This document discusses power management techniques for sensor networks. It notes that sensor nodes are battery-powered and must operate for months to years on limited power. It describes the key components of sensor nodes that consume power, including the microcontroller, radio, sensors, and DC-DC converter. The document outlines various power management approaches that can optimize energy usage at the node, network, and protocol levels, such as putting components into low-power sleep modes, efficient routing protocols, and energy-aware software. The goal is to significantly extend the lifetime of battery-powered sensor networks.
2. Need for Power Management
1. Sensor nodes are battery driven and they
must have a lifetime on the order of months to
years.
2. Battery replacement is not an option for
networks with thousands of physically
embedded nodes.
3. In some cases, these networks may be
required to operate solely on energy
scavenged from the environment through
seismic, photovoltaic, or thermal conversion.
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4. The wireless sensor node is node is comprised of
four subsystems:
i) a computing subsystem consisting of a
microprocessor or micro controller,
ii) a communication subsystem consisting of a
short range radio for wireless communication,
iii) a sensing subsystem that links the node to
the physical world and consists of a group of
sensors and actuators, and
iv) a power supply subsystem, which houses the
battery and the dc-dc converter, and powers
the rest of the node.
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5. Microcontroller Unit
1. MCUs usually support various operating
modes, including Active, Idle, and Sleep
modes, for power management.
2. However, transitioning between operating
modes involves a power and latency
overhead.
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6. Radio
In general, radios can operate in four distinct
modes of operation: Transmit, Receive, Idle, and
Sleep.
An important observation in the case of most
radios is that operating in Idle mode results in
significantly high power consumption, almost
equal to the power consumed in the Receive
mode.
As that as the radio’s operating mode changes,
the transmit activity in the radio electronics
causes a significant amount of power consumed.
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7. Sensors
Sources of power consumption in a sensor
1. signal sampling and conversion of physical
signals to electrical ones
2. signal conditioning
3. analog-to-digital conversion
In general, however, passive sensors such as
temperature,consume negligible power relative to
other components of sensor node.
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8. Battery Issues
The operation of batteries depends on many factors like
1. battery dimensions,
2. type of electrode material used
Unfortunately, depending on the battery type (lithium ion,
NiMH, NiCd, alkaline, etc.), the minimum required current
consumption of sensor nodes often exceeds the rated
current capacity, leading to suboptimal battery lifetime.
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9. DC-DC CONVERTER
The efficiency factor associated with the converter plays a
big role in determining battery lifetime.
A low efficiency factor leads to significant energy loss in
the converter, reducing the amount of energy available to
other sensor node components.
Also, the voltage level across the battery terminals
constantly decreases as it gets discharged.
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10. Energy-Aware Software
Sensor network lifetime can be significantly enhanced if
the system software, including the operating system (OS),
application layer, and network protocols, are all designed
to be energy aware.
Network-Wide Energy
Optimization
The network as a whole should be energy aware, for
which the network-level global decisions should be energy
aware.
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11. Traffic Distribution
The protocols that provide an energy efficient multihop
route between source and destination does not always
maximize the network lifetime.
It is desirable to avoid routes through regions of the
network that are running low on energy resources, thus
preserving them for future.
It is, in general, undesirable to continuously forward traffic
via the same path, even though it minimizes the energy.
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12. Topology Management
In typical deployment scenarios, a dense network is
required to ensure adequate coverage of both the sensing
and multihop routing functionality, in addition to improving
network fault-tolerance.
Denser distributions of sensors lead to increasingly
tracking results but it reduces network lifetime.
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13. Conclusion
We discussed several energy optimization and
management techniques at node, link, and network level,
which can lead to significant enhancement in sensor
network lifetime.
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14. References:
POWER MANAGEMENT IN WIRELESS SENSOR
NETWORK
WITH HIGH CONSUMING SENSOR, Vana Jelicic IEEE
PAPER.
POWER SAVING AND ENERGY OPTIMIZATION
TECHNIQUES FOR WIRELESS SENSOR NETWORK,
Sandra Sendra, Jaime Lloret, Miguel García and José F.
Toledo IEEE PAPER.
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