# 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. under water sensor network; mobility; path planning; routing; quality of information; value of information; mobile sink; data mule; UWSN; AUV; QoS; QoI;  
communication channel can be used to offload large quantities of data from the sensor nodes to AUVs which are in close proximity [11]. An important issue for offloading data from sensor nodes using AUVs is the path planning for the AUV, i.e., the sequence in which the AUV visits the nodes for data offloading. An efficiently planned path can reduce the overall data delivery latency and increase the information accumulated over a set period of time. The visitation sequence also determines the order of priority in which emergency reporting nodes are catered to. Let us assume that there is a surveillance or monitoring application that must report a significant event on an urgent basis. In a traditional sensor network, the information can be sent to the sink node instantaneously by initiating a data transfer from either the sink or the source nodes. However, for UWSNs with mobile sinks, the sensor nodes must signal the event to a remote agent that controls the AUV. The AUV must travel to the required node for data collection. The tour time of an AUV depends upon the speed of the AUV and the weather and oceanic conditions. The timing of delivery of data from the sensor nodes to the sink is determined by the schedule of resurfacing, diving and node visitation. Therefore, the time taken to report the information about an event depends upon the choices made by the path planning algorithm for the AUV. Figure 1 describes a generalized example of such a monitoring application where an AUV has been deployed to retrieve data from the underwater sensor nodes. In this paper, we extend our work regarding the use of the value of information (VoI) in UWSNs [12]. We employ VoI in a similar spirit to as it has been described in [13; 14; 15]. We argue the advantage of employing VoI in UWSNs through an example. We propose the use of VoI functions, which we have named as Infotentials. Infotentials are monotonically decreasing functions that model the temporal depreciation of VoI. Drawing from intuition based on these functions, we develop heuristics that are to be used for the AUV path planning. We formulate five different path planning algorithms for the AUVs for data collection purposes. In the end, we provide a detailed comparative analysis of the path planners for VoI maximization. This paper has been organized in the following manner.