hybridization of JAYA algorithm with pigeon optimizer
- PSO:
-
Particle swarm optimizer
- PopSize:
-
The size of the population
- RSU:
-
Roadside unit
- S-JAYA:
-
Modified solution method of JAYA
- SP:
-
Vehicles allowable speed range
- TR:
-
Transmission range
- UB:
-
Upper bound
- VANETs:
-
Vehicular ad-hoc NETworks
- VWCA:
-
VANETs weighted clustering algorithm
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Dalbah, L.M., Al-Betar, M.A. & Awadallah, M.A. Jaya clustering-based algorithm for multiobjective IoV network routing optimization. Soft Comput 28, 5639–5665 (2024). https://doi.org/10.1007/s00500-023-09350-y
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DOI: https://doi.org/10.1007/s00500-023-09350-y