Optimized energy allocation in battery powered image sensor networks

Authors:
Chao Yu;Gaurav Sharma
Affiliations:
Electrical and Computer Engineering Dept., University of Rochester, Rochester, NY;Electrical and Computer Engineering Dept., University of Rochester, Rochester, NY
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 4
Cited 1

Multiple view geometry in computer visiond

Multiple view geometry in computer visiond
The coverage problem in a wireless sensor network

Mobile Networks and Applications
Collaborative image coding and transmission over wireless sensor networks

EURASIP Journal on Applied Signal Processing
A method for coordinating the distributed transmission of imagery

IEEE Transactions on Image Processing

Camera scheduling and energy allocation for lifetime maximization in user-centric visual sensor networks

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We investigate energy allocation strategies in image sensor networks for the purpose of maximizing the network operational lifetime. For the application scenarios that we consider, visual coverage over a monitored region is obtained by deploying wireless, battery-powered image sensors. Each sensor camera provides coverage over a part of the monitored region and a central processor coordinates the sensors in order to gather required visual data. We characterize the network lifetime as a stochastic random variable that depends upon the coverage geometry for the sensors and the distribution of data requests over the monitored region. Using this characterization we consider optimized strategies for energy allocation among the sensors that maximize the expected network lifetime. The formulation naturally leads to a max-min optimization problem that aims to maximize the duration of coverage for the most critical region for which the available energy is the least. We transform this problem into an equivalent linear programming problem, leading to a computationally efficient solution. The effectiveness of the proposed energy allocation strategy is validated by simulations.