Title: Deep learning-based decision-making system for cooperative routing in wireless multimedia sensor network

Authors: M. Nagalingayya; Basavaraj S. Mathpati

Addresses: Department of Computer Science and Engineering, Sharnbasva University Kalaburgi, Vidya Nagar, Gulbarga, Karnataka, India ' Department of Computer Science and Engineering, Sharnbasva University Kalaburgi, Vidya Nagar, Gulbarga, Karnataka, India

Abstract: This research aims to present a deep belief network (DBN) based a technique for choosing the most suitable cooperative nodes. Additionally, constraints such as: 1) tri-level energy consumption of nodes (text at level 1 has a lower energy level than information; at level 2, which has a medium energy level for text, image and multimedia data; level 3: higher energy levels for high-definition pictures); 2) reliability; 3) delay are examined while sending multimedia data across the network. Making the right decision, a novel hybrid dragon integrated firefly (DIFF) schemes that integrate the ideas of firefly optimisation (FF) and dragonfly optimisation (DA) method is intended to adjust the optimal weight of DBN. The chosen scheme's efficiency is then compared to other traditional methods in terms of alive nodes, delay, residual energy, network lifespan and analysis method.

Keywords: routing protocol; optimisation; deep belief network; DBN; multimedia system; reliability.

DOI: 10.1504/IJNVO.2024.138491

International Journal of Networking and Virtual Organisations, 2024 Vol.30 No.3, pp.257 - 281

Received: 19 May 2022
Accepted: 16 Apr 2023
Published online: 07 May 2024 *

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