Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks

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.

Collective Event Detection Using Bio-inspired Minimalistic Communication in a Swarm of Underwater Robots

“…Many algorithms and protocols have been proposed and implemented for improving deep sea monitoring using underwater wireless sensor networks (UWSNs) (Zhou et al, 2015;Debont et al, 2012). Although many techniques used in the classical wireless sensor networks can be used for their underwater counterparts, communication in an underwater environment is especially challenging.…”

“…Since underwater sensor networks might be mobile due to underwater currents, the communication protocol presented by Zhou et al (2015) includes a "heartbeat" which periodically communicates with neighboring nodes and constructs a routing tree. Additionally, the system aggregates data and processes it locally to detect an event before forwarding the event to the sink node.…”

“…Repeated and periodic exchange of information is employed in the above implementations of event detection. While a "heartbeat" signal (Zhou et al, 2015) is important for dynamic deep sea sensor networks where nodes move with currents, it is a costly solution for the shallow lagoon of Venice with minimal water movement. As previously mentioned, each aMussel robot is able to dive up to the surface of the lagoon and use their ultra long range communication capabilities to alert the base station and therefore obviates beacon nodes as in (Debont et al, 2012) or "data aggregator" nodes.…”

“…As previously mentioned, each aMussel robot is able to dive up to the surface of the lagoon and use their ultra long range communication capabilities to alert the base station and therefore obviates beacon nodes as in (Debont et al, 2012) or "data aggregator" nodes. In addition, the construction of an elaborate routing tree as suggested by Zhou et al (2015) and (Debont et al, 2012) necessitates an increased communication payload which is not necessary for event detection in systems such as the robotic swarms developed within the framework of subCULTron.…”

“…Many environmental monitoring systems which use sensor networks for collecting data in a large area have focused on reducing the energy consumption in order to increase network longevity (Zhou et al, 2015;Kaur and Sood, 2017). However, most of the existing protocols and algorithms for underwater sensor networks focus on making the algorithms usable for a wide range of communication devices, especially for deep sea environments.…”