مقاله انگلیسی رایگان در مورد الگوریتم سنجش توزیع شده غیر متمرکز – الزویر 2019

1. Introduction

2. Compressed Sensing and Distributed Compressed Sensing

3. DDCS Model Building

4. Results

5. Discussion

6. Conclusion

References

Distributed Compressed Sensing (DCS) is an effective method to reduce data transmission and energy consumption in wireless sensor networks (WSN). To further enhance the data compression ratio in clustered WSNs, a new data collection method which named Decentralized Distributed Compressed Sensing (DDCS) is proposed in this paper. This method can be divided into three parts: cluster head election, data compression, and joint reconstruction. In the cluster head elections, sparsity is introduced as a reference factor. In data compression, the cluster head data is used as the common data of sensors in the same cluster. After remove the common data, member sensors in the same cluster only compress and transmits their specific data. In joint reconstruction, using residual correlation to reconstruct the signal through the OMP algorithm. Simulation results show that the performance of DDCS is better than traditional DCS. It can greatly reduce the amount of data transmission, the cluster head energy consumption, and the network delay at the cluster head.

Introduction

Due to the limit of energy and the difficulty in maintenance of the sensor nodes, energy consumption control is always the hot research topic of the WSN1 . Generally, there is great correlation in time and spatial of sensor data in the same area. Therefore, while ensuring that the detection information is not lost, reducing the amount of data transmission is an effective method to reduce communication energy consumption in WSN2 . A few scholars have done some researches about the combination of DCS and WSN. Cheng proposes the concept of Hierarchical Data Compressed Sensing (HDCS), which studies the compression method of correlation data from two hierarchical, within cluster and between clusters3. Some also study the fusion of DCS and clustering algorithm (LEACH, DEEN)4. Yang proposes Regionalized Compressive Sensing (RCS) whose purpose is to improve the practical efficiency of DCS applications5. In RCS, the direct transmission and DCS transmission are simultaneously applied in the wireless sensor network.