Resource-Aware Dynamic Clustering Utilizing State Estimation in Visual Sensor Networks

Abstract

Generally, resource-awareness plays a key role in wireless sensor networks due the limited capabilities in processing, storage and communication. In this paper we present a resource- aware cooperative state estimation facilitated by a dynamic cluster-based protocol in a visual sensor network (VSN). The VSN consists of smart cameras, which process and analyze the captured data locally. We apply a state estimation algorithm to improve the tracking results of the cameras. To design a lightweight protocol, the final aggregation of the observations and state estimation are only performed by the cluster head. Our protocol is based on a market-based approach in which the cluster head is elected based on the available resources and a visibility parameter of the object gained by the cluster members. We show in simulations that our approach reduces the costs for state estimation and communication as compared to a fully distributed approach. As resource-awareness is the focus of the clusterbased protocol we can accept a slight degradation of the accuracy on the object’s state estimation by a standard deviation of about 1.48 length units to the available ground truth