Stochastic event capture using mobile sensors subject to a quality metric

Abstract

Mobile sensors cover more area over a 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 problem of event capture using mobile sensors. The events of interest arrive at certain points in the sensor field and fade away according to 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. For this scenario we analyze how the quality of coverage scales with the velocity, path and number of mobile sensors. We characterize the 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 minimum speed and sensor trajectory required to satisfy a bound on event loss probability and (ii) for sensors with fixed speed, what is the minimum number of sensors required to satisfy a bound on event loss probability. When events occur only along a line or a closed curve our algorithms return optimal velocity for the minimum velocity problem. For the minimum sensor problem, the number of sensors used is within a factor 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. The results of this paper have wide range of applications in areas like surveillance, wildlife monitoring, hybrid sensor networks and under-water sensor networks.

Novel Methods for Multi-hop Sensor Positioning on the Surface of a Solar System Body

“…Controlled movement generally consists of mobile devices in the network and moving to specified destinations with defined mobility patterns for specific objectives. The receiver node can adapt its route to achieve more efficient coverage management [16][17][18], energy composition reduction [19,20], transport layer parameters' improvement [21,22], etc. Controlling the device's movements offers new possibilities to improve the data collection efficiency, or optimize the network topology for different type of objectives as the above referenced works show [23].…”

Optimising quality of information in data collection for mobile sensor networks

“…Similarly, Gu et al [9] propose a partition-based algorithm to schedule the movement of mobile elements, which minimises the required moving speed and eliminates buffer overflow. Bisnik et al [10] further study the problem of quality coverage on event detection using mobile sensors. They also analyse the effect of controlled mobility to the fraction of events captured.…”

DREAM: On the reaction delay in large scale wireless networks with mobile sensors

“…These studies are based on random mobility model and do not address the issue of actively controlling the movement of sensors. Bisnik et al [6] analyzed the performance of detecting stochastic events using mobile sensors. Chin et al [4] proposed to improve the coverage of a region by patrolling static routes using mobile sensors.…”