Abstract
Wireless Sensor Networks (WSNs) have been extensively applied in ecological environment monitoring. Typically, event boundary detection is an effective method to determine the scope of an event area in large-scale environment monitoring. This paper proposes a novel lightweight Entropy based Event Boundary Detection algorithm (EEBD) in WSNs. We first develop a statistic model using information entropy to figure out the probability that a sensor is a boundary sensor. The EEBD is independently executed on each wireless sensor in order to judge whether it is a boundary sensor node, by comparing the values of entropy against the threshold which depends on the boundary width. Simulation results demonstrate that the EEBD is computable and offers valuable detection accuracy of boundary nodes with both low and high network node density. This study also includes experiments that verify the EEBD which is applicable in a real ocean environmental monitoring scenario using WSNs.
Highlights
Wireless Sensor Networks (WSNs) are composed of a considerable number of low-cost, low-power and small-sized wireless sensors and have gained particular interest for many environment applications [1]
When compared with the analysis of the entire event area, event boundary detection is more efficient as it provides a proper view of the sensors that will be affected by broadcast messages [4]
This paper proposes a new lightweight Event Boundary Detection distributed algorithm (EEBD) to identify the real event boundary sensor nodes of a monitoring area using WSNs
Summary
Wireless Sensor Networks (WSNs) are composed of a considerable number of low-cost, low-power and small-sized wireless sensors and have gained particular interest for many environment applications [1]. These sensor nodes are often utilized to monitor and detect real-world events like oil diffusion, fires, chemical leaks by monitoring various physical parameters such as humidity, concentration, temperature, salinity and so on. This paper proposes a new lightweight Event Boundary Detection distributed algorithm (EEBD) to identify the real event boundary sensor nodes of a monitoring area using WSNs. Two main principles of Information Entropy, that is, uncertainty and information quantity [5], are applied to figure out the Symmetry 2019, 11, 537; doi:10.3390/sym11040537 www.mdpi.com/journal/symmetry. A series of simulations show that the EEBD algorithm provides good precision when detecting event boundaries
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
