Transcript A Distance-based Clustering Routing Protocol in Wireless

A Distance-based Clustering Routing
Protocol in Wireless Sensor Networks
LEACH-SC
Presented By
M. Jaffar Khan
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Abstract
• Classical LEACH protocol widely used until now because it has many
advantages in
– energy efficiency,
– data aggregation and so on…
• In this paper, based on the LEACH protocol, we propose a new
distance-based clustering routing protocol, LEACH-SC (LEACHselective cluster).
• In LEACH-SC, a new method is used to choose cluster heads, i.e.
– an ordinary node A will choose a cluster head which is the closest to
the center point between A and the sink.
• The simulation results show that compared with LEACH,
– LEACH-SC protocol can greatly reduce the overall network energy
consumption,
– balance the energy consumption among the sensors
– extend the lifetime of the network.
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I. INTRODUCTION
• In recent years, many routing protocols for WSNs have been proposed [16] which can be classified into four classes:
1.
clustering-based routing protocols,
•
2.
3.
4.
groups sensor nodes where each group of nodes has a cluster-head(CH) or a gateway.
data centric routing protocols,
geographic-based routing protocol
hybrid routing protocol.
• Many clustering-based routing protocols have been proposed such as
LEACH[3], LEACH-C[4], HEED[5], TEEN[6] etc.
– Among them, LEACH is the most popular hierarchical routing algorithm for
sensor networks.
[1] Ming Yu, Leung, K.K. “A dynamic clustering and energy efficient routing technique for sensor networks”. IEEE on Wireless
Communications, Vol: 6(8): pp3069-3079, August 2007,
[2] F. Bouabdallah, N. Bouabdallah and R. Boutaba. “Cross-Layer Design for Energy Conservation in Wireless Sensor Networks”. In IEEE
International Conference on Communications, 2009, June 2009, Accession Number: 10815184
[3] Wendi Rabiner Heinzelman et al.“Energy-Efficient Communication Protocol for Wireless Microsensor Networks”．n Proceeding of the
33rd Hawaii International Conference on System Sciences，January 2000,pp1-10
[4] Heinzelman WR. “Application-Specific protocol architectures for wireless networks [D].” Boston: MIT, Doctor thesis ,2000.
[5]Younis O, Fahmy S. “Heed: A hybrid, energy-efficient, distributed clustering approach for ad-hoc sensor networks”. IEEE Trans. on mobile
Computing, 2004,3(4), pp 660−669.
[6] Manjeshwar A, Grawal DP. “TEEN: A protocol for enhanced efficiency in wireless sensor networks”. In Proc. of the 15th Parallel and
Distributed Processing Symp. San Francisco: 2001. vol. 3, pp.30189a
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I. INTRODUCTION
• LEACH[3] is a self-organized, adaptive clustering protocol that uses
– randomization to distribute the energy load evenly among the sensors
in the network.
• The operation of LEACH is divided into rounds.
– Each round begins with a set-up phase when the clusters are
organized, followed by a steady-state phase
– In the set-up phase,
• there are cluster-head electing phase and the cluster formation phase.
• After the cluster-heads have been chosen, sensor nodes which are chosen as
cluster-heads broadcast an advertisement message to inform non-cluster
sensor nodes that the chosen sensor nodes are new cluster-heads. Then noncluster sensor nodes join the cluster with strongest signal strength.
– a steady-state phase
• when data are transferred from the nodes to the cluster head and on to the
BS.
[3] Wendi Rabiner Heinzelman et al.“Energy-Efficient Communication Protocol for
Wireless Microsensor Networks”．In Proceeding of the 33rd Hawaii International
Conference on System Sciences，January 2000,pp1-10
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I. INTRODUCTION
• LEACH-C(Leach centralized)[4]modified LEACH
by using global information and centralized
clustering algorithm for cluster formation in
order to realize uniform distribution of cluster
heads throughout the network.
– But LEACH-C is quite complex and the overhead is
relatively high.
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I. INTRODUCTION
• TEEN[6] makes use of a hierarchical scheme along with
a data centric mechanism.
– The working process is similar to the LEACH, but TEEN
• defines soft threshold and hard threshold to reduce the number of
transmissions.
– The first time a parameter from the attribute set reaches
its hard threshold value, the node switches on its
transmitter and sends the sensed data.
– If the range of variation of the monitoring data reaches the
soft threshold, the node forwards the latest data.
– drawback
• if the thresholds are not reached, the nodes will never
communicate.
[6] Manjeshwar A, Grawal DP. “TEEN: A protocol for enhanced efficiency in wireless
sensor networks”. In Proc. of the 15th Parallel and Distributed Processing Symp. San
Francisco: 2001. vol. 3, pp.30189a
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II. A DISTANCE-BASED CLUSTERING
PROTOCOL
• 2.1 The shortage of LEACH
• 2.2 LEACH-SC Protocol
– 2.2.1 System model
– 2.2.2 Optimization Goals
– 2.2.3 Optimization analysis
• 2.3 Analysis of the Protocol
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2.1 The shortage of LEACH
• The working procedure of LEACH is
– to select cluster heads randomly and then broadcast an
advertisement.
