Value of Information Based Data Retrieval in UWSNs

Sensor nodes in underwater sensor networks may acquire data at a higher rate than their ability to communicate over underwater acoustic channels. Autonomous underwater vehicles may mitigate this mismatch by offloading high volumes of data from the sensor nodes and ferrying them to the sink. Such a m...

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Bibliographic Details
Main Authors: Fahad Ahmad Khan, Sehar Butt, Saad Ahmad Khan, Ladislau Bölöni, Damla Turgut
Format: Article
Language:English
Published: MDPI AG 2018-10-01
Series:Sensors
Subjects:
AUV
QoS
QoI
VoI
Online Access:http://www.mdpi.com/1424-8220/18/10/3414
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spelling doaj-cf1aab31b5ca464d8c7f0a315e1b31292020-11-24T21:27:50ZengMDPI AGSensors1424-82202018-10-011810341410.3390/s18103414s18103414Value of Information Based Data Retrieval in UWSNsFahad Ahmad Khan0Sehar Butt1Saad Ahmad Khan2Ladislau Bölöni3Damla Turgut4Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USADepartment of Electrical Engineering and Computer Science, University of Engineering & Technology Lahore, Punjab 54890, PakistanDepartment of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USADepartment of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USADepartment of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USASensor nodes in underwater sensor networks may acquire data at a higher rate than their ability to communicate over underwater acoustic channels. Autonomous underwater vehicles may mitigate this mismatch by offloading high volumes of data from the sensor nodes and ferrying them to the sink. Such a mode of data transfer results in high latency. Occasionally, these networks need to report high priority events such as catastrophes or intrusions. In such a scenario the expectation is to have a minimal end-to-end delay for event reporting. Considering this, underwater vehicles should schedule their visits to the sensor nodes in a manner that aids efficient reporting of high-priority events. We propose the use of the Value of Information metric in order to improve the reporting of events in an underwater sensor network. The proposed approach classifies the recorded data in terms of its value and priority. The classified data is transmitted using a combination of acoustic and optical channels. We perform experiments with a binary event model, i.e., we classify the events into high-priority and low-priority events. We explore a couple of different path planning strategies for the autonomous underwater vehicle. Our results show that scheduling visits to sensor nodes, based on algorithms that address the value of information, improves the timely reporting of high priority data and enables the accumulation of larger value of information.http://www.mdpi.com/1424-8220/18/10/3414under water sensor networkmobilitypath planningroutingquality of informationvalue of informationmobile sinkdata muleUWSNAUVQoSQoIVoI
collection DOAJ
language English
format Article
sources DOAJ
author Fahad Ahmad Khan
Sehar Butt
Saad Ahmad Khan
Ladislau Bölöni
Damla Turgut
spellingShingle Fahad Ahmad Khan
Sehar Butt
Saad Ahmad Khan
Ladislau Bölöni
Damla Turgut
Value of Information Based Data Retrieval in UWSNs
Sensors
under water sensor network
mobility
path planning
routing
quality of information
value of information
mobile sink
data mule
UWSN
AUV
QoS
QoI
VoI
author_facet Fahad Ahmad Khan
Sehar Butt
Saad Ahmad Khan
Ladislau Bölöni
Damla Turgut
author_sort Fahad Ahmad Khan
title Value of Information Based Data Retrieval in UWSNs
title_short Value of Information Based Data Retrieval in UWSNs
title_full Value of Information Based Data Retrieval in UWSNs
title_fullStr Value of Information Based Data Retrieval in UWSNs
title_full_unstemmed Value of Information Based Data Retrieval in UWSNs
title_sort value of information based data retrieval in uwsns
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2018-10-01
description Sensor nodes in underwater sensor networks may acquire data at a higher rate than their ability to communicate over underwater acoustic channels. Autonomous underwater vehicles may mitigate this mismatch by offloading high volumes of data from the sensor nodes and ferrying them to the sink. Such a mode of data transfer results in high latency. Occasionally, these networks need to report high priority events such as catastrophes or intrusions. In such a scenario the expectation is to have a minimal end-to-end delay for event reporting. Considering this, underwater vehicles should schedule their visits to the sensor nodes in a manner that aids efficient reporting of high-priority events. We propose the use of the Value of Information metric in order to improve the reporting of events in an underwater sensor network. The proposed approach classifies the recorded data in terms of its value and priority. The classified data is transmitted using a combination of acoustic and optical channels. We perform experiments with a binary event model, i.e., we classify the events into high-priority and low-priority events. We explore a couple of different path planning strategies for the autonomous underwater vehicle. Our results show that scheduling visits to sensor nodes, based on algorithms that address the value of information, improves the timely reporting of high priority data and enables the accumulation of larger value of information.
topic under water sensor network
mobility
path planning
routing
quality of information
value of information
mobile sink
data mule
UWSN
AUV
QoS
QoI
VoI
url http://www.mdpi.com/1424-8220/18/10/3414
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