A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failure...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2017-05, Vol.17 (5), p.1092
Main Authors: Kim, Changhwa, Shin, DongHyun
Format: Article
Language:English
Subjects:
Communication
Data integrity
Data loss
Datasets
Error detection
Loss reduction
Military technology
Pattern method (forecasting)
Property damage
Remote sensors
Sensors
Underwater acoustics
Wireless communications
Wireless networks
Wireless sensor networks
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Summary:There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss.
ISSN:1424-8220
1424-8220
DOI:10.3390/s17051092