Wu, Shuang and Ren, Xiaoqiang and Dey, Subhrakanti and Shi, Ling (2017) Optimal Scheduling of Multiple Sensors with Packet Length Constraint. IFAC-PapersOnLine, 50 (1). pp. 14430-14435. ISSN 2405-8963

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Abstract

This paper considers the problem of sensory data scheduling of multiple processes. There are n independent linear time-invariant processes and a remote estimator monitoring all the processes. Each process is measured by a sensor, which sends its local state estimate to the remote estimator. The sizes of the packets are different due to different dimensions of each process, and thus it may take different lengths of time steps for the sensors to send their data. Because of bandwidth limitation, only a portion of all the sensors are allowed to transmit in each time step. Our goal is to minimize the average of estimation error covariance of the whole system at the remote estimator. The problem is formulated as a Markov decision process (MDP) with average cost over an infinite time horizon. We prove the existence of a deterministic and stationary policy for the problem. We also find that the optimal policy has a consistent behavior and threshold type structure. A numerical example is provided to illustrate our main results.

Item Type:	Article
Additional Information:	This paper was presented at IFAC 2017 World Congress - The 20th World Congress of the International Federation of Automatic Control, 9-14 Jul 2017, Toulouse, France.
Keywords:	Sensor scheduling; Markov decision process; packet length; threshold policy;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	11895
Identification Number:	https://doi.org/10.1016/j.ifacol.2017.08.2283
Depositing User:	Subhrakanti Dey
Date Deposited:	28 Nov 2019 11:56
Journal or Publication Title:	IFAC-PapersOnLine
Publisher:	Elsevier
Refereed:	Yes
URI:	Publisher Organisation
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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