Reduction in Encoding Redundancy over Visual Sensor Networks

Abstract

Visual sensor networks (VSN) are wireless sensor networks in which each sensor has video capture and processing capability.Power consumption may be examined for encoding, transmitting, and receiving subsystems, and research has been performed on minimizing these power levels in parallel. When multiple camera modules of a visual sensor node are aimed at the same objects with different fields of view (FOVs), the captured images may overlap. Such overlapped FOVs give rise to encoding redundancy over the VSN and also lead to increased power consumption among adjacent nodes. The power-rate-distortion (P-R-D) is determined and used to construct an optimization problem for minimizing power consumption of each node, hence maximizing node lifetime. The optimal solution provides distributed power allocation and node scheduling over the VSN at the same time, via simple information sharing, resulting in network lifetime maximization. .