http://www.cnr.it/ontology/cnr/individuo/prodotto/ID64080
Energy Management in Sensor Networks for Environmental Monitoring (Articolo in rivista)
- Type
- Label
- Energy Management in Sensor Networks for Environmental Monitoring (Articolo in rivista) (literal)
- Anno
- 2007-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.3383/es.1.1.2 (literal)
- Alternative label
[1] Anastasi G., [1] Di Francesco M., [2] Conti M., [2] Gregori E., [2] Passarella A. (2007)
Energy Management in Sensor Networks for Environmental Monitoring
in Environmental Semeiotics journal
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- [1] Anastasi G., [1] Di Francesco M., [2] Conti M., [2] Gregori E., [2] Passarella A. (literal)
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- Pagina fine
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- Codice Puma: cnr.iit/2007-A0-005 (literal)
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- Rivista
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- [1] Università di Pisa, Dipartimento di Ingeneria Informatica, Pisa, Italy; [2] IIT-CNR, Pisa, Italy (literal)
- Titolo
- Energy Management in Sensor Networks for Environmental Monitoring (literal)
- Abstract
- A wireless sensor networks consists of a large number of sensor nodes deployed over a geographical area for monitoring physical phenomena (e.g., temperature, humidity, vibrations, seismic events, etc.). The set of potential applications of sensor networks is extremely large. However, environmental monitoring - including seismic and geological monitoring - represents a class of applications that can particularly benefit from sensor networks. Long-term data collection required by such applications asks for long network lifetimes (in the order of months or even years). Since node recharge is typically impossible or expensive, energy is a very critical issue in the sensor network design. In this paper we discuss energy management schemes for sensor networks, and propose an adaptive (and low-latency) energy management scheme for multi-hop (IEEE 802.15.4) sensor networks. We show by simulation that the solution proposed here is able to dynamically adapt to variations in the sensor network configuration and traffic patterns. Thus, it allows substantial energy savings. (literal)
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