On Optimal Information Capture by Energy-Constrained Mobile Sensors

• Published in: IEEE transactions on vehicular technology Vol. 59; no. 5; pp. 2472 - 2484
• Main Authors: Shibo He, Jiming Chen, Youxian Sun, Yau, David K Y, Nung Kwan Yip
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01-06-2010; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Biosensors; Chemical and biological sensors; Detection, estimation, filtering, equalization, prediction; Energy capture; Energy consumption; Exact sciences and technology; Industrial control; Information analysis; Information, signal and communications theory; Intelligent sensors; mobile sensor coverage; Monitoring; quality of monitoring (QoM); Random processes; sensor network; Sensors; Signal and communications theory; Signal, noise; Studies; Sun; Telecommunications and information theory; Utility functions; Energy consumption; quality of monitoring (QoM); Multisensor; Utility function; Measurement sensor; Coverage; Scheduling; Stochastic process; Optimization; mobile sensor coverage; sensor network; Quality control; Analytical method; Electric power consumption; System simulation; Sensor array; Signal detection; Gain
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2010.2044592

A mobile sensor is used to cover a number of points of interest (PoIs), where dynamic events appear and disappear according to the given random processes. The sensor, which is of sensing range r, visits the PoIs in a cyclic schedule and gains information about any event that falls within its range. We consider the temporal dimension of the sensing as given by a utility function, which specifies how much information is gained about an event as a function of the cumulative sensing or observation time. The quality of monitoring (QoM), i.e., the fraction of information captured about all events, depends on the speed of the sensor and has been analyzed in an earlier paper for different utility functions. The prior work, however, does not consider the energy of motion, which is an important constraint for mobile sensor coverage. In this paper, we analyze the expected Information captured Per unit of Energy consumption (IPE) as a function of the event type (in terms of the utility function), the event dynamics, and the speed of the mobile sensor. Our analysis uses a realistic energy model of motion, and it allows the sensor speed to be optimized for information capture. The case of multiple sensors will also be discussed. Extensive simulation results verify and illustrate the analytical results.