F. Khan, S. Khan, D. Turgut, and L. Bölöni. Optimizing Resurfacing Schedules to Maximize Value of Information in UWSNs. In Proceedings of IEEE GLOBECOM'16, December 2016.
In Underwater Sensor Networks (UWSNs) with high volume of data recording activity, a mobile sink such as a Autonomous Underwater Vehicle (AUV) can be used to offload data from the sensor nodes. When the AUV approaches the underwater node, it can use high data rate optical communication. However, the data is not considered delivered when it was transferred from the sensor node to the AUV, but when the AUV had resurfaced and transferred the data to the sink. If the data is not time sensitive, it is sufficient for the AUV to resurface only once at the end of its data collection path. However, for time-sensitive data, it is more advantageous for the AUV to resurface multiple times during its path, and upload the data collected since the previous resurfacing. Thus, a resurfacing schedule needs to complement the path planning process. In this paper we are using the metric of Value of Information (VoI) as the optimization criteria to capture the time- sensitive nature of collected information. We propose a genetic algorithm based approach to determine the resurfacing schedule for an AUV which is already provided with the sequence of nodes to be visited.
@inproceedings{Khan-2016-GLOBECOM,
author = "F. Khan and S. Khan and D. Turgut and L. B{\"o}l{\"o}ni",
title = "Optimizing Resurfacing Schedules to Maximize Value of Information in UWSNs",
booktitle = "Proceedings of IEEE GLOBECOM'16",
month = "December",
year = "2016",
abstract = {In Underwater Sensor Networks (UWSNs) with high volume of data recording activity, a mobile sink such as a Autonomous Underwater Vehicle (AUV) can be used to offload data from the sensor nodes. When the AUV approaches the underwater node, it can use high data rate optical communication. However, the data is not considered delivered when it was transferred from the sensor node to the AUV, but when the AUV had resurfaced and transferred the data to the sink. If the data is not time sensitive, it is sufficient for the AUV to resurface only once at the end of its data collection path. However, for time-sensitive data, it is more advantageous for the AUV to resurface multiple times during its path, and upload the data collected since the previous resurfacing. Thus, a resurfacing schedule needs to complement the path planning process. In this paper we are using the metric of Value of Information (VoI) as the optimization criteria to capture the time- sensitive nature of collected information. We propose a genetic algorithm based approach to determine the resurfacing schedule for an AUV which is already provided with the sequence of nodes to be visited. },
}
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