Title: Improved fuzzy C means with deep learning-based MANET routing model for multimedia communication

Authors: Manjula A. Biradar; Sujata Mallapur

Addresses: Department of Computer Science and Engineering, Sharnbasava University, Sharan Nagar, Kalaburagi, Karnataka, 585105, India ' Faculty of Engineering and Technology (Exclusively for Women), Department of Artificial Intelligence and Machine Learning, Sharnbasava University, Sharan Nagar, Kalaburagi, Karnataka, 585105, India

Abstract: The rapid growth of wireless communication amazed the researchers to done multimedia communication via wireless networks. The significant rise of mobile ad-hoc networks (MANET) in wireless communication is widely researched by researchers for an efficient transmission of multimedia data. MANET works on non-infrastructure topology with high quality of service (QoS) for better user experience. Though, it suffers from limitations such as routing, limited bandwidth, dynamic mobile node nature, etc. That's why, this research paper is dedicated to introduce a MANET routing model for multimedia communication by providing reliable retransmission for better communication. An optimal cluster-based routing via improved fuzzy C-means (FCM) clustering takes place before it gets started nodal energy prediction is done by modified deep CNN model. And optimal cluster head selection is done via self-improved coati optimisation (SICO) under certain constraints. Finally, it is finished off with reliable retransmission to enhance the reliability of communication. Further, the efficiency of the proposed model is proved by various analysis.

Keywords: MANET routing; multimedia communication; FCM; fuzzy C-means; SICO; reliable retransmission.

DOI: 10.1504/IJNVO.2024.144082

International Journal of Networking and Virtual Organisations, 2024 Vol.31 No.4, pp.306 - 338

Received: 20 Dec 2023
Accepted: 21 Jun 2024
Published online: 24 Jan 2025 *

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