1. Seminar On
Low Energy Efficient Wireless
Sensor Network
PRESENTED BY-DEEPAK KUMAR DHAL
REGD. NO-0901304038
ELECTRONICS AND COMMUNICATION ENGINEERING
GANDHI INSTITUTE OF TECHNOLOGY AND MANAGEMENT
NOVEMBER 2012
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2. CONTENT
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What is WSN?
Power consumption in WSN
Sources of energy waste
General approaches to energy saving
MAC protocol for WSN
Conclusion
Reference
3. What is WSN?
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A wireless sensor network is a collection of nodes
“sensors” organized into a cooperative network.
Wireless sensor network consists of sensor nodes
deployed over a geographical area for monitoring
physical phenomena like temperature, humidity,
vibrations, seismic events, and so on.
SENSOR NODES COMPONENTS
•Sensing Subsystem
•Processing Subsystem
•Wireless communication
subsystem
•Power source
4. Power consumption in WSNs
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The power issue in the wireless sensor network is
one of the biggest challenges, because the sensor
has a limited source of power which is also hard to
replace or recharge “e.g. sensors in the battle field,
sensors in a large forest … etc”.
Why limited source of power?
Inexpensive nature.
Limited size and weight.
Redundant nature.
5. Major Sources of Energy Waste in WSNs
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1. Useful power consumption:
Transmitting or receiving data.
Processing query requests.
Forwarding queries and data to the neighbors.
2. Wasteful power consumption:
Idle listening to the channel “waiting for possible traffic”.
Retransmitting because of collisions “e.g. two packets arrived at
the same time at the same sensor”.
Overhearing “when a sensor received a packet doesn’t belong to
it”.
Generating and handling control packets.
Over-emitting “when a sensor received a packet while it is not
rea
6. GENERAL APPROACHES TO
ENERGY SAVING
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Duty Cycling
Data Driven
Duty cycle
Duty cycle is defined as the fraction of time nodes which
are active during their lifetime.
Data Driven
Data driven approaches can be used to improve the energy
efficiency even more.
7. DUTY CYCLING
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It can be achieved through two different approaches:
it is possible to exploit node redundancy which is typical in sensor
networks and adaptively select only a minimum subset of nodes to
remain active for maintaining connectivity.
Nodes that are not currently needed for ensuring connectivity can go
to sleep and save energy. SENSOR
MODES
TRANSMISSION RECEPTION IDLE SLEEP
WAKE SLEEP
UP
Goal: reduce the time where the sensor is being idle.
Drawback: Additional delay because of waiting for the next-hop node to
wake up
8. 8
ON-DEMAND PROTOCOL
The basic idea is that a node should wake up only when another node
wants to communicate with it.
The main problem associated with on-demand schemes is how to
inform the sleeping node that some other nodes are willing to
communicate with it.
SCHEDULED RENDEZVOUS APPROACH
The basic idea behind scheduled rendezvous schemes is that each
node should wake up at the same time as its neighbours.
Typically, nodes wake up according to a wakeup schedule and remain
active for a short time interval to communicate with their
neighbours. Then, they go to sleep until the next rendezvous time.
9. MAC PROTOCOL FOR WSN
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MAC ( medium
access control)
Contension Hybrid
TDMA based
based
S(sensor)-
MAC
T(time out)-
MAC
μ (energy- DEE(dynami
c)-MAC
Z(zebra)-
MAC
A(advertisem
ent)-MAC
efficient)-MAC
U(utilization
SPARE-MAC
)-MAC
10. S-MAC
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Stand for:
Sensors Medium Access Control.
Strategy:
All node follow a periodic sleep/wake cycle, When a node is idle, it is more likely to
be asleep instead of continuously listening to the channel. S-MAC reduces the listen
time by letting the node go into periodic sleep mode.
Advantages:
Periodic Listen.
Collision Avoidance.
Overhearing Avoidance.
Message passing.
Disadvantages:
S-MAC fixed duty cycle i.e. active time is fixed
• if message rate is less energy is still wasted in idle-listening.
11. T-MAC
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Stand for:
Timeout Medium Access Control.
Strategy:
It adaptively adjusts the sleep and wake periods based on the estimated
traffic flow.
Advantage
Times out on hearing nothing.
Disadvantage
Early sleeping problem
i.e. node goes to sleep when a
neighbor still has message
for it.
12. U-MAC
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Stand for
Utilization Medium Access Control
Strategy
U-MAC is based on the S-MAC protocol and provides three
main improvements on SMAC:
various duty cycles, utilization based tuning of duty-cycle,
and selective sleeping after transmission.
13. μ- MAC
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Stand for
Energy-Efficient Medium Access Control
Strategy
μ-MAC assumes a single time slotted channel as shown in Figure.
Protocol operation alternates between a contention and a contention-
free period.
The contention period is used to build a network topology and to
initialize transmission sub channels.
14. DEE-MAC
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Stand for
Dynamic Energy Efficient Medium Access Control
Strategy
DEE-MAC is an approach to reduce energy consumption,
which lets the idle listening nodes go into sleep using synchronization
performed at the cluster head
DEE-MAC operation comprise of two phase:
1) Cluster formation phase
2) Transmission phase
15. SPARE-MAC
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Stand for
Slot Periodic Assignment for Reception Medium Access Control
Strategy
save energy through limiting the impact of idle listening and traffic overhearing.
It utilizes a distributed scheduling solution, which assigns specific time slots to
each sensor node for reception.
16. Z-MAC
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Stand for
Zebra Medium Access Control
Strategy
guaranteed access to its owner slot (TDMA style)
a contention-based access to other slots (CSMA style)
Advantage
• collisions and energy consumptions are reduced.
17. A-MAC
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Stands for
Advertisement-based Medium Access Control
Strategy
node is active only when it is the sender or the receiver, during other time it
just goes to sleep.
Advantage
energy waste is avoided on overhearing and idle listening.
18. Data Driven Approach
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Data-driven approaches can be used to improve the energy efficiency even more.
Data-driven approaches can be divided to data reduction schemes address the
case of unneeded samples, while energy-efficient data acquisition schemes are
mainly aimed at reducing the energy spent by the sensing subsystem.
Data reduction can be divided two parts
1) in-network processing
2) Dataprediction
In-network processing consists in performing data aggregation (e.g., computing
average of some values) at intermediate nodes between the sources and the sink.
In this way, the amount of data is reduced while traversing the network towards
the sink.
Data prediction consists in building an abstraction of a sensed phenomenon
19. CONCLUSION
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Energy is one of the most critical resources for WSNs. Extensive
research has been conducted to address these limitations by developing
schemes that can improve resource efficiency.
In this paper, we have summarized some research results which have
been presented in the literature on energy saving methods in sensor
networks.
Although many of these energy saving techniques look promising,
there are still many challenges that need to be solved in the sensor
networks.
20. REFERENCE
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Energy Saving in Wireless Sensor Networks, Zahra Rezaei, Shima
Mobininejad, Department of Computer Engineering Islamic Azad
University, Arak Branch , Arak , Iran.
I.Demirkol,C.Ersoy,F.Alagöz, "MAC Protocols for Wireless Sensor
Networks: A Survey", IEEE Communications Magazine.
A.Bachir, Mischa Dohler,T.Watteyne,K.Leung, "MAC Essentials for
Wireless Sensor Networks", IEEE COMMUNICATIONS SURVEYS
& TUTORIALS.