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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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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