Storage Allocation for Camera Sensor Networks using Feedback-based Price Discrimination

Camera sensor networks, mainly with surveillance cameras, are growing in size and complexity. Storage space is the prime resource in such systems but current surveillance setups are still very much centralized and limited in resources due to cost and security constraints. Allocating the correct amount of storage to each camera sensor considering their large difference in characteristics and video content is challenging. In this paper we propose a framework using feedback-based price discrimination of storage resources in order to guarantee a uniform quality level of the videos in camera sensor networks, regardless of the specific camera sensor parameters. We designed a lightweight solution using simple video quality metrics, cascade control and PI (Proportional and Integral) controllers to define the optimal price of resources per camera.