A multi-node energy prediction approach combined with optimum prediction interval for RF powered WSNs

Research output: Contribution to journalArticle

11 Downloads (Pure)

Abstract

Energy prediction plays a vital role in designing an efficient power management system for any environmentally powered Wireless Sensor Networks (WSNs). Most of the Moving Average (MA)-based energy prediction methods depend on past energy readings of the concerned node to predict its future energy availability. However, in case of RF powered WSNs the harvesting history of the main node along with neighbouring nodes can also be used to develop a more robust prediction technique. In this paper, we propose a Multi-Node energy prediction method for Radio Frequency Energy Harvesting (RF-EH) WSNs, which predicts the future energy availability by taking into account harvesting history of all nodes surrounding the main node. We analyse the effective distance for prediction and also develop a mathematical model to compute the optimum value of prediction interval, which has a major effect in prediction accuracy and system design, considering energy neutrality. Results show that Multi-Node prediction is less sensitive to prediction interval while inheriting the advantages of MA techniques. Also, nodes located at a larger distance were utilized less for prediction, and as the prediction interval increased, the utilization of more distant nodes decreased. Furthermore, we also establish a linear relation between the prediction interval and the energy threshold limit.
Original languageEnglish
Article number5551
Number of pages14
JournalSENSORS
Volume19
Issue number24
DOIs
Publication statusPublished - 16 Dec 2019

Fingerprint

Wireless sensor networks
intervals
sensors
predictions
Radio
Reading
Theoretical Models
History
energy
availability
Availability
histories
Energy harvesting
management systems
systems engineering
mathematical models
radio frequencies
Systems analysis
Mathematical models
thresholds

Keywords

  • Wireless sensor networks
  • Energy harvesting
  • Prediction
  • RF energy

Cite this

@article{556e26373cb54ca596f5e2b017c31ec7,
title = "A multi-node energy prediction approach combined with optimum prediction interval for RF powered WSNs",
abstract = "Energy prediction plays a vital role in designing an efficient power management system for any environmentally powered Wireless Sensor Networks (WSNs). Most of the Moving Average (MA)-based energy prediction methods depend on past energy readings of the concerned node to predict its future energy availability. However, in case of RF powered WSNs the harvesting history of the main node along with neighbouring nodes can also be used to develop a more robust prediction technique. In this paper, we propose a Multi-Node energy prediction method for Radio Frequency Energy Harvesting (RF-EH) WSNs, which predicts the future energy availability by taking into account harvesting history of all nodes surrounding the main node. We analyse the effective distance for prediction and also develop a mathematical model to compute the optimum value of prediction interval, which has a major effect in prediction accuracy and system design, considering energy neutrality. Results show that Multi-Node prediction is less sensitive to prediction interval while inheriting the advantages of MA techniques. Also, nodes located at a larger distance were utilized less for prediction, and as the prediction interval increased, the utilization of more distant nodes decreased. Furthermore, we also establish a linear relation between the prediction interval and the energy threshold limit.",
keywords = "Wireless sensor networks, Energy harvesting, Prediction, RF energy",
author = "Bikrant Koirala and Keshav Dahal and Paul Keir and Wenbing Chen",
year = "2019",
month = "12",
day = "16",
doi = "10.3390/s19245551",
language = "English",
volume = "19",
journal = "SENSORS",
issn = "1424-8220",
publisher = "Multidisciplinary Digital Publishing Institute",
number = "24",

}

A multi-node energy prediction approach combined with optimum prediction interval for RF powered WSNs. / Koirala, Bikrant; Dahal, Keshav; Keir, Paul; Chen, Wenbing.

In: SENSORS, Vol. 19, No. 24, 5551, 16.12.2019.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A multi-node energy prediction approach combined with optimum prediction interval for RF powered WSNs

AU - Koirala, Bikrant

AU - Dahal, Keshav

AU - Keir, Paul

AU - Chen, Wenbing

PY - 2019/12/16

Y1 - 2019/12/16

N2 - Energy prediction plays a vital role in designing an efficient power management system for any environmentally powered Wireless Sensor Networks (WSNs). Most of the Moving Average (MA)-based energy prediction methods depend on past energy readings of the concerned node to predict its future energy availability. However, in case of RF powered WSNs the harvesting history of the main node along with neighbouring nodes can also be used to develop a more robust prediction technique. In this paper, we propose a Multi-Node energy prediction method for Radio Frequency Energy Harvesting (RF-EH) WSNs, which predicts the future energy availability by taking into account harvesting history of all nodes surrounding the main node. We analyse the effective distance for prediction and also develop a mathematical model to compute the optimum value of prediction interval, which has a major effect in prediction accuracy and system design, considering energy neutrality. Results show that Multi-Node prediction is less sensitive to prediction interval while inheriting the advantages of MA techniques. Also, nodes located at a larger distance were utilized less for prediction, and as the prediction interval increased, the utilization of more distant nodes decreased. Furthermore, we also establish a linear relation between the prediction interval and the energy threshold limit.

AB - Energy prediction plays a vital role in designing an efficient power management system for any environmentally powered Wireless Sensor Networks (WSNs). Most of the Moving Average (MA)-based energy prediction methods depend on past energy readings of the concerned node to predict its future energy availability. However, in case of RF powered WSNs the harvesting history of the main node along with neighbouring nodes can also be used to develop a more robust prediction technique. In this paper, we propose a Multi-Node energy prediction method for Radio Frequency Energy Harvesting (RF-EH) WSNs, which predicts the future energy availability by taking into account harvesting history of all nodes surrounding the main node. We analyse the effective distance for prediction and also develop a mathematical model to compute the optimum value of prediction interval, which has a major effect in prediction accuracy and system design, considering energy neutrality. Results show that Multi-Node prediction is less sensitive to prediction interval while inheriting the advantages of MA techniques. Also, nodes located at a larger distance were utilized less for prediction, and as the prediction interval increased, the utilization of more distant nodes decreased. Furthermore, we also establish a linear relation between the prediction interval and the energy threshold limit.

KW - Wireless sensor networks

KW - Energy harvesting

KW - Prediction

KW - RF energy

U2 - 10.3390/s19245551

DO - 10.3390/s19245551

M3 - Article

VL - 19

JO - SENSORS

JF - SENSORS

SN - 1424-8220

IS - 24

M1 - 5551

ER -