Data Aggregation and Clustering

This chapter explores four main concepts to minimize communications in very large wireless sensor networks (WSN): clustering, compression, in‐network processing, and compressive sensing. The main idea of clustering is to organize the network into smaller sub‐networks, so that data can be collected and analyzed in a location‐restricted way, meaning only some important or aggregated data comes to the final network‐wide sink. There are mainly two concepts for in‐network aggregation and processing: compression and aggregation. In compression, data remains as it is, but its resource usage is minimized. In aggregation, the data is somehow processed and only part of it continues to the sink. The chapter provides some examples of compression and aggregation. Compressive sampling is a powerful approach to reduce the amount of produced data at its source. It is quite similar to compression techniques but works before the data has been sampled.