Wireless Sensor Network (WSN) Mi nalysis Processing Sensor field 1 Sensor Field 2 Base station Sensor Multiple sensors (often hundreds or thousands) form a network to cooperatively monitor large or complex physical environments Acquired information is wirelessly communicated to a base station (BS), which propagates the information to remote devices for storage, analysis, and processing
Wireless Sensor Network (WSN) • Multiple sensors (often hundreds or thousands) form a network to cooperatively monitor large or complex physical environments • Acquired information is wirelessly communicated to a base station (BS), which propagates the information to remote devices for storage, analysis, and processing Base Station Sensor Processing Sensor Field 1 Sensor Field 2 Internet Mining Analysis Storage
Networked vs Individual sensors Extended range of sensing Cover a wider area of operation Redundancy Multiple nodes close to each other increase fault tolerance Improved accuracy Sensor nodes collaborate and com bine their data to increase the accuracy of sensed data Extended functionality Sensor nodes can not only perform sensing functionality but also provide forwarding servIce
Networked vs. Individual Sensors • Extended range of sensing: • Cover a wider area of operation • Redundancy: • Multiple nodes close to each other increase fault tolerance • Improved accuracy: • Sensor nodes collaborate and combine their data to increase the accuracy of sensed data • Extended functionality: • Sensor nodes can not only perform sensing functionality, but also provide forwarding service
History of wireless Sensor Networks ● DARPA: Distributed Sensor Nets Workshop (1978) Distributed Sensor Networks(DSN) program(early 1980s Sensor Information Technology(SenslT) program UCLA and Rockwell Science Center Wireless Integrated Network Sensors (WINS) Low Power Wireless Integrated Microsensor(LWIM)(1996) UC-Berkeley Smart Dust project (1999) Concept of motes": extremely small sensor nodes Berkeley Wireless Research Center(BWRC) PicoRadio project (2000) MIT HAMPS(micro-Adaptive Multidomain Power-aware Sensors)(2005)
History of Wireless Sensor Networks • DARPA: • Distributed Sensor Nets Workshop (1978) • Distributed Sensor Networks (DSN) program (early 1980s) • Sensor Information Technology (SensIT) program • UCLA and Rockwell Science Center • Wireless Integrated Network Sensors (WINS) • Low Power Wireless Integrated Microsensor(LWIM) (1996) • UC-Berkeley • Smart Dust project (1999) • Concept of “motes”: extremely small sensor nodes • Berkeley Wireless Research Center (BWRC) • PicoRadio project (2000) • MIT • μAMPS (micro-Adaptive Multidomain Power-aware Sensors) (2005)
History of Wireless Sensor Networks Recent commercial efforts Crossbowwww.xbow.com) Sensoriawww.sensoria.com Worldsens (worldsens. citi. insa-lyon fr) DustNetworkswww.dustnetworks.com) EmberCorporation(www.ember.com)
History of Wireless Sensor Networks • Recent commercial efforts • Crossbow (www.xbow.com) • Sensoria (www.sensoria.com) • Worldsens (worldsens.citi.insa-lyon.fr) • Dust Networks (www.dustnetworks.com) • Ember Corporation (www.ember.com)
WSN Communication Characteristics of typical WSN ow data rates(comparable to dial-up modems) Energy-constrained sensors IEEE 802. 11 family of standards Most widely used Wlan protocols for wireless communications in general Can be found in early sensor networks or sensors networks without stringent energy constraints IEEE 802. 15. 4 is an example for a protocol that has been designed specifically for short-range communications in WSNs ow data rates ow power consumption Widely used in academic and commercial WSN solutions
WSN Communication • Characteristics of typical WSN: • Low data rates (comparable to dial-up modems) • Energy-constrained sensors • IEEE 802.11 family of standards • Most widely used WLAN protocols for wireless communications in general • Can be found in early sensor networks or sensors networks without stringent energy constraints • IEEE 802.15.4 is an example for a protocol that has been designed specifically for short-range communications in WSNs • Low data rates • Low power consumption • Widely used in academic and commercial WSN solutions