Resource optimisation in a wireless sensor network with guaranteed estimator performance[Note 1]

Abstract

New control paradigms are needed for large networks of wireless sensors and actuators in order to efficiently utilise system resources. In this study, the authors consider the problem of discrete-time state estimation over a wireless sensor network. Given a tree that represents the sensor communications with the fusion centre, the authors derive the optimal estimation algorithm at the fusion centre, and provide a closedform expression for the steady-state error covariance matrix. They then present a tree reconfiguration algorithm that produces a sensor tree that has low overall energy consumption and guarantees a desired level of estimation quality at the fusion centre. The authors further propose a sensor tree construction and scheduling algorithm that leads to a longer network lifetime than the tree reconfiguration algorithm. Examples are provided throughout the paper to demonstrate the algorithms and theory developed. * Some preliminary results [2] of this study were presented by the same authors (excluding the second author) at the 46th IEEE Conference on Decision and Control at New Orleans, 2007.

Object Tracking in Wireless Sensor Networks: Challenges and Solutions

“…A major shortcoming of this method is that sensors must be activated all the time which may lead to the depletion of their batteries. Shi et al (2010), the authors proposed an algorithm that constructs a tree of sensors with minimum energy and desirable level of quality at the fusion center. After tree initialization, the algorithm keeps adjusting and reconfiguring the tree in a way that reduces the energy consumption and improves the estimation quality.…”

On Energy Efficiency in Collaborative Target Tracking in Wireless Sensor Network: A Review

“…a tree) that satisfies state estimation constraints. This problem is addressed in [29] where it is shown that choosing the tree with minimum energy consumption is very difficult. Thereby, the authors propose a tree reconfiguration algorithm composed of three procedures: (1) a recursive tree initialization procedure that uses the minimum power transmission to establish connections of each node with its immediate neighbors, (2) a switching tree topology procedure that is triggered when the desired quality is not achieved.…”

“…Moreover, it is also shown in [29] that minimizing the overall energy consumption may not lead to maximizing the network lifetime. Thus, a tree scheduling algorithm that choose M trees from N N −2 possible trees is necessary 1 .…”

Stability of State Estimation over Sensor Networks with Markovian Fading Channels*

“…Remark 3. A key difference of our approach when compared to that in Shi et al (2010);Shi (2009), is that we consider packet dropouts. Thus, the estimation error covariance matrix will not be stationary.…”

“…Several interesting approaches have been reported for state estimation of linear time-invariant (LTI) systems via wireless sensor networks. For example, the works Shi et al (2010) and Shi (2009) focus on delay issues in a multiple-sensor network with no dropouts, whereas Gupta et al (2009) studies the effect of dropouts within an architecture with…”