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Stochastic Event Capture Using Mobile Sensors Subject to a Quality Metric
 

Summary: i
Stochastic Event Capture Using Mobile Sensors
Subject to a Quality Metric
Nabhendra Bisnik, Student Member, IEEE, Alhussein A. Abouzeid, Member, IEEE, Volkan Isler, Member, IEEE
Abstract
Mobile sensors cover more area over a fixed period of time than the same number of stationary sensors. However, the quality of
coverage achieved by mobile sensors depends on the velocity, mobility pattern, number of mobile sensors deployed and the dynamics
of the phenomenon being sensed. The gains attained by mobile sensors over static sensors and the optimal motion strategies for
mobile sensors are not well understood. In this paper we consider the following event capture problem: The events of interest arrive
at certain points in the sensor field and disappear according to known arrival and departure time distributions. An event is said to
be captured if it is sensed by one of the mobile sensors before it fades away. We analyze how the quality of coverage scales with
velocity, path and number of mobile sensors. We characterize cases where the deployment of mobile sensors has no advantage over
static sensors and find the optimal velocity pattern that a mobile sensor should adopt.
We also present algorithms for two motion planning problems: (i) for a single sensor, what is the sensor trajectory and the
minimum speed required to satisfy a bound on the event loss probability, and (ii) for sensors with fixed speed, what is the minimum
number of sensors required to satisfy a bound on the event loss probability?
When the robots are restricted to move along a line or a closed curve, our algorithms return the optimal velocity for the minimum
velocity problem. For the minimum sensor problem, the number of sensors used is within a factor of two of the optimal solution.
For the case where the events occur at arbitrary points on a plane, we present heuristic algorithms for the above motion planning
problems and bound their performance with respect to the optimal.

  

Source: Abouzeid, Alhussein A. - Department of Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute

 

Collections: Engineering; Computer Technologies and Information Sciences