Correlation-based communication in wireless multimedia sensor networks
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Wireless multimedia sensor networks (WMSNs) are networks of interconnected devices that allow retrieving video and audio streams, still images, and scalar data from the environment. In a densely deployed WMSN, there exists correlation among the observations of camera sensors with overlapped coverage areas, which introduces substantial data redundancy in the network. In this dissertation, efficient communication schemes are designed for WMSNs by leveraging the correlation of visual information observed by camera sensors. First, a spatial correlation model is developed to estimate the correlation of visual information and the joint entropy of multiple correlated camera sensors. The compression performance of correlated visual information is then studied. An entropy-based divergence measure is proposed to predict the compression efficiency of performing joint coding on the images from correlated cameras. Based on the predicted compression efficiency, a clustered coding technique is proposed that maximizes the overall compression gain of the visual information gathered in WMSNs. The correlation of visual information is then utilized to design a network scheduling scheme to maximize the lifetime of WMSNs. Furthermore, as many WMSN applications require QoS support, a correlation-aware QoS routing algorithm is introduced that can efficiently deliver visual information under QoS constraints. Evaluation results show that, by utilizing the correlation of visual information in the communication process, the energy efficiency and networking performance of WMSNs could be improved significantly.