Compressive sensing (CS) has become a popular signal processing technique and has
extensive applications in numerous fields such as wireless communications, image …

In this paper, we propose an integration of compressive sensing (CS) and clustering in
WSNs utilizing block diagonal matrices (BDMs) as the measurement matrices. Such an …

This paper considers sequential compressed acquisition and progressive reconstruction of
spatially and temporally correlated sensor data streams in wireless sensor networks (WSNs) …

Abstract Conventional Compressive Sampling (CS)-based data aggregation methods
require a large number of sensor nodes for each CS measurement leading to an inefficient …

In this paper, we propose a distributed data collection algorithm for robotic networks, which
exploits the integration between compressed sensing (CS) and collaboration of mobile …

Compressive sensing (CS) provides a new paradigm for data collection in wireless sensor
networks (WSNs). In this paper, we continue to exploit the integration between CS and tree …

In this paper, an integration of compressive sensing (CS) and clustering in wireless sensor
networks (WSNs) is proposed to significantly reduce the energy consumption related to data …

Abstract The Internet of Things (IoTs) is an integrated network including physical devices,
mobile robots, cameras, sensors, vehicles, etc. There are many items embedded with …

Wireless sensor networks (WSNs) provide a lot of emerging applications. They suffer from
some limitations such as energy constraints and cooperative demands essential to perform …

Wireless sensor networks (WSNs) could benefit a lot from compressive sensing (CS).
Inherent physical structure of sensors of WSNs (battery‐powered devices) demands …