An Improved Clustering Method Vanet Routing and Communication
Abhilasha Chauhan1, Vishal Gupta2
1Abhilasha Chauhan*, School of Computer Science and Engineering, ICFAI University, Dehradun, India.
2Vishal Gupta, Professor, Department f ECE School of Computer Science and Engineering, ICFAI university, Dehradun, India.
Manuscript received on January 13, 2020. | Revised Manuscript received on January 20, 2020. | Manuscript published on February 10, 2020. | PP: 31-34 | Volume-9 Issue-4, February 2020. | Retrieval Number: C8125019320/2020©BEIESP | DOI: 10.35940/ijitee.C8125.029420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The rising popularity of network based technologies has witnessed growing interests in research of inter-vehicular communications. In this scenario, Vehicular Ad-hoc Network (VANET) has evolved as the largely admired network traffic routing and control system. The main idea of this work is to enhance quality of clustering approach implemented in VANET. To achieve this, authors proposed the addition of two new elements in the existing clustering architecture, namely, the number of cluster heads required in a specific simulation area and the selection of paramount candidate to be used as cluster head. Supervised learning technique is implemented in the employed methodology. The proposed architecture is evaluated in terms of Jitter and Packet Delivery Ratio (PDR). The simulation results demonstrated that the node variation with PDR shows relatively higher average PDR for polynomial kernel as compared to the average PDR for linear kernel.
Keywords: Vehicular Ad-hoc Network (VANET), Clustering, Polynomial Kernel, Linear Kernel, Cluster Head.
Scope of the Article: Clustering