Green industrial internet of things through data compression
by Marcus V. Silva; Eduardo E. Mosca; Rafael L. Gomes
International Journal of Embedded Systems (IJES), Vol. 15, No. 6, 2022

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.

Online publication date: Thu, 30-Mar-2023

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Embedded Systems (IJES):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com