WSN Platforms

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Currently there is no common WSN platform. Some designs such as Berkeley Motes and their clones have broader user and developer communities. However, many research labs and commercial companies prefer to develop and produce their own devices. Since there is no true killer application for WSNs that would drive the costs down, it is often more convenient and even less expensive to build your own WSN devices than to buy commercially available ones -- see Make your own Sensor Network device for details.

Miniaturization, another challenge for the WSN design, is expected to follow from recent and future progress in the fields of MEMS and NEMS. Some of the existing WSN platforms are given below. Most of the device designs are still in research stage.

General list

Jean Paul BerrĂ­os has put together a nice series of photos of WSN platforms.

Standard wireless protocols

See Radio Transceivers.

See Wikipedia: "Comparison of wireless data standards".


Energy is the scarcest resource of WSN nodes, and it determines the lifetime of WSNs. WSNs are meant to be deployed in large numbers in various environments, including remote and hostile regions, with ad-hoc communications as key. For this reason, algorithms and protocols need to address the following issues:

  • Lifetime maximization
  • Robustness and fault tolerance
  • Self-configuration

Amongst the hot topics in WSN software, the following can also be pointed out:

  • Security
  • Mobility (when sensor nodes or base stations are moving)
  • Middleware: the design of middle-level primitives between the software and the hardware

Middleware and Operating Systems

There is a need and considerable research efforts currently invested in the design of middleware for WSN's. There are various research efforts in developing middleware for wireless sensor networks.

  • AutoSec (Automatic Service Composition, in development at University of California, Irvine)
  • Bertha (OS underlying the Pushpin Computing platform)
  • BTnut Nut/OS (OS for the BTnodes,
  • COMiS (part of TinyMaCLaS project,
  • Contiki
  • CORMOS: A Communication Oriented Runtime System for Sensor Networks
  • DSWare
  • eCos
  • Enviro-Track
  • Global Sensor Networks;GSN (Application Oriented Middleware for sensor networks)[3].
  • Impala
  • jWebDust - Application Environment
  • LiteOS
  • MagnetOS
  • MANTIS (MultimodAl NeTworks In-situ Sensors)
  • MiLAN
  • Netwiser - A Network IDE with a portable middleware framework
  • SenOS
  • SensorWare
  • SINA
  • SOS
  • TinyDB
  • TinyGALS
  • TinyOS
  • t-Kernel
  • VIP Bridge- Integrate Different Sensor Networks

Programming languages

Many WSN developers choose to program WSN devices in the microcontroller assembly or C. However, researchers are looking for a better, more convenient way of programming sensor network nodes. Several issues have to be addressed: implementing complex algorithms with limited hardware resources, managing computational parallelism, achieving flexibility and hardware independence of the software.

  • c@t (Computation at a point in space (@) Time )
  • DCL (Distributed Compositional Language)
  • galsC
  • nesC
  • Protothreads
  • SQTL


WSNs are composed of a large number of sensor nodes, therefore, an algorithm for a WSN is implicitly a distributed algorithm. In WSNs the scarcest resource is energy, and one of the most energy-expensive operation is data transmission. For this reason, algorithmic research in WSN mostly focuses on the study and design of energy aware algorithms for data transmission from the sensor nodes to the bases stations. Data transmission is usually multi-hop (from node to node, towards the base stations), due to the polynomial growth in the energy-cost of radio tranmission with respect to the tranmission distance.

The algorithmic approach to WSN differentiates itself from the protocol approach by the fact that the mathematical models used are more abstract, more general, but sometimes less realistic than the models used for protocol design.


There are platforms specifically designed to simulate Wireless Sensor Networks, like TOSSIM, which is a part of TinyOS. Traditional network simulators like ns-2 have also been used. Apart from the above mentioned simulators, there are other simulators in the literature.

  • NetTopo - NetTopo is a research oriented open source sensor network simulator by Lei Shu
  • Emstar - An Environment for Developing Wireless Embedded Systems Software
  • DEFT NETZ - Complete Networking Suite encompassing IP Multicasting, Wireless, Cellular, Ethernet, ATM, FDDI, Token Ring Networking and Packet,Circuit, Burst Switching Technologies.
  • JiST / SWANS - a high-performance discrete event simulation engine (JiST) and a scalable wireless network simulator (SWANS) built atop the JiST platform.
  • GloMoSim - GLobal MObile Information systems SIMulator, a scalable simulation environment for wireless and wired network systems
  • SENS - a sensor environment and network simulator
  • J-Sim - a component-based, compositional simulation environment; formerly known as JavaSim
  • SWAN - Simulator for Wireless Ad-Hoc Networks, a C++ simulator for wireless ad hoc networks
  • SensorSim - a patch to the NS-2 simulator
  • Tython - a dynamic simulation environment for sensor networks
  • WiseNet
  • OpSeNet
  • OMNeT++ - a modular, easy-to-use discrete event simulator with many extensions for wireless network simulations
  • NesCT - package for simulating TinyOS NesC applications
  • Sidh
  • Avrora
  • Shawn - discrete event simulator designed with the simulation of large wireless sensor networks in mind
  • Prowler and JProwler
  • AlgoSenSim - an algorithm oriented sensor network simulator
  • Netwiser - A Network IDE with a built in simulator
  • WSNet & WSim - A development framework for WSN containing a network simulator and a hardware platform simulator.
  • COOJA - WSN Simulator/Emulator . Is part of Contiki, but can be used with any other WSN-OS that supports Sky or Mica Motes (It integrates ATEMU and mspsim).

Commercial sensor nodes

The following lists some of the sensor nodes on the market.

Data visualization

The data gathered from wireless sensor networks is usually saved in the form of numerical data in a central base station. There are many programs, like TosGUI and MonSense,GSN that facilitate the viewing of these large amounts of data. Additionally, the Open Geospatial Consortium (OGC) is specifying standards for interoperability interfaces and metadata encodings that enable real time integration of heterogeneous sensor webs into the Internet, allowing any individual to monitor or control Wireless Sensor Networks through a Web Browser.

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