Wireless sensor network

A Wireless Sensor Network (WSN) is a mesh network of small sensor nodes communicating among themselves using RF communication, and deployed in large scale (from tens to thousands) to sense the physical world. Unique characteristics of a WSN are:

• Small-scale sensor nodes
• Limited power they can harvest or store
• Harsh environmental conditions
• Node failures
• Mobility of nodes
• Dynamic network topology
• Communication failures
• Heterogeneity of nodes
• Large scale of deployment
• Unattended operation

Sensor nodes can be imagined as small computers, extremely basic in terms of their interfaces and their components. They usually consist of a processing unit with limited computational power and limited memory, sensors (including specific conditioning circuitry), a communication device (usually radio transceivers or alternatively optical), and a power source usually in the form of a battery. Other possible inclusions are energy harvesting modules, secondary ASICs, and possibly secondary communication devices (e.g. RS232 or USB).

The base stations are one or more distinguished components of the WSN with much more computational, energy and communication resources. They act as a gateway between sensor nodes and the end user.

Challenges

There are many challenges in implementing a WSN ranging from hardware, software, mechanical and even human-related. Keeping the power usage sufficiently low so that they operate for enough time involves careful power management and in some cases managing charging. Radio communication hardware has to be small enough while using a suitable network algorithm. A high bit-rate saves power by reducing communication time but in order to obtain a good range, especially in wet environments high-power hardware is often needed. These two tasks illustrate the careful balance and compromises that are needed in WSN designs.

Software and Hardware Platforms

Hardware

The main challenge is to produce low cost and tiny sensor nodes. With respect to these objectives, current sensor nodes are mainly prototypes. Miniaturization and low cost are understood to follow from recent and future progress in the fields of MEMS and NEMS. Some of the existing sensor nodes are given below. Some of the nodes are still in research stage.

• Mica Mote (http://www.tinyos.net/scoop/special/hardware/)
• WINS (Rock Well) Wireless Integrated Network Sensors)
• WINS (UCLA)
• Smart Dust (UC Berkeley)
• COTS Dust (UC Berkeley)
• Sensor Webs (JPL) (http://sensorwebs.jpl.nasa.gov/)
• EYES Project (http://eyes.eu.org)
• Cortex Project

Software

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

Operating Systems

• TinyOS
• Bertha (pushpin computing platform)
• SOS
• Contiki
• MANTIS ( MultimodAl NeTworks In-situ Sensors)
• MagnetOS
• jallad
• CORMOS : A Communication Oriented Runtime System for Sensor Networks
• Mate
• Accent : A communication oriented Network operating system kernel
• Chimes II
• SenOS
• EYES

Middleware

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. A nice survey of those efforts can be found here [1]. In general approaches can be classified into distributed database, mobile agents, and event-based [2].

• TinyDB
• COUGAR
• SINA
• SensorWare
• MiLAN
• Enviro-Track
• Impala
• TinyGALS
• DSWare
• AutoSec
• MagnetOS
• COMiS

Programming Languages

Programming the sensor nodes is difficult when compared to the normal computer systems. Resource constrainted nature of these nodes gives raise to new programming models.

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

Algorithms

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.

Protocols

Protocols for WSN need to address the specificities of the WSN nodes hardware. They are usually more "down to earth", compared to the algorithmic approach, and more directly implementable in real world WSN's.

Wireless Sensor Network Simulators

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

• Emstar - An Environment for Developing Wireless Embedded Systems Software
• 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 - (formerly known as JavaSim) is a component-based, compositional simulation environment
• SWAN - Simulator for Wireless Ad-Hoc Networks
• SensorSim - This is a patch to Ns-2 simulator
• Tython - A DYNAMIC SIMULATION ENVIRONMENT FOR SENSOR NETWORKS
• WiseNet
• ATEMU
• OpSeNet
• OMNeT++
• OPTNET
• Sidh
• Avrora
• Shawn - discrete event simulator designed with the simulation of large wireless sensor networks in mind

Applications of WSNs

The applications for WSNs are many and varied. They could be used in industry to monitor dangerous/hermetically-sealed environments. They could be deployed in wilderness areas, where they would remain for many years (monitoring some environmental variable) without the need to recharge/replace their power supplies. They could form a perimeter about a property and monitor the progression of intruders (passing information from one node to the next). There are a vast quantity of possible amount of uses for WSNs.

Typical applications of WSNs include monitoring, tracking, and controlling. Some of the specific applications are habitat monitoring, object tracking, nuclear reactor controlling, fire detection, traffic monitoring, etc. In a typical application, a WSN is scattered in a region where it is meant to collect data through its sensor nodes.

• Environmental monitoring
• Habitat monitoring
• Acoustic detection
• Seismic Detection
• Military surveillance
• Inventory tracking
• Medical monitoring
• Smart spaces

Area Monitoring

Area monitoring is a typical application of WSNs. In area monitoring, the WSN is deployed over a region where some phenomenon is to be monitored. As an example, a large quantity of sensor nodes could be deployed over a battlefield to detect enemy intrusion instead of using landmines. When the sensors detect the event being monitored (heat, pressure, sound, light, electro-magnetic field, vibration, etc), the event needs to be reported to one of the base stations, which can take appropriate action (e.g., send a message on the internet or to a satellite). Depending on the exact application, different objective functions will require different data-propagation strategies, depending on things such as need for real-time response, redundancy of the data (which can be tackled via data aggregation techniques), need for security, etc.

