A Data Aggregation Method Based on Compressed Sensing in Wireless Sensor Networks

Abstract

The invention discloses a data aggregation method based on compressed sensing in a wireless sensor network. The method includes: uniform clustering of the sensor network is performed, a node with the most residual energy is selected as a cluster head node, member nodes independently select whether to participate in sampling with the probability ptx, and the cluster head node always participate in sampling; then sampling nodes obtain original signals f and obtain sparse representations x thereof through transform of sparse transform bases, x are projected in a measuring matrix phi, sparse measuring signals y are obtained and sent to the cluster head node, and the cluster head node merges the collected measuring signals to a signal Y by employing vectorization operators and sends the signal Y to a fusion center; and finally the fusion center performs reconstruction on the signals one by one by employing an adaptive weight GPSR algorithm and recovers the sparse representations X thereof. According to the method, the characteristics of noise-containing signals, large data bulk, and high timeliness requirement of the wireless sensor network are completely achieved, the adaptive weight GPSR algorithm does not need to know the signal sparsity in advance, and all high-dimensional signals can be accurately reconstructed in a short period.

Description

technical field [0001] The invention belongs to the technical field of wireless sensor networks, and in particular relates to a data aggregation method based on compressed sensing in a wireless sensor network. Background technique [0002] In recent years, wireless sensor networks have been widely used in many fields due to their advantages of concealment, fault tolerance, and convenient deployment, such as environmental monitoring, security, and smart home. Usually, a wireless sensor network is composed of a large number of nodes with wireless communication capabilities, computing capabilities and sensing capabilities, which can cooperate to complete various tasks of environment perception, information collection and target recognition. In order to complete these tasks, each node needs to collect a large amount of real-time data and send it to the fusion center through multi-hop routing for data processing and analysis. This process requires a large amount of storage space...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a data aggregation method based on compressed sensing in a wireless sensor network, aiming to solve the problem that the traditional compressed sensing-based wireless sensor network data aggregation method has no joint utilization of information in the time and space domains. The efficiency of the network data acquisition model is low, and the amount of data transmitted between the networks is relatively large

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