Programming sensor networks using abstract regions

Abstract

Wireless sensor networks are attracting increased interest for a wide range of applications, such as environmental monitoring and vehicle tracking. However, developing sensor network applications is notoriously difficult, due to extreme resource limitations of nodes, the unreliability of radio communication, and the necessity of low power operation. Our goal is to simplify application design by providing a set of programming primitives for sensor networks that abstract the details of low-level communication, data sharing, and collective operations. We present abstract regions, a family of spatial operators that capture local communication within regions of the network, which may be defined in terms of radio connectivity, geographic location, or other properties of nodes. Regions provide interfaces for identifying neighboring nodes, sharing data among neighbors, and performing efficient reductions on shared variables. In addition, abstract regions expose the trade-off between the accuracy and resource usage of communication operations. Applications can adapt to changing network conditions by tuning the energy and bandwidth usage of the underlying communication substrate. We present the implementation of abstract regions in the TinyOS programming environment, as well as results demonstrating their use for building adaptive sensor network applications.