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Retrieval of Mouse Oocytes
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Value of Information Based Data Retrieval in UWSNs.

Fahad Ahmad Khan1,2, Sehar Butt3, Saad Ahmad Khan4,5

  • 1Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USA. fahad.khan@knights.ucf.edu.

Sensors (Basel, Switzerland)
|October 14, 2018
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Summary

Autonomous underwater vehicles improve high-priority event reporting in sensor networks by using a Value of Information metric. This approach prioritizes data, reducing latency for critical event detection and enhancing overall network efficiency.

Keywords:
AUVQoIQoSUWSNVoIdata mulemobile sinkmobilitypath planningquality of informationroutingunder water sensor networkvalue of information

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Area of Science:

  • * Underwater Sensor Networks
  • * Robotics and Autonomous Systems
  • * Data Communication and Networking

Background:

  • * Underwater sensor networks face challenges with high data acquisition rates exceeding communication capabilities via acoustic channels.
  • * Autonomous underwater vehicles (AUVs) are used for data offloading, but this can introduce significant latency.
  • * Timely reporting of high-priority events (e.g., catastrophes, intrusions) is crucial, demanding minimal end-to-end delay.

Purpose of the Study:

  • * To enhance the reporting of high-priority events in underwater sensor networks.
  • * To investigate the effectiveness of the Value of Information (VoI) metric for optimizing AUV data collection and delivery.
  • * To compare different path planning strategies for AUVs based on data value and priority.

Main Methods:

  • * Development and application of a Value of Information metric to classify sensor data by value and priority.
  • * Utilizing a hybrid approach for data transmission, combining acoustic and optical communication channels.
  • * Experimental evaluation using a binary event model (high-priority vs. low-priority events) and distinct AUV path planning strategies.

Main Results:

  • * AUV path planning algorithms incorporating the Value of Information metric significantly improve the timely reporting of high-priority data.
  • * The proposed approach leads to the accumulation of greater overall information value within the network.
  • * Effective classification and prioritization of data are key to reducing latency for critical event dissemination.

Conclusions:

  • * The Value of Information metric offers a viable strategy for optimizing data reporting in underwater sensor networks with AUVs.
  • * Intelligent scheduling of AUV visits based on data value and priority is essential for efficient and timely event reporting.
  • * This research demonstrates a method to balance data offloading needs with the critical requirement for rapid high-priority event detection.