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Video sensor network.
In fact the term wireless video sensor network has been coined (e.g., [1 3]), reflecting the relevance that video transmission in WSN has gained.
Each video is 10s length and downsampled to 15 frame per seconds (fps) 416×240 pixels to mimic the requirement of a decent video sensor network.
Wireless video sensor network (VSN) has the potential to improve the ability to develop user-centric surveillance applications to monitor and prevent harmful events [4,5].
To this end, we propose a fully distributed algorithm, that considers the problem of allocating the resources in wireless video sensor network, in a way to ensure a trade-off between both: the encoding power and the source rate at each node, while serving the desired video quality requirement.
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The power management problem in video sensor networks was investigated [15].
These days, video sensor networks are also used to monitor very large outdoor areas for environment surveillance and safety.
Such paradigm can be used to implement video sensor networks (VSNs) that can serve as an alternative to existing video surveillance applications.
The authors in [26] developed a generalized power consumption model to address the optimization of network lifetime and resource allocation for wireless video sensor networks (WVSNs).
The emerging development of video sensor networks poses its own set of unique challenges, including high-bandwidth and low latency requirements for real-time processing and control.
While research into large-scale sensor networks has been carried out for various applications, the idea of massive video sensor networks consisting of cameras connected over a wireless network is largely new and relatively unexplored.
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