Adaptive Dynamic Programming-Based Multi-Sensor Scheduling for Collaborative Target Tracking in Energy Harvesting Wireless Sensor Networks

Abstract

Collaborative target tracking is one of the most important applications of wireless sensor networks (WSNs), in which the network must rely on sensor scheduling to balance the tracking accuracy and energy consumption, due to the limited network resources for sensing, communication, and computation. With the recent development of energy acquisition technologies, the building of WSNs based on energy harvesting has become possible to overcome the limitation of battery energy in WSNs, where theoretically the lifetime of the network could be extended to infinite. However, energy-harvesting WSNs pose new technical challenges for collaborative target tracking on how to schedule sensors over the infinite horizon under the restriction on limited sensor energy harvesting capabilities. In this paper, we propose a novel adaptive dynamic programming (ADP)-based multi-sensor scheduling algorithm (ADP-MSS) for collaborative target tracking for energy-harvesting WSNs. ADP-MSS can schedule multiple sensors for each time step over an infinite horizon to achieve high tracking accuracy, based on the extended Kalman filter (EKF) for target state prediction and estimation. Theoretical analysis shows the optimality of ADP-MSS, and simulation results demonstrate its superior tracking accuracy compared with an ADP-based single-sensor scheduling scheme and a simulated-annealing based multi-sensor scheduling scheme.

A Low-Power Distributed Visual Sensor Network for Real-Time Barcode Localization and Identification

“…The distributed object-tracking method of [5] provides a triggering mechanism to schedule the states of a node, i.e., active or sleeping, by measuring if a node's informative content is beyond a threshold. Afterwards, Liu presents a multi-sensor scheduling approach based on the adaptive dynamic programming algorithm for cooperative target tracking [6]. However, the triggering mechanism in prior work [5,6] is often operated in a centralized way, fusing the information of multiple nodes in a sink node to predict the states.…”

“…Afterwards, Liu presents a multi-sensor scheduling approach based on the adaptive dynamic programming algorithm for cooperative target tracking [6]. However, the triggering mechanism in prior work [5,6] is often operated in a centralized way, fusing the information of multiple nodes in a sink node to predict the states. In this paper, we propose a dynamic triggering method that is deliberately designed to operate in a fully distributed manner.…”

“…where D i , i ∈ [1,6] is the ith digit, and ⊕ is the bitwise XOR operator. A digit pattern is the combination of four white and black bars, where the width of each bar is different.…”

“…The triggering mechanisms in current distributed VSNs are barely designed in a distributed fashion, such as the triggering method based on clustering informative observation [5]. In [6], the prediction of a node's state is performed via the fusion of states passed from multiple nodes to a sink node.…”

Advances and Opportunities in Passive Wake-Up Radios with Wireless Energy Harvesting for the Internet of Things Applications

“…On the other hand, many other authors have reviewed the MAC protocols for the wake-up radios [27,28,29,30], with only a few considering its combination with the energy harvesting system [31,32,33]. Some surveys consider the receiver only [17,34], while others [35], made a comparison of some of the wake-up radio schemes.…”