Field Reconstruction in Sensor Networks With Coverage Holes and Packet Losses

Abstract

Environmental monitoring is often performed through a wireless sensor network, whose nodes are randomly deployed over the geographical region of interest. Sensors sample a physical phenomenon (the so-called field) and send their measurements to a sink node, which is in charge of reconstructing the field from such irregular samples. In this work, we focus on scenarios of practical interest where the sensor deployment is unfeasible in certain areas of the geographical region, e.g., due to terrain asperities, and the delivery of sensor measurements to the sink may fail due to fading or to transmission collisions among sensors simultaneously accessing the wireless medium. Under these conditions, we carry out an asymptotic analysis and evaluate the quality of the estimation of a d-dimensional field (d ≥ 1) when the sink uses linear filtering as a reconstruction technique. Specifically, given the matrix representing the sampling system, V, we derive both the moments and an expression of the limiting spectral distribution of VV H , as the size of V goes to infinity and its aspect ratio has a finite limit bounded away from zero. By using such asymptotic results, we approximate the mean square error on the estimated field through the η-transform of VV H , and derive the sensor network performance under the conditions described above.

Continuous tracking for mobile targets with mobility nodes in WSNs

“…According to formulas (2) and (3), when the target appears, the probability of getting the measurement ei for sensor i is expressed as: (4) Sensor i compares its measurement with a threshold A. If its measurement is greater than A, it decides 1 which means it can detect the target, otherwise decides 0 means cannot.…”

“…Second, in practice, it is difficult to deploy sensor nodes evenly in the deployment area. Generally, sensors are scattered randomly so that some coverage holes may exist in the networks [4]. If targets enter the area in holes, no sensors can monitor them effectively.…”

Investigating the accuracy of mobile urban sensing

“…Since V depends on the sampling positions, which are distributed according to f (z 1 , z 2 ), in the following we refer to η V as η f . We then use a result appeared in [6] that links η f to η u , i.e., the η-transform of VV H computed in the case where the sample locations are random variables with uniform distribution. We obtain:…”

“…II. Finally, the analytical expressions of the g(y) required by (6) were obtained by fitting mixed normal/exponential distributions to the experimental data. The process was repeated for different combinations of road type, daytime and vehicle penetration rate.…”

Lifetime Maximization for Multi-modal Confident Information Coverage in Sensor Networks

“…Wireless sensor networks (WSNs) recently have been used for a large variety of critical applications, such as environmental monitoring [2], field reconstruction [3] and precision agriculture [4]. These applications normally have strict user coverage requirements.…”