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Power Management and Power Consumption Optimization Techniques in Wireless Sensor Networks

A Wireless Sensor Network (WSN) is a distributed collection of resource
constrained tiny nodes capable of operating with minimal user attendance.
Due to their flexibility and low cost, WSNs have recently become widely
applied in traffic regulation, fire alarm in buildings, wild fire
monitoring, agriculture, health monitoring, building energy management,
and ecological monitoring. However, deployment of the WSNs in
difficult-to-access areas makes it difficult to replace the batteries - the
main power supply of a sensor node. It means that the power limitation of
the sensor nodes appreciably constraints their functionality and potential
applications. The use of harvesting components such as solar cells alone and
energy storage elements such as super capacitors and rechargeable batteries
is insufficient for the long-term sensor node operation. With this thesis
we are going to show that long-term operation could be achieved by adopting
a combination of hardware and software techniques along with energy
efficient WSN design. To demonstrate the hardware power management, an
energy scavenging module was designed, implemented and tested. This module
is able to handle both alternating current (AC) based and direct current
(DC) based ambient sources. The harvested energy is stored in two energy
buffers of different kind, and is delivered to the sensor node in accordance
with an efficient energy supply switching algorithm. The software part of
the thesis presents an analytical criterion to establish the value of the
synchronization period minimizing the average power dissipated by a WSN
node. Since the radio chip is usually the most power hungry component on a
board, this approach can help one to decrease the amount of power
consumption and prolong the lifetime of the entire WSN. The following part
of the thesis demonstrates a methodology for power consumption evaluation of
WSN. The methodology supports the Platform Based Design (PBD) paradigm,
providing power analysis for various sensor platforms by defining separate
abstraction layers for application, services, hardware and power supply
modules. Finally, we present three applications where we use the designed
hardware module and apply various power management strategies. In the first
application we apply the WSN paradigm to the entertainment area, and in
particular to the domain of Paintball. The second one refers to a wireless
sensor platform for monitoring of dangerous gases and early fire detection.
The platform operation is based on the pyrolysis product detection which
makes it possible to prevent fire before inflammation. The third application
is connected with medical research. This work describes the powering of
wireless brain-machine interfaces.

Identiferoai:union.ndltd.org:unitn.it/oai:iris.unitn.it:11572/367818
Date January 2009
CreatorsSomov, Andrey
ContributorsSomov, Andrey, Passerone, Roberto
PublisherUniversità degli studi di Trento, place:TRENTO
Source SetsUniversità di Trento
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/doctoralThesis
Rightsinfo:eu-repo/semantics/openAccess
Relationfirstpage:1, lastpage:135, numberofpages:135

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