Wireless Visual Sensor Networks Energy Optimization Based on New Entropy Model

Abstract

Last advances in low power sensors has led to the development of wireless visual sensor networks. These networks comparing to traditional wireless sensor networks provides valuable visual information, therefor are suitable for surveillance and control applications. One of the important challenges in wireless visual sensor networks is energy consumption. Therefore, in this paper we address the problem of energy optimization in wireless visual sensor networks. The entropy of the captured images in each camera node sensor as a quality criteria is used. For realization of this goal, we introduced a new formula for expressing the entropy of captured image in each camera node. This model is a function of the distance between camera node and target and the angel between the main view line of camera and the target. Then, we introduced a new formula which expresses the relation between the image entropy and the number of bits required for displaying image pixel value. In next step, we proposed node selection algorithm based on entropy. For proposing our algorithm, first optimization of energy consumption is formulated, then the problem is solved as a convex problem. We used from CVX library in MATLAB and Log-Barrier Method for solving our problem and shown the simulation result of them. Finally, we compare our proposed algorithm with MDT benchmark algorithm, CVX and Log-Barrier algorithms. Also we compare the sensitivity to error for both algorithms.