PRIDE: A Data Abstraction Layer for Large-Scale 2-tier Sensor Networks

Abstract

It is a challenging task to provide timely access to global data from sensors in large-scale sensor network applications. Current data storage architectures for sensor networks have to make trade-offs between timeliness and scalability. PRIDE is a data abstraction layer for 2-tier sensor networks, which enables timely access to global data from the sensor tier to all participating nodes in the upper storage tier. The design of PRIDE is heavily influenced by collaborative real-time applications such as search-and-rescue tasks for high-rise building fires, in which multiple devices have to collect and manage data streams from massive sensors in cooperation. PRIDE achieves scalability, timeliness, and flexibility simultaneously for such applications by combining a model-driven full replication scheme and adaptive data quality control mechanism in the storage-tier. We show the viability of the proposed solution by implementing and evaluating it on a large-scale 2-tier sensor network testbed. The experiment results show that the model-driven replication provides the benefit of full replication in a scalable and controlled manner.