Value of Information Based Data Retrieval in UWSNs

Abstract

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.

Value of Information in Wireless Sensor Network Applications and the IoT: A Review

“…In [23], they propose a genetic algorithm to find the optimal resurfacing time for the AUV that maximizes the collected VoI. The results in [24] indicate an improvement of the information quality collected by the AUV when incorporating VoI in path planning algorithms.…”

“…Most approaches in this category combine a base value V max with a decay function f (t, t 0 ), where an information object generated at time t 0 has value V max which then decays over time. Most commonly used are exponential decay functions [19], [24], [32]. At time t, the VoI can for instance be expressed as…”

Data Management for Enhanced Resource Utilization in Internet of Things Systems

“…Considering the VoI is beneficial for improving the collected data quality in multi-application IoT systems, however, it does not improve the resilience of data collection in congested WSNs with high packet loss. In a few recent studies, [62][63][64][65], the VoI has been used in order to improve data management in WSNs. The studies include different strategies aiming to maximize the collected VoI including transmission scheduling, path finding, and routing algorithms.…”