Approximate l0recovery algorithm-based data collection scheme in wireless sensor networks

作者：Li Guorui; Wang Ying; He Jingsha

来源：Journal of Huazhong University of Science and Technology (Natural Science Edition), 2015, 43(5): 39-43.

DOI：10.13245/j.hust.150508

• Compressive sampling
• Data collection
• Data collection scheme
• Matrix projection
• Minimization problems
• Recovery algorithms
• Unconstrained optimization problems
• Weighting functions

To solve the data collection problem in wireless sensor network, an efficient and energy-saving data collection scheme based on compressive sampling theory was proposed. The matrix projection method was adopted to compress the sensors'sensed data in the data collection phase. Meanwhile, in order to convert the constrained l0norm minimization problem into an unconstrained optimization problem, a family of exponential functions was utilized to approximate the l0norm of the original signal in the data recovery phase. Furthermore, a series of weighting functions were also designed to accelerate the convergence speed of the recovery algorithm. The experiment results have shown that the proposed scheme is efficient and low cost in terms of bandwidth and energy in the data collection phase and also provides a higher recovery rate than the existed recovery schemes within an appropriate reconstruction time in the data recovery phase.

• 出版日期2015
• 单位北京大学; 东北大学