State-Centric Programming for Sensor-Actuator Network Systems

D istributed embedded systems such as wireless sensor and actuator networks require new programming models and software tools to support the rapid design and prototyping of sensing and control applications. Unlike centralized platforms and web-based distributed systems, these distributed sensor-actuator network (DSAN) systems are characterized by a massive number of potentially failing nodes, limited energy and bandwidth resources, and the need to rapidly respond to sensor input. As application developers, we must fundamentally rethink the organization and programming of these deeply embedded systems. What is the appropriate mental model we can use to reason about the collective behaviors of a system when programming a distributed application so that the application is portable, scalable, and robust? What are the organizational principles for developers to build large applications by mixing and matching various ad hoc communication protocols while shielded from dealing with a multitude of communication events? How does the software architecture expose the underlying system constraints so that application developers can consider important performance trade-offs? This article describes a state-centric, agent-based design methodology to mediate between a system developer’s mental model of physical phenomena and the distributed execution of DSAN applications. Building on the ideas of data-centric networking,1 sensor databases,2 and proximity-based group formation,3 we introduce the notion of collaboration groups, which abstracts common patterns in application-specific communication and resource allocation. An application developer specifies computations as the creation, aggregation, and transformation of states, which naturally map to the vocabulary used by signal processing and control engineers. More specifically, programmers write applications as algorithms for state update and retrieval, with input supplied by dynamically created collaboration groups. As a result, programs written in the state-centric framework are more invariant to system configuration changes, making the resulting software more modular and portable across multiple platforms. Using a distributed tracking application with sensor networks, we’ll demonstrate how state-centric programming can raise the abstraction level for application developers.