eprintid: 10058858
rev_number: 26
eprint_status: archive
userid: 608
dir: disk0/10/05/88/58
datestamp: 2018-10-24 08:04:42
lastmod: 2021-12-06 00:17:26
status_changed: 2018-10-24 08:04:42
type: proceedings_section
metadata_visibility: show
creators_name: Fathy, Y
creators_name: Barnaghi, P
creators_name: Tafazolli, R
title: An adaptive method for data reduction in the Internet of Things
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
keywords: Temperature sensors, Wireless sensor networks, Data communication, Energy consumption, Sensor phenomena and characterization, Predictive models
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: Enormous amounts of dynamic observation and measurement data are collected from sensors in Wireless Sensor Networks (WSNs) for the Internet of Things (IoT) applications such as environmental monitoring. However, continuous transmission of the sensed data requires high energy consumption. Data transmission between sensor nodes and cluster heads (sink nodes) consumes much higher energy than data sensing in WSNs. One way of reducing such energy consumption is to minimise the number of data transmissions. In this paper, we propose an Adaptive Method for Data Reduction (AM-DR). Our method is based on a convex combination of two decoupled Least-Mean-Square (LMS) windowed filters with differing sizes for estimating the next measured values both at the source and the sink node such that sensor nodes have to transmit only their immediate sensed values that deviate significantly (with a pre-defined threshold) from the predicted values. The conducted experiments on a real-world data show that our approach has been able to achieve up to 95% communication reduction while retaining a high accuracy (i.e. predicted values have a deviation of ±0.5 from real data values).
date: 2018-05-07
date_type: published
publisher: IEEE
official_url: https://doi.org/10.1109/WF-IoT.2018.8355187
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1578641
doi: 10.1109/WF-IoT.2018.8355187
isbn_13: 9781467399449
lyricists_name: Fathy, Yasmin
lyricists_id: YABBA16
actors_name: Fathy Abbas, Yasmin Abbas
actors_id: YABBA16
actors_role: owner
full_text_status: public
series: World Forum on Internet of Things
publication: IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings
volume: 4
pagerange: 729-735
event_title: 2018 IEEE 4th World Forum on Internet of Things (WF-IoT), 5-8 February 2018, Singapore
book_title: 2018 IEEE 4th World Forum on Internet of Things (WF-IoT)
citation:        Fathy, Y;    Barnaghi, P;    Tafazolli, R;      (2018)    An adaptive method for data reduction in the Internet of Things.                     In:  2018 IEEE 4th World Forum on Internet of Things (WF-IoT).  (pp. pp. 729-735).  IEEE       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10058858/1/WFIoT18_bare_conf.pdf