Directions in Multi-Query Optimization for Sensor Networks

Abstract

The widespread dissemination of small-scale sensor nodes has sparked interest in a powerful new database abstraction for sensor networks: Clients “program” the sensors through queries in a high-level declarative language (such as a variant of SQL), and catalog management and query processing techniques abstract the user from the physical details of tasking the sensors. We call the resulting system a sensor data management system (SDMS). Sensor networks have important constraints on communication, computation and power consumption. Energy is the most valuable resource for unattended battery-powered nodes. Since radio communication consumes most of the available node power, our goal is to identify strategies that reduce network traffic. We give an overview of three distinct approaches to reducing the cost of processing aggregate queries in sensor networks: i) selection of suitable routes for collecting results of multiple queries, ii) data reduction techniques that exploit query commonalities and iii) a hybrid pull-push communication paradigm for query and result propagation. We pay particular attention to the third approach and present in detail an algorithm for finding a pull-push configuration that minimizes on expectation the network traffic. Experimental analysis shows that our algorithm offers significant energy savings.

The authors wish to thank Douglas Holzhauer and Zen Pryke from the Air Force Rome Labs for helpful discussions. This work is supported by NSF Grants CCR-0205452, IIS-0133481, and IIS-0330201, by the Cornell Information Assurance Institute, and by Lockheed Martin.