Sensor Network Platforms and Tools

We discussed various aspects of sensor networks, including sensing and estimation, networking, infrastructure services, sensor tasking, and data storage and query. A real-world sensor network application most likely has to incorporate all these elements, subject to energy, bandwidth, computation, storage, and real-time constraints. This makes sensor network application development quite different from traditional distributed system development or database programming. With ad hoc deployment and frequently changing network topology, a sensor network application can hardly assume an always-on infrastructure that provides reliable services such as optimal routing, global directories, or service discovery.

There are two types of programming for sensor networks, those carried out by end users and those performed by application developers. An end user may view a sensor network as a pool of data and interact with the network via queries. Just as with query languages for database systems like SQL, a good sensor network programming language should be expressive enough to encode application logic at a high level of abstraction, and at the same time be structured enough to allow efficient execution on the distributed platform. Ideally, the end users should be shielded away from details of how sensors are organized and how nodes communicate.

On the other hand, an application developer must provide end users of a sensor network with the capabilities of data acquisition, processing, and storage. Unlike general distributed or database systems, collaborative signal and information processing (CSIP) software comprises reactive, concurrent, distributed programs running on ad hoc, resource-constrained, unreliable computation and communication platforms. Developers at this level have to deal with all kinds of uncertainty in the real world. For example, signals are noisy, events can happen at the same time, communication and computation take time, communications may be unreliable, battery life is limited, and so on. Moreover, because of the amount of domain knowledge required, application developers are typically signal and information processing specialists, rather than operating systems and networking experts. How to provide appropriate programming abstractions to these application writers is a key challenge for sensor network software development. In this chapter, we focus on software design issues to support this type of programming.

To make our discussion of these software issues concrete, we first give an overview of a few representative sensor node hardware platforms. We present the challenges of sensor network programming due to the massively concurrent interaction with the physical world. TinyOS for Berkeley motes and two types of nodecentric programming interfaces: an imperative language, nesC, and a dataflow-style language, TinyGALS. Node-centric designs are typically supported by node-level simulators such as ns-2 and TOSSIM. State-centric programming is a step toward programming beyond individual nodes. It gives programmers platform support for thinking in high-level abstractions, such as the state of the phenomena of interest over space and time.

Source of Information : Elsevier Wireless Networking Complete 2010