On the Feasibility of Distributed Sampling Rate Adaptation in Heterogeneous and Collaborative Wireless Sensor Networks

In this paper we develop a general framework for multi-sensor, heterogeneous sensing in collaborative wireless sensor networks (WSNs) that can be used in a variety of large scale monitoring applications. In order to achieve better tolerance against unstable wireless links and nodes with inadequate battery, it is important to consider distributed approaches for sampling rate adaptation. We show that the fully distributed mechanisms suffer from high convergence time, which make them difficult to implement in large-scale WSNs. To overcome this limitation, we next propose two alternate approaches. We perform extensive simulations to compare these schemes and argue their scalability and applicability in real world monitoring scenarios.