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The real time probability density function (PDF) estimation of any environmental function from sensor network measurement is addressed. The sensor measurement data is modeled using Gaussian mixture PDFs and an algorithm is proposed to estimate the parameters by maximizing the log likelihood function of the sensor data. Here the real time probability density function (PDF) estimation of environmental...
Deploying the sensor nodes at the best locations for random field reconstruction via sensor network is a fundamental task. One-dimensional random field is a stochastic process. In this paper, we first propose an optimal sensor deployment strategy for Wiener process estimation. The optimal locations for the deployed sensors are uniformly distributed in the field. In addition, we propose a suboptimal...
In a wireless sensor network nodes can be deployed randomly to collect data from an area of interest. So it is mandatory for each node in the network to be aware of its location in the physical world, in order to map the collected information to the base station. Thus, localization becomes an important technique in sensor networks. Further, power conservation is also an important factor as the nodes...
Data collection is a fundamental issue in wireless sensor networks. In many application scenarios for sensor networks, approximate data collection is a wise choice due to the constraints in communication bandwidth and energy budget. In this paper, we focus on efficient approximate data collection with given error bounds in wireless sensor networks. The key idea of our data collection approach ADC...
CDHL algorithm is a new hybrid range-free localization algorithm, which combines the Centroid and DV-Hop algorithms. The basic theory of the algorithm was introduced in this paper, and the average localization error rate of this hybrid algorithm is discussed and the algorithm energy consumption is analyzed. Simulation experiments show that the proposed algorithm is effective on different network situations,...
This paper addresses distributed tracking of the probability distribution of state parameters of a space-time-variant process described by a linear partial differential equation using a particle filter (PF). We focus on localizing an acoustic source in a given region. The underlying wave equation leads to a high-dimensional estimation problem. We propose a technique for reducing the computational...
A distributed estimation problem using sensor networks is considered. A parameter is observed in noise by sensors, phase-modulated using complex exponentials and transmitted over a Gaussian multiple-access channel to a fusion center. The received signal is used to estimate the parameter under observation. The system is evaluated using the asymptotic variance of the estimate. The relationship between...
Due to the relatively high node density and source-to-sink communication pattern, wireless sensor networks (WSNs) are subject to congestion and packet losses. Further, the availability of low-cost hardware, such as Cyclops cameras, is promoting wireless multimedia sensing to support, for example, visual surveillance. As a result, congestion control is becoming more critical in WSNs. In this paper,...
Existing contention based nonpersistent medium access control protocols in Wireless Sensor Network (WSN) do not perform well in high contention. Their performances are affected by occurrence of collision due to uniform probability distribution in choosing Time Slot (TS) during backoff period. To address this issue nonuniform probability distribution was proposed. However success rate still drops for...
Wireless sensor networks (WSN) have been proposed as a solution to environment sensing, target tracking, data collection and others. WSN collect an enormous amount of data over space and time. The objective is to estimate of a parameter or function from these data. Learning is used in detection and estimation problems when no probabilistic model relating an observation. This paper investigates a general...
Understanding the energy consumption of individual tasks in wireless sensor networks (WSN) is an important aspect for a network deployment. The fundamental task of WSNs is to gather data in the long-term manner. All additive processes such as routing and localization should not significantly affect the life time of the WSN. It was already proved that concurrent anchor free localization algorithms...
By introducing a wireless fading model, we rebuild the perception model of a wireless sensor network. The profiles of a multi-target and multi-sensor mixing matrix at each frequency are estimated as samples of the spectrum superposition of multiple targets. A differential evolution approach is employed to separate multiple targets, at the same time, to decouple path fading and Doppler shifts in the...
In this paper, the problem of sequential estimation in a wireless sensor network (WSN) is formulated in a cooperative game theoretic framework. This framework allows addressing the issue of fair resource allocation for sequential estimation task at the Fusion center (FC) in a WSN as a solution of a cooperative game. We propose a simple game theoretic solution to the problem of power allocation for...
In densely deployed wireless sensor networks, observations of the sensor nodes are spatially correlated. In this paper, we study a joint channel decoding scheme utilizing bit correlation of the sensor observations according to bit levels of analog-digital converter (ADC). If sensor ADC output is interpreted as natural binary numeral, carry propagation may occur between adjacent ADC output values....
Regression is one of the effective techniques for data analysis in a WSN. Besides distributed data, the limited power supply and bandwidth capacity of nodes makes doing regression difficult in WSNs. Conventional methods, which employ some numerical optimization techniques such as Nelder-Mead simplex and gradient descent, generally work in a pre-established Hamiltonian path among the nodes. Low estimation...
Recent advances in wireless communications technology and low-power, low-cost CMOS imaging sensors enable a new sensing modality employing ubiquitous distributed video sensing. In many video sensing applications multimedia streams are often required by the base station to provide detailed information of the target spot in the sensor field. Such applications demand a strict throughput requirement for...
We consider the problem of Maximum Likelihood (ML) estimation of clock parameters in a two-way timing exchange scenario where the random delays assume a Weibull distribution, which represents a more generalized model. The ML estimate of the clock offset for the case of exponential distribution was obtained earlier. Moreover, it was reported that when the fixed delay is known, MLE is not unique. We...
To reduce the amount of data transfer in net- worked control systems and wireless sensor networks, measurements are usually sampled only when an event occurs, rather than synchronous in time. Today's event sampling methodologies are triggered by the current value of the sensor. State-estimators are designed to cope with such methods. In this paper we propose a sampling method in which an event is...
The location estimation of sensor nodes is a fundamental and essential issue for wireless sensor networks (WSNs), because the gathered data is meaningful only when the location information of the sensor nodes is known. In this paper, we proposed a novel localization algorithm. In the proposed scheme, we first estimate the location of sensor nodes using Convex Position Estimation (CPE), and then refine...
In wireless sensor networks (WSNs) the position information of individual nodes is a matter of vital importance because allows the implementation of necessary network functions such as routing, querying and other applications. The objective of this paper is to propose an algorithm of three-dimensional distributed range-free localization for WSNs, using an unmanned aerial vehicle (UAV) equipped with...
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