Energy-efficient Data Aggregation Schemes for Low-power Distributed Wireless Sensor Networks using Compressed Sensing

The advancements in distributed computing and technologies such as Industry 4.0 have rapidly deployed wireless sensor networks. In many scenarios, battery-connected wireless sensors gather the surrounding information that is to be aggregated at a base station. The volume of data generated from large-scale wireless networks has significant impacts on storage, network latency, and bandwidth. This demands efficient data aggregation systems for new-generation smart networks. Compressed sensing techniques are proven to deliver efficient compression for sparse signals. This paper evaluates the extension of such compression techniques to distributed low-power wireless sensor networks for efficient data aggregation.