Energy-Efficient Communication Using Auto-Associative Polynomial Convolutional Neural Network in WSN

IF 1.7 4区 计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Kanjoor Vamanan Praveen, Joe Prathap Pathrose Mary, Nagarajan Ramshankar, Sundaram Murugesan
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引用次数: 0

Abstract

Several changes have been implemented over the years to provide better resource management and service delivery for artificial wireless sensor networks (WSNs) that rely on the Internet of Things (IoT). Here, 5G networks offer high data rates with ultra-low latency and robust reliability, which is essential for managing the substantial data volumes generated by IoT devices in 5G WSNs. IoT needs an optimal communication network to transmit data among different devices. The whole network is categorized as heterogeneous clusters in clustering. The cluster head (CH) selection achieves proficient data communication to the sink node through the chosen CH. In this manuscript, an energy-efficient communication using auto-associative polynomial convolutional neural network in 5G WSN (EEC-HAPCNN) is proposed for improved data transmission through the selected route. Initially, clustering is done by parallel adaptive canopy k-means clustering (PaC-k-M) algorithm. Then, Tasmanian devil optimization algorithm (TDOA) selects the CH required for facilitating the high capacity and low latency features of 5G. The data are given to sink node through the selected CH utilizing hierarchical auto-associative polynomial convolutional neural network (HAPCNN) for efficient routing in 5G wireless communication network. The proposed EEC-HAPCNN method is implemented in NS-3 (network simulator 3). The proposed approach is examined using performance metrics like throughput, energy consumption, network lifetime, and number of nodes alive. The proposed EEC-HAPCNN method provides 17.45%, 17.63%, and 18.43% lesser energy consumption and 17.64%, 17.64%, 18.54%, and 19.33% greater network life time compared with existing DBN-MRFO-5G-WSN, IDCNN-t-DSBO, DACP-WSN-ANN, EEO-IWSN-ML, and EECA-ML-WSN techniques.

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来源期刊
CiteScore
5.90
自引率
9.50%
发文量
323
审稿时长
7.9 months
期刊介绍: The International Journal of Communication Systems provides a forum for R&D, open to researchers from all types of institutions and organisations worldwide, aimed at the increasingly important area of communication technology. The Journal''s emphasis is particularly on the issues impacting behaviour at the system, service and management levels. Published twelve times a year, it provides coverage of advances that have a significant potential to impact the immense technical and commercial opportunities in the communications sector. The International Journal of Communication Systems strives to select a balance of contributions that promotes technical innovation allied to practical relevance across the range of system types and issues. The Journal addresses both public communication systems (Telecommunication, mobile, Internet, and Cable TV) and private systems (Intranets, enterprise networks, LANs, MANs, WANs). The following key areas and issues are regularly covered: -Transmission/Switching/Distribution technologies (ATM, SDH, TCP/IP, routers, DSL, cable modems, VoD, VoIP, WDM, etc.) -System control, network/service management -Network and Internet protocols and standards -Client-server, distributed and Web-based communication systems -Broadband and multimedia systems and applications, with a focus on increased service variety and interactivity -Trials of advanced systems and services; their implementation and evaluation -Novel concepts and improvements in technique; their theoretical basis and performance analysis using measurement/testing, modelling and simulation -Performance evaluation issues and methods.
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