Optimal video sensing strategy and performance optimization for mobile wireless video sensors

Wireless video sensor networks have been envisioned for a wide variety of important applications. In this work, we investigate the following research problem: given a mobile video sensor with an initial resource configuration, what is the maximum video quality it can provide, and what is the best video encoding and streaming strategy to achieve this performance? To address this problem, we study the energy consumption of each sensor node in video compression and wireless data transmission. We statistically model the node mobility and study its impact on wireless video transmission. We develop a task-oriented performance metric to measure the video sensing performance of the sensor node. We develop an optimal resource allocation and scheduling scheme for the video sensor to maximize the performance metric. The results provide an important step stone for our future performance study of wireless video sensor networks.