Semantic Scholar Open Access 2023 43 sitasi

IMFOCA-IOV: Intelligent Moth Flame Optimization based Clustering Algorithm for Internet of Vehicle

Preeti Rani Rohit Sharma

Abstrak

Intelligent transportation systems (ITS) are receiving much attention today because of their significant effect on transportation safety, efficiency, and convenience. The Vehicle ad hoc networks (VANETs) in the ITS network are enhanced through the Internet of Vehicles (IOV), a continuation of the Internet of Things (IoT). In the IOV paradigm, the network's topology is extremely dynamic, and data is transmitted using 5G cellular communication. This work proposes an intelligent moth flame optimization-based clustering algorithm (IMFOCA) for the IOVs (IMFOCA-IOV). The IMFOCA-IOV algorithm provides maximum coverage for the IOV node with minimum cluster heads (CHs) required for routing. Simulation results are delivered to confirm that the IMFOCA-IOV algorithm can decrease the power consumption of IOV. The proposed IMFOCA-IOV algorithm performed better than CACONET, GWOCNET CLPSO, and MOPSO algorithms regarding the number of clusters and transmission range.

Topik & Kata Kunci

Computer Science

Penulis (2)

Preeti Rani

Rohit Sharma

Format Sitasi

APA MLA BibTeX

Rani, P., Sharma, R. (2023). IMFOCA-IOV: Intelligent Moth Flame Optimization based Clustering Algorithm for Internet of Vehicle. https://doi.org/10.1109/ICCCNT56998.2023.10307646

Akses Cepat

PDF tidak tersedia langsung

Cek di sumber asli →

Lihat di Sumber doi.org/10.1109/ICCCNT56998.2023.10307646

Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Total Sitasi: 43×
Sumber Database: Semantic Scholar
DOI: 10.1109/ICCCNT56998.2023.10307646
Akses: Open Access ✓