Commercial Sensor Nodes

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

• BTnodes (Polytechnical School of Zurich, Switzerland)
• Intel motes
• SPOT Small Programmable Object Technology (Sun microsystems).
• MICAz motes (Crossbow technology)
• TMote Sky

Standards

• ZigBee

Visualization of Wireless Sensor Networks Data

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, 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.

WSN Research Centers

Examples of major academic centers for research in wireless sensor networks are CITRIS at Berkeley and CENS at UCLA, in the USA and the NCCR MICS in Switzerland.

Center for Embedded Networked Sensing (CENS)

The Center for Embedded Networked Systems (CENS) at the University of California, Los Angeles, directed by Deborah Estrin, is also a leading research center with $40 million in core funding from the National Science Foundation [3].

Center for Information Technology Research in the Interest of Society (CITRIS)

The Center for Information Technology Research in the Interest of Society (CITRIS) at the University of California, Berkeley, currently directed by S. Shankar Sastry, is a $300 million multicampus research center that includes research and development of wireless sensor networks, and has used them to study microclimate variations in individual redwood trees [4].

National Center of Competence in Research on Mobile Information and Communication Systems (NCCR MICS)

The NCCR MICS was launched in 2001 and is currently in its second round. It involves research institutions, universities and corporate partners from all over Switzerland. It is performing research in mobile information and communication systems, with a strong emphasis on wireless sensor networks and novel self-organizing networks and information systems.

Tyndall National Institute (formerly NMRC)

The Microelectronic Applications Integration (MAI), sector of the Tyndall National Institute in Cork, Ireland, headed by Dr. Cian O'Mathuna, is currently involved in developing microsensing and microactuation devices for use in miniaturised wireless sensor networks. In particular the Ambient Technology Group is developing modular interchangeable hardware layers for use in many sensor network applications.

See also

• TinyOS
• Smartdust
• Mesh networking
• Sensor network
• Mobile ad-hoc network (MANETS)
• ZigBee
• TinyMaCLaS

Reference Books

• Wireless Sensor Networks, Cauligi S. Raghavendra (Editor), Krishna M. Sivalingam (Editor), Taieb Znati.
• Wireless Sensor Networks: Architectures and Protocols, Edgar H. Callaway, Jr. and Edgar H. Callaway, CRC Press, August 2003, 352 pages.
• Information Processing in Sensor Networks, Feng Zhao, and Leonidas J. Guibas (Eds).
• Handbook of sensor networks; algorithms and architectures, Edited by Ivan Stojmenovic, Wiley-Interscience, 2005, 531 pages.
• Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems, Mohammad Ilyas, Imad Mahgoub, CRC Press.
• Wireless Sensor Network A Systems Perspective, Nirupama Bulusu, Sanjay Jha, Artech House, Published July 2005, ISBN 1580538673
• Protocols and Architectures for Wireless Sensor Networks, Holger Karl, Andreas Willig, ISBN 0-470-09511-3, 526 pages, January 2006
• Adhoc and Sensor Networks Theory and Applications, Carlos de Morais Cordeiro (Philips Research North America, USA) & Dharma Prakash Agrawal (University of Cincinnati, USA), March 2006.
• Networking Wireless Sensors, Bhaskar Krishnamachari (University of Southern California), (ISBN-13: 9780521838474 | ISBN-10: 0521838479)
• Energy Scavenging for Wireless Sensor Networks: With Special Focus on Vibrations, Shad Roundy, Paul Kenneth Wright, Jan M. Rabaey, 232 pages, Kluwer Academic Publishers; (January 1, 2004), ISBN 1402076630.
• Distributed Sensor Networks", S. S. Iyengar, R. R. Brooks, Chapman & Hall/CRC; (October 22, 2004), ISBN 1584883839 .
• Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems, Mohammad Ilyas, Imad Mahgoub, 672 pages CRC Press; (July 16, 2004), ISBN 0849319684 .
• Algorithmic Aspects Of Wireless Sensor Networks (Lecture Notes in Computer Science)", Sotiris Nikoletseas, Jose Rolim, Springer-Verlag; (September 30, 2004), ISBN 3540224769 .
• Mobile, Wireless, and Sensor Networks : Technology, Applications, and Future Directions Rajeev Shorey, A. Ananda, Mun Choon Chan, Wei Tsang Ooi, ISBN 0-471-75558-3, 422 pages, March 2006 .

External links

• Overview of wireless sensor networks from the IEEE Computer Society.
• EnOcean EnOcean enables a wireless community of batteryless sensors to connect to just a few transceivers that need to be powered for continuous operation.
• Software Infrastructure for Wireless Sensor Networks.
• TECO Particle Web Site.
• BiSNET: Biologically-inspired architecture for Sensor NETworks Web Site.
• TinyMote Web Site.
• TinyOS community forum
• MoteIV Corporation
• FEUP WSN Group
• Wireless Sensor Networks Blog