Non-Bayesian Quickest Detection with Stochastic Sample Right Constraints

Abstract

In this paper, we study the design and analysis of optimal detection scheme for sensors that are deployed to monitor the change in the environment and are powered by the energy harvested from the environment. In this type of applications, detection delay is of paramount importance. We model this problem as quickest change detection problem with a stochastic energy constraint. In particular, a wireless sensor powered by renewable energy takes observations from a random sequence, whose distribution will change at a certain unknown time. Such a change implies events of interest. The energy in the sensor is consumed by taking observations and is replenished randomly. The sensor cannot take observations if there is no energy left in the battery. Our goal is to design a power allocation scheme and a detection strategy to minimize the worst case detection delay, which is the difference between the time when an alarm is raised and the time when the change occurs. Two types of average run length (ARL) constraint, namely an algorithm level ARL constraint and an system level ARL constraint, are considered. We propose a low complexity scheme in which the energy allocation rule is to spend energy to take observations as long as the battery is not empty and the detection scheme is the Cumulative Sum test. We show that this scheme is optimal for the formulation with the algorithm level ARL constraint and is asymptotically optimal for the formulations with the system level ARL constraint.

30 pages, 5 figures

References in corpus (2)

• Throughput Maximization for the Gaussian Relay Channel with Energy Harvesting Constraints
• State-of-the-Art in Sequential Change-Point Detection

Cited by in corpus (8)

• Age of Information Minimization for an Energy Harvesting Source with Updating Erasures: With and Without Feedback
• Quickest Change Detection in Adaptive Censoring Sensor Networks
• Optimal Status Update for Age of Information Minimization with an Energy Harvesting Source
• Bayesian Quickest Change Point Detection with Sampling Right Constraints
• Adaptive Transmission for Distributed Detection in Energy Harvesting Wireless Sensor Networks
• Quickest Change Detection with a Censoring Sensor in the Minimax Setting
• Asymptotic Performance Analysis of Non-Bayesian Quickest Change Detection with an Energy Harvesting Sensor
• Bayesian Methods for Multiple Change-Point Detection with Reduced Communication