Energy Consumption Trade-offs in Power Constrained Networks

Wireless Sensor Networks are a valuable technology to
support many applications in different areas.
Participating nodes in these networks are inherently
resource constrained, since they have limited
processing capabilities, storage, communications
speed and bandwidth, and mainly they usually have
limited power supply. One of the most complex
scenarios is a Visual Sensor Networks (VSN), which
include cameras as sensing devices. This kind of
sensor networks has different processing and network
requirements. These requirements are associated with
the application of the visual sensor network
performance (e.g. image/video acquisition frequency,
processing and transmission), but they have a huge
impact on the node lifetime. Energy consumption
trade-offs in power constrained networks in general,
and in visual sensor networks in particular, are
addressed in this work.

Autorentext

Cintia Borges Margi is currently Assistant Professor atUniversity of Sao Paulo, Brazil. She received her PhD in ComputerEngineering from University of California at Santa Cruz in June2006. Her research interests in computer engineering includewired and wireless computer networks, wireless sensor networks,and energy consumption issues.

Klappentext

Wireless Sensor Networks are a valuable technology tosupport many applications in different areas.Participating nodes in these networks are inherentlyresource constrained, since they have limitedprocessing capabilities, storage, communicationsspeed and bandwidth, and mainly they usually havelimited power supply. One of the most complexscenarios is a Visual Sensor Networks (VSN), whichinclude cameras as sensing devices. This kind ofsensor networks has different processing and networkrequirements. These requirements are associated withthe application of the visual sensor networkperformance (e.g. image/video acquisition frequency,processing and transmission), but they have a hugeimpact on the node lifetime. Energy consumptiontrade-offs in power constrained networks in general,and in visual sensor networks in particular, areaddressed in this work.