Sensor scheduling with time, energy and communication constraints

C. Rusu, John Thompson, Neil Robertson

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
278 Downloads (Pure)


In this paper we present new algorithms and anal- ysis for the linear inverse sensor placement and scheduling problems over multiple time instances with power and communi- cations constraints. The proposed algorithms, which deal directly with minimizing the mean squared error (MSE), are based on the convex relaxation approach to address the binary optimization scheduling problems that are formulated in sensor network scenarios. We propose to balance the energy and communications demands of operating a network of sensors over time while we still guarantee a minimum level of estimation accuracy. We measure this accuracy by the MSE for which we provide average case and lower bounds analyses that hold in general, irrespective of the scheduling algorithm used. We show experimentally how the proposed algorithms perform against state-of-the-art methods previously described in the literature.
Original languageEnglish
Pages (from-to)528-539
JournalIEEE Transactions on Signal Processing
Issue number2
Early online date13 Nov 2017
Publication statusPublished - 15 Jan 2018


Dive into the research topics of 'Sensor scheduling with time, energy and communication constraints'. Together they form a unique fingerprint.

Cite this