Adaptation and cross-layer issues in sensor networks

An intrinsic characteristic of current projects in the area of sensor networks is the heterogeneity of hardware and application requirements. In addition, the requirements of current applications are expected to change over time. This makes developing, deploying, and optimizing sensor network applications an extremely difficult task. In this paper, we present the architecture of TinyCubus, a flexible and adaptive cross-layer framework for TinyOS-based sensor networks that aims at providing the necessary infrastructure to cope with the complexity of such systems. TinyCubus consists of three parts: a data management framework that selects and adapts both system and data management components, a cross-layer framework that enables optimizations through cross-layer interactions, and a configuration engine that installs components dynamically. We show the feasibility of our architecture by describing and evaluating a code distribution algorithm that optimizes its behavior by using application knowledge about the sensor topology.