Result: Reliable and efficient programming abstractions for wireless sensor networks
University of California, Los Angeles, United States
CC BY 4.0
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Further Information
It is currently difficult to build practical and reliable programming systems out of distributed and resource-constrained sensor devices. The state of the art in today's sensomet programming is centered around a component-based language called nesC. nesC is a node-level language-a program is written for an individual node in the network-and nesC programs use the services of an operating system called TinyOS. We are pursuing an approach to programming sensor networks that significantly raises the level of abstraction over this practice. The critical change is one of perspective: rather than writing programs from the point of view of an individual node, programmers implement a central program that conceptually has access to the entire network. This approach pushes to the compiler the task of producing node-level programs that implement the desired behavior. We present the Pleiades programming language, its compiler, and its runtime. The Pleiades language extends the C language with constructs that allow programmers to name and access node-local state within the network and to specify simple forms of concurrent execution. The compiler and runtime system cooperate to implement Pleiades programs efficiently and reliably. First, the compiler employs a novel program analysis to translate Pleiades programs into message-efficient units of work implemented in nesC. The Pleiades runtime system orchestrates execution of these units, using TinyOS services, across a network of sensor nodes. Second, the compiler and runtime system employ novel locking, deadlock detection, and deadlock recovery algorithms that guarantee serializability in the face of concurrent execution. We illustrate the readability, reliability and efficiency benefits of the Pleiades language through detailed experiments, and demonstrate that the Pleiades implementation of a realistic application performs similar to a hand-coded nesC version that contains more than ten times as much code.