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학술지 Soft Computing Techniques Aware Clustering-Based Routing Protocols in Vehicular Ad Hoc Networks: A Review
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저자
Manoj Sindhwani, Shippu Sachdeva, Krishan Arora, 윤태현, 유대승, Gyanendra Prasad Joshi, 조웅
발행일
202208
출처
Applied Sciences, v.12 no.15, pp.1-16
ISSN
2076-3417
출판사
MDPI
DOI
https://dx.doi.org/10.3390/app12157922
초록
The vehicular ad hoc network is an emerging area of technology that provides intelligent transportation systems with vast advantages and applications. Frequent disconnections between the vehicular nodes due to high-velocity vehicles impact network performance. This can be addressed by efficient clustering techniques. Several recent studies have attempted to develop optimal clustering algorithms to improve network performance metrics using soft computing techniques. Although sufficient work on soft computing techniques has been carried out, it seems less commonplace to find an analysis of various algorithms?? network parameters together. This paper provides a systematic analysis of the clustering-based routing protocols used in vehicular networks that are aware of soft computing techniques. The categorization is performed according to various soft computing techniques: particle swarm optimization, k-means, neural networks, artificial bee colony, genetic algorithm, firefly algorithm, and fuzzy logic. A comparative study of soft computing strategies is also provided in the survey with a focus on their objectives, along with their strengths and limitations. This survey makes it easier for researchers to pick the required soft computing technique used in vehicular networks in order to improve metrics such as packet delivery ratio, end-to-end delay, throughput, cluster lifetime, and message overhead.
KSP 제안 키워드
Artificial bee colony, Clustering Technique, Clustering algorithm, Clustering-based routing, End to End(E2E), End-To-end delay, Genetic Algorithm, High-velocity, Intelligent Transport Systems(ITS), Message overhead, Network Parameters
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