A State-Based Programming Model for Wireless Sensor Networks

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viii Contents 8.2.4 Program State Machines (PSM), SpecCharts . . . . . . . . . 144 8.2.5 Communicating FSMs: CRSM and CFSM . . . . . . . . . . 145 8.2.6 Esterel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 8.2.7 Functions driven by state machines (FunState) . . . . . . . 146 8.3 Sensor-Node Programming Frameworks . . . . . . . . . . . . . . 146 8.3.1 TinyOS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 8.3.2 Contiki . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 8.3.3 Protothreads . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 8.3.4 SenOS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 9 Conclusions and Future Work 151 9.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 9.2 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 9.2.1 Problem Analysis: Shortcomings of Events . . . . . . . . . 152 9.2.2 Solution Approach: State-based Programming . . . . . . . 152 9.2.3 Prototypical Implementation . . . . . . . . . . . . . . . . . 153 9.2.4 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 9.3 Limitations and Future Work . . . . . . . . . . . . . . . . . . . . . 153 9.3.1 Language and Program Representation . . . . . . . . . . . 154 9.3.2 Real-Time Aspects of OSM . . . . . . . . . . . . . . . . . . 155 9.3.3 Memory Issues . . . . . . . . . . . . . . . . . . . . . . . . . 155 9.4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . 156 A OSM Code Generation 157 A.1 OSM Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 A.2 Variable Mapping (C include file) . . . . . . . . . . . . . . . . . . . 159 A.3 Control Flow Mapping–Stage One (Esterel) . . . . . . . . . . . . . 161 A.4 Control Flow Mapping–Stage Two (C) . . . . . . . . . . . . . . . . 164 A.4.1 Output of the Esterel Compiler . . . . . . . . . . . . . . . . 164 A.4.2 Esterel-Compiler Output Optimized for Memory Efficiency 169 A.5 Compilation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 A.5.1 Example Compilation Run . . . . . . . . . . . . . . . . . . 173 A.5.2 Makefile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 B Implementations of the EnviroTrack Group Management 175 B.1 NesC Implementation . . . . . . . . . . . . . . . . . . . . . . . . . 175 B.2 OSM Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . 180 Bibliography 181
1 Introduction 1.1 Background Over the past decades, advances in sensor technology, miniaturization and lowcost, low-power chip design have led to the development of wireless sensor nodes: small, inexpensive, and programmable devices that combine computing, sensing, short-range wireless communication, and an autonomous power supply. This development has inspired the vision of wireless sensor networks— wireless networks of sensor nodes that can be deployed in the environment at the large scale to unobtrusively monitor phenomena of the real world. There is a wide range of applications envisioned for such wireless sensor networks, including precision agriculture, monitoring of fragile goods and building structures, monitoring the habitat of endangered species and the animals themselves, emergency response, environmental and micro-climate monitoring, logistics, and military surveillance. The most popular programming model for developing sensor-network applications today is the event-driven model. Several programming frameworks based on that model exist, for example, the BTnode system software [21], Contiki [37], the TinyOS system software [59] and nesC programming language [45], SOS [52] and Maté [79]. The event-driven model is based on two main abstractions: events and actions. Events in the context of event-driven programming can be considered abstractions of real-world events. Events are typically typed to distinguish different event classes and may contain parameters, for example, to carry associated event data. At runtime, the occurrence of an event can trigger the execution of a computational action. Typically, there is a one-to-one association between event types and actions. Then, an event-driven program consists of as many actions as there are event types. Actions are typically implemented as functions of a sequential programming language. They always run to completion without being interrupted by other actions. In order not to monopolize the CPU for any significant time, actions need to be non-blocking. Therefore, at any point in the control flow where an operation needs to wait for some event to occur (e.g., a reply message or acknowledgment), the operation must be split into two parts: a non-blocking operation request and an asynchronous completion event. The completion event then triggers another action, which continues the operation. One of the main strengths of the event-driven model is that its support in the underlying system software incurs very little memory and runtime overhead. Also, the event-driven model is simple, yet intuitively captures the reactive nature of sensor-network applications. In contrast, the multi-threaded programming model, another programming approach that has been applied to wireless sensor networks, is typically considered to incur too much memory and computational overhead (mainly because of per-thread stacks and context switches).
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A State-Based Programming Model for Wireless Sensor Networks

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