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Energy-efficient cooperative routing scheme with recurrent neural network based decision making system for wireless multimedia sensor networks

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Abstract

“Wireless multimedia sensor networks (WMSNs)” are deployed in wider range of applications including video surveillance and area monitoring. However, due to the error-prone unreliable medium and application-based quality of service (QoS) requirements, routing in WMSNs becomes a serious issue. Thereby, this work intends to find the maximum energy cooperative route in WMSNs. Accordingly, Recurrent Neural Network (RNN) oriented decision making system is introduced for selecting the appropriate cooperative nodes with the knowledge of: (i) Tri-level energy utilization of nodes (ii) Reliability (iii) Delay to encounter the multimedia services in the network for transmitting the multimedia information. To make the precise decision on this, this paper intends to enhance the system model of RNN via optimizing the weights. For this optimization, a new Sea lion Adapted Grey Wolf Optimization (SA-GWA) is introduced, which is the hybridization of both Sea lion Optimization (SLnO) and Grey Wolf Optimizer (GWO). Finally, the superiority of the proposed model is validated over existing models in terms of reliability, residual energy and delay analysis.

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Abbreviations

ANN:

Artificial Neural Network

RNN:

Recurrent Neural Network

NN:

Neural Network

CH:

Cluster Head

CRS:

Cooperative Routing Scheme

CN:

Cooperative Node

DL:

Deep Learning

EDACR:

Energy-Efficient Distributed Adaptive Cooperative Routing

EE:

Energy Efficiency

EA-CRP:

Energy-Aware and Layering-Based Clustering and Routing Protocol

FC-RNN:

Fully Connected RNN

GWO:

Grey Wolf Optimizer

HD:

High Definition

MPR:

Multilayer Perceptron Regression

PSO:

Particle Swarm Optimization

QoS:

Quality of Service

RNN:

Recurrent Neural Network

SA-GWA:

Sea Lion Adapted Grey Wolf Optimization

SNR:

Signal To Noise Ratio

SINR:

Signal-to-Interference-Plus-Noise Ratio

SBCs:

Single Board Computers

SNs:

Sensor Nodes

SLnO:

Sea Lion Optimization

TCEM:

Topology Control and Sleeping Method

WMSNs:

Wireless Multimedia Sensor Networks

WSN:

Wireless Sensor Network

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Sharnbasva University Kalaburgi, Vidya Nagar, Gulbarga, Karnataka, 585105, India

    M Nagalingayya & Basavaraj S Mathpati

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  1. M Nagalingayya
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  2. Basavaraj S Mathpati
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Correspondence to M Nagalingayya.

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Nagalingayya, M., Mathpati, B.S. Energy-efficient cooperative routing scheme with recurrent neural network based decision making system for wireless multimedia sensor networks. Multimed Tools Appl 81, 39785–39801 (2022). https://doi.org/10.1007/s11042-022-12938-5

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  • DOI: https://doi.org/10.1007/s11042-022-12938-5

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