4 research outputs found
Stationary and Mobile Target Detection using Mobile Wireless Sensor Networks
In this work, we study the target detection and tracking problem in mobile
sensor networks, where the performance metrics of interest are probability of
detection and tracking coverage, when the target can be stationary or mobile
and its duration is finite. We propose a physical coverage-based mobility
model, where the mobile sensor nodes move such that the overlap between the
covered areas by different mobile nodes is small. It is shown that for
stationary target scenario the proposed mobility model can achieve a desired
detection probability with a significantly lower number of mobile nodes
especially when the detection requirements are highly stringent. Similarly,
when the target is mobile the coverage-based mobility model produces a
consistently higher detection probability compared to other models under
investigation.Comment: 7 pages, 12 figures, appeared in INFOCOM 201
Space-time percolation and detection by mobile nodes
Consider the model where nodes are initially distributed as a Poisson point
process with intensity over and are moving in
continuous time according to independent Brownian motions. We assume that nodes
are capable of detecting all points within distance of their location and
study the problem of determining the first time at which a target particle,
which is initially placed at the origin of , is detected by at
least one node. We consider the case where the target particle can move
according to any continuous function and can adapt its motion based on the
location of the nodes. We show that there exists a sufficiently large value of
so that the target will eventually be detected almost surely. This
means that the target cannot evade detection even if it has full information
about the past, present and future locations of the nodes. Also, this
establishes a phase transition for since, for small enough ,
with positive probability the target can avoid detection forever. A key
ingredient of our proof is to use fractal percolation and multi-scale analysis
to show that cells with a small density of nodes do not percolate in space and
time.Comment: Published at http://dx.doi.org/10.1214/14-AAP1052 in the Annals of
Applied Probability (http://www.imstat.org/aap/) by the Institute of
Mathematical Statistics (http://www.imstat.org