Distributed Detection and Estimation in Wireless Sensor Networks

  title={Distributed Detection and Estimation in Wireless Sensor Networks},
  author={Sergio Barbarossa and Stefania Sardellitti and Paolo Di Lorenzo},

Fault-Resilient Distributed Detection and Estimation Over a SW-WSN Using LCMV Beamforming

Analysis and experimental results obtained demonstrate that the proposed SW-WSN model achieves faster convergence rates for both distributed detection and distributed estimation while being resilient to node failures when compared to results obtained using state-of-the-art methods.

Distributed Two-Step Quantized Fusion Rules Via Consensus Algorithm for Distributed Detection in Wireless Sensor Networks

Simulations show that the proposed quantized two-step distributed detection algorithm approaches the performance of the unquantized centralized (with a fusion center) detector and its power consumption is shown to be 50% less than the existing (unquantized) conventional algorithm.

Quantized fusion rules for energy-based distributed detection in wireless sensor networks

It is shown how the effect of quantizing the test statistic can be mitigated by increasing the number of SN samples, i.e., bandwidth can be traded off against increased latency.

Distributed detection in practical wireless sensor networks via a two-step consensus algorithm

Simulations show that the proposed quantized two-step distributed detection algorithm approaches the performance of the unquantized centralized (fusion center) detector.

Energy Balancing for Robotic Aided Clustered Wireless Sensor Networks Using Mobility Diversity Algorithms

Simulation results show that the proposed MR aided technique is able to significantly reduce the transmission power required and thus extend the operational lifetime of the WSN.

A Distributed Algorithm for Sensor Network Localization with Limited Measurements of Relative Distance

By considering the rank constraint, a distributed algorithm is presented to solve SNL under a milder graph condition and simulation cases are presented to validate the improved localization accuracy, efficiency, and robustness by comparing to the state of the art SNL method.

A Secure Optimum Distributed Detection Scheme in Under-Attack Wireless Sensor Networks

This work addresses the problem of centralized detection of a binary event in the presence of fraction falsifiable sensor nodes (SNs) for a bandwidth-constrained under-attack spatially uncorrelated distributed wireless sensor network by adopting the modified deflection coefficient as an alternative function to be optimized.

A Practical Implementation of an Agriculture Field Monitoring Using Wireless Sensor Networks and IoT Enabled

Experimental results show that the proposed WSN features an effective large ROI monitoring with minimal number of SNs, a significantly reduced SN transmission power required and thus an extended WSN operational lifetime.

Exploration of Beamforming Approach to Enhance the Detection Rate of Underwater Targets in Distributed Multiple Sensor Systems

This work mathematically modeled the scenario and derived the equations for related parameters and verified it with simulation results, showing that the detection performance increases after each stage of distributed detection, with the aid of beamforming.

Optimal wireless power transfer and harvested power allocation for diffusion LMS in wireless sensor networks

Simulation results suggest that compared to the conventional case where there is no WPT, the network MSD is reduced by up to approximately 10 dB, because of lower sensing noise and higher information transmission power due to the additional harvested power at the CNs.

Decentralized detection in sensor networks

A binary decentralized detection problem in which a network of wireless sensors provides relevant information about the state of nature to a fusion center, and it is shown that having a set of identical binary sensors is asymptotically optimal, as the number of observations per sensor goes to infinity.

Distributed double threshold spatial detection algorithms in wireless sensor networks

Two alternative event-driven double threshold detection algorithms to be used in decentralized wireless sensor networks using a fixed sample size and a sequential detector are proposed.

Asymptotic results for decentralized detection in power constrained wireless sensor networks

Large deviation theory is used to show that having identical sensor nodes, i.e., each node using the same transmission scheme, is asymptotically optimal, and a performance metric by which sensor node candidates can be compared is established.

Distributed Detection in Sensor Networks With Packet Losses and Finite Capacity Links

It is shown that the message evolution can be reformulated as the evolution of a linear dynamical system, which is primarily characterized by network connectivity, and that a consensus to the centralized maximum a posteriori (MAP) estimate can almost always reached by the sensors for any arbitrary network.

Cross-Layer Design of Sequential Detectors in Sensor Networks

A network of sensors polled by a mobile agent (the SENMA paradigm) is used for detection purposes, with both the remote nodes and the mobile agent implementing Wald's sequential tests. When polled,

Toward a theory of in-network computation in wireless sensor networks

The topic of this article is to survey some lines of research that may be useful in developing a theory of in-network computation, which aims to elucidate how a wireless sensor network should efficiently perform such distributed computation.

Distributed signal subspace projection algorithms with maximum convergence rate for sensor networks with topological constraints

This paper proposes a distributed algorithm allowing each node to improve the reliability of its own reading thanks to the interaction with the other nodes, assuming that the field monitored by the network is a smooth function.

Computing and communicating functions over sensor networks

The maximum rate at which functions of sensor measurements can be computed and communicated to the sink node is studied, focusing on symmetric functions, where only the data from a sensor is important, not its identity.

Wireless Sensors in Distributed Detection Applications

The classical framework for decentralized detection is reviewed and it is argued that, while this framework provides a useful basis for developing a theory for detection in sensor networks, it has serious limitations.

An Efficient Message-Passing Algorithm for Optimizing Decentralized Detection Networks

This work outlines this multi-objective design problem within the Bayesian decentralized detection paradigm, modeling resource constraints by a directed acyclic network with low-rate, unreliable communication links, and state conditions under which the offline algorithm admits an efficient message-passing interpretation.