Title: Green industrial internet of things through data compression

Authors: Marcus V. Silva; Eduardo E. Mosca; Rafael L. Gomes

Addresses: State University of Ceará, Fortaleza-CE, Brazil ' State University of Ceará, Fortaleza-CE, Brazil ' State University of Ceará, Fortaleza-CE, Brazil

Abstract: Industrial internet of things (IIoT) plays an essential role in efficient and sustainable production in industries. Despite Wi-Fi (Standard IEEE 802.11) being considered a key technology for IIoT, it still generates higher energy consumption in IIoT devices, mainly due to the size of packets sent and the defined maximum transmission unit (MTU) for the network infrastructure. Thus, an existing problem is the need to reduce the size of transmitted packets and MTU, where data compression is a promising approach to deal with it. In order to deal with this situation, this article proposes two lightweight data compression methods to minimise the volume of data to be sent by IIoT devices: a customised binary Huffman-tree and a Lempel-Ziv-Welch algorithm with a flexible dictionary. Results from real experiments suggest that the proposed methods reduce energy consumption by 8% when compared to the existing solutions for IIoT.

Keywords: data volume minimisation; MTU reduction; industrial internet of things; IIoT.

DOI: 10.1504/IJES.2022.129802

International Journal of Embedded Systems, 2022 Vol.15 No.6, pp.457 - 466

Received: 19 Jan 2022
Received in revised form: 05 Aug 2022
Accepted: 30 Aug 2022
Published online: 30 Mar 2023 *

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