Advanced multi-hop clustering (AMC) in vehicular ad-hoc network

被引:8
|
作者
Katiyar, Abhay [1 ,2 ]
Singh, Dinesh [1 ]
Yadav, Rama Shankar [1 ]
机构
[1] Motilal Nehru Natl Inst Technol Allahabad, Dept Comp Sci & Engn, Prayagraj 211004, Uttar Pradesh, India
[2] Jabalpur Engn Coll, Dept Comp Sci & Engn, Jabalpur, Madhya Pradesh, India
关键词
VANET; Clustering; Multi-hop clustering; Neighbourhood following strategy; Routing; ROUTING PROTOCOLS; ENERGY-EFFICIENT; MOBILE; ALGORITHM; COMMUNICATION; CHALLENGES; STABILITY; VANETS; SCHEME;
D O I
10.1007/s11276-021-02822-9
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Clustering improves network stability and scalability significantly by efficiently handling the fast topological change in VANET. Multi-hop clustering is introduced in VANET to handle some significant issues observed in the single-hop clustering, i.e., low cluster coverage, high number of clusters formed, and inefficient bandwidth utilization in routing decisions and internetwork data processing. Among many, cluster forming based on neighbourhood following strategy is the most recent and advanced way to form multi-hop clustering. By exploring the weaknesses and limitations of the existing neighbourhood following strategy, this paper introduced an advanced multi-hop clustering (AMC) algorithm. The proposed algorithm is empowered with an efficient cluster formation procedure that helps the vehicle to select and follow the most suitable target vehicle from one-hop neighbours. The suggested CH selection and cluster merging procedure contribute to strengthening stability. Further, we suggested the routing protocol of AMC to check the data transmission performance. Here, one vehicle appointed as a cross node at the road junction assigns the weight to the road segments by proper connectivity analysis. The lowest weight route signifies the best data forwarding path. The algorithm performance is tested in the realistic type scenario where vehicles' speed and arrival time are randomized. The detailed simulation result shows the strength of the AMC algorithm.
引用
收藏
页码:45 / 68
页数:24
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