# Optimizing Resurfacing Schedules to Maximize Value of Information in UWSNs

### Cite as:

F. A. Khan, S. A. Khan, D. Turgut, and L. Bölöni. Optimizing Resurfacing Schedules to Maximize Value of Information in UWSNs. In Proc of. IEEE Global Communications Conference (GLOBECOM 2016), December 2016.

(unavailable)

### Abstract:

Underwater Sensor Networks (UWSNs) are prone to low data rate communication issues. In time-sensitive UWSNs with high volume of data recording activity, mobile sinks such as Autonomous Underwater Vehicles (AUVs) are used to offload data from the sensor nodes. The AUV communicates with the sensor node using high data rate optical communications over very short distances. Efficient path planning of AUVs is necessary in order to offload data in a timely manner to the sink. This path planning involves time sensitivity of the data at the sensor nodes and resurfacing locations for the AUV. We provide genetic algorithm based solutions for determining resurfacing schedules provided the AUV already has the information of the sequence of nodes that are required to be visited. We use Value of Information (VoI) as a time based metric to aid in the development of our algorithms in order to timely retrieve data so that it may help in e.g. responding to emergency stimuli on a priority real-time basis.

### BibTeX:

@inproceedings{FAKhan-2016-Globecom,
title = "Optimizing Resurfacing Schedules to Maximize Value of Information in {UWSN}s",
author = "F. A. Khan and S. A. Khan and D. Turgut and L. B{\"o}l{\"o}ni",
booktitle = "Proc of. IEEE Global Communications Conference (GLOBECOM 2016)",
year = "2016",
month = "December",
doi = "10.1109/glocom.2016.7842108",
abstract = {
Underwater Sensor Networks (UWSNs) are prone to low data rate communication issues. In time-sensitive UWSNs with high volume of data recording activity, mobile sinks such as Autonomous Underwater Vehicles (AUVs) are used to offload data from the sensor nodes. The AUV communicates with the sensor node using high data rate optical communications over very short distances. Efficient path planning of AUVs is necessary in order to offload data in a timely manner to the sink. This path planning involves time sensitivity of the data at the sensor nodes and resurfacing locations for the AUV. We provide genetic algorithm based solutions for determining resurfacing schedules provided the AUV already has the information of the sequence of nodes that are required to be visited. We use \emph{Value of Information (VoI)} as a time based metric to aid in the development of our algorithms in order to timely retrieve data so that it may help in e.g. responding to emergency stimuli on a priority real-time basis.
},
}


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