相关论文: Compressed Sensing in Multi-Hop Large-Scale Wirele…

A Wireless Sensor Network (WSN) is a collection of tiny nodes that have low energy levels and have become an essential component of the modern communication infrastructure and very important in industry and academia. Energy is crucial in…

Wireless sensor networks (WSN) acts as the backbone of Internet of Things (IoT) technology. In WSN, field sensing and fusion are the most commonly seen problems, which involve collecting and processing of a huge volume of spatial samples in…

Compressive sensing has been receiving a great deal of interest from researchers in many areas because of its ability in speeding up data acquisition. This framework allows fast signal acquisition and compression when signals are sparse in…

Design of control applications over wireless sensor networks (WSNs) is a challenging issue due to the bandwidth-limited communication medium, energy constraints and real-time data delivery requirements. This paper introduces a new…

Reliable and energy-efficient wireless data transmission remains a major challenge in resource-constrained wireless neural recording tasks, where data compression is generally adopted to relax the burdens on the wireless data link.…

Wireless Sensor Networks are basically used for gathering information needed by smart environments but they are particularly useful in unattended situations where terrain, climate and other environmental constraints may hinder in the…

In this paper we investigate the problem of gathering the data in wireless sensor network using a single Mobile Element. In particular we consider the case where the data are produced by measurements and they need to be delivered to a…

In wireless sensor networks (WSNs), implementing a high-precision time synchronization scheme on resource-constrained sensor nodes is a major challenge. Our investigation of the practical implementation on a real testbed of the…

In this paper, we demonstrate some applications of compressive sensing over networks. We make a connection between compressive sensing and traditional information theoretic techniques in source coding and channel coding. Our results provide…

Compressed sensing (CS) enables people to acquire the compressed measurements directly and recover sparse or compressible signals faithfully even when the sampling rate is much lower than the Nyquist rate. However, the pure random sensing…

This paper presents a wireless neural recording system featuring energy-efficient data compression and encryption. An ultra-high efficiency is achieved by leveraging compressed sensing (CS) for simultaneous data compression and encryption.…

The wireless sensor network is a collection of energy-constrained nodes. Their objective is to sense, collect and process information for some ad-hoc purpose. Typically the nodes are deployed in geographically inaccessible regions. Thus the…

There is an immediate need for creative ways to improve resource ef iciency given the dynamic nature of robust sensor networks and their increasing reliance on data-driven approaches.One key challenge faced is ef iciently managing large…

Energy is one of the most important resources in wireless sensor networks. Recently, the mobility of base station has been exploited to preserve the energy. But in event driven networks, the mobility issue is quite different from the…

The ever-increasing number of WSN deployments based on a large number of battery-powered, low-cost sensor nodes, which are limited in their computing and power resources, puts the focus of WSN time synchronization research on three major…

In recent years, the wireless sensor network (WSN) is playing a key role in sensing, collecting and disseminating information in various applications. An important feature associated with WSN is to develop an efficient data distribution and…

Compressive sensing has been successfully used for optimized operations in wireless sensor networks. However, raw data collected by sensors may be neither originally sparse nor easily transformed into a sparse data representation. This…

The purpose of a wireless sensor network (WSN) is to provide the users with access to the information of interest from data gathered by spatially distributed sensors. Generally the users require only certain aggregate functions of this…

Compressive sampling has shown great potential for making wideband spectrum sensing possible at sub-Nyquist sampling rates. As a result, there have recently been research efforts that aimed to develop techniques that leverage compressive…

We propose a novel search-and-rescue management method that relies on the aerial deployment of Wireless Sensor Network (WSN) for locating victims after floods. The sensor nodes will collect vital information such as heat signatures for…