Abstract
With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s). When sensory data are collected at sink node(s), the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady.
Highlights
The Earth’s surface is mostly covered by oceans, which impact our life extensively [1]
It is worth noting that some connected components in gevt may contain the majority of event sources, since sensory data for sensor nodes in these connected components may deviate to a relatively large extent from the normal sensing range; while the situation for sensor nodes contained in the other connected components is not that serious somehow
Due to the vast un-explored ocean space and harsh underwater environments, the importance and difficulty of underwater exploration is well recognized and underwater wireless sensor networks are emerging as a pressing research topic in recent decades
Summary
The Earth’s surface is mostly covered by oceans, which impact our life extensively [1]. A monitoring course-based event localization technique is proposed in [21], where monitoring courses can facilitate the event location determination and identify possible network issues before forwarding data packets to sink node(s) These techniques are promising in determining event boundaries in underwater environments. Our sub-region query processing mechanism developed in [22] has been improved, where a set of neighboring sensor nodes, whose sensory data deviate from a normal sensing range in a collective fashion, are identified. These sensory data are routed to sink node(s) through our routing tree [22] in an energy-efficient fashion.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
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.