– Non-CH nodes pick the advertisement packet with the strongest
received signal strength then join that cluster.
• The algorithm itself has one severe problem in some
conditions.
– For example, As the topology graph shows in Fig 2-1,
• some nodes may choose a cluster so that the distance between its
cluster-head and the sink is even further than the distance between
the node itself and the sink.
• According to the energy model of LEACH protocol, the energy cost
will increases as the communication distance d increases.
– That’s to say, selecting cluster heads in such a random way will increase the
communication cost of nodes and decrease the energy efficiency of the
system.
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2.1 The shortage of LEACH
Figure 2-1 Routing for the network using LEACH
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2.2 LEACH-SC Protocol
• to save the energy cost of the sensor networks and
prolong the system’s lifetime,
– we propose a distance-based clustering protocol, LEACHSC（LEACH-selective cluster).
• The basic idea of the protocol is as follows:
• Firstly some assumptions are addressed in this paper:
– sink is located relatively close to the WSN field.
– cluster heads and nodes has the knowledge of its location
information.
• There are many ways for sensors to know their location
information without GPS, such as APIT[7], GFF[8] etc.
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2.2 LEACH-SC Protocol
• The operation of LEACH-SC is also divided into rounds.
– Each round begins with a set-up phase and steady phase.
– We do not change the way LEACH elects its cluster heads
• but changed the cluster formation algorithm.
– After the cluster heads are selected,
– cluster-heads broadcast an advertisement message that includes
• the cluster-head ID and location information to inform non-cluster head nodes.
– Non-cluster head nodes first record all the information from cluster
heads within their communication range.
– Then the node finds the cluster head which is closest to the middlepoint between the node itself and the sink and joins that cluster.
• In other words, how nodes join the cluster in order to prolong the system lifetime.
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2.3 Analysis of the Protocol
• Next the mathematical analysis will be introduced to
prove
– why it is most energy-efficient when ordinary nodes choose the
cluster head which is closest to the midpoint between itself and
the sink.
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2.2.1 System model
• As we know in wireless communications,
– free Space channel model is used
• if the communication distance is less than distance threshold
d0;
• otherwise, multi-path fading model is used.
• So the transmission energy of transmitting a k-bit
message over a distance d using this radio model
is:
• is the transmitter circuitry dissipation per bit.
• The receiving cost is:
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2.2.2 Optimization Goals
• to minimize the energy cost in the network and to prolong the
lifetime, so the mathematical model we build is:
–
–
–
–
–
E is total energy cost in the network.
E is the transmission cost,
E is the receiving cost,
E is the energy cost while being in idle state,
E is the energy cost while sensing.
total
T
R
I
S
• In general, the receiving cost, idle cost and sensing cost for a node
is almost constant
– while its transmission cost is variable.
• As a result, it’s the transmitting cost that determine the network’s overall cost.
So the Equation 2-4 can be changed to:
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2.2.2 Optimization Goals
•
According to the transmitting cost in the wireless model we can also change
Equation 2-5 into:
– k is the number of bit forwarding on the distance d.
– Eelec is the transmitter circuitry dissipation per bit.
– ε is the transmit amplifier dissipation per bit.
•
From the eq.(2-6) we can see that
– d has a crucial impact on the network’s energy cost. Then we can simplify the system model
into:
– n is set to 2 or 4.
•
The communication distance between nodes in wireless sensor networks are
usually short and mostly is the two-way communication. In the paper we set n=2,
which means the optimization goal is
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2.2.2 Optimization Goals
• distance between a node and a cluster head
as d
• the distance between a cluster head and the
sink as d .
• According to our wireless model, we further
simplify the optimization goal into:
toCH
CHtoSink
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2.2.3 Optimization analysis
• As it’s shown in Fig, we define
– M as the midpoint between the Node and the
Sink.
– A perpendicular is drawn from Cluster Head to
the line between the Sink and the node and H is
the Perpendicular foot.
• To make it simpler, we define
–
–
–
–
dtoSink (Distance between node and sink)as c,
dtoCH as b,
dCHtoSink as a,
the distance between H (Perpendicular Foot) and
M (Mid Point)is x,
– the distance between Cluster Head and M is d,
– the distance between Cluster Head and H is h.
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2.2.3 Optimization analysis
• We can see from the trigonometric formulas
that:
• Because we have
,substituting
, we get
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2.2.3 Optimization analysis
• From (2-10), we can see that when the value
of d is fixed, is only related to d, i.e
toSink
–
is equivalent to
.
• As a result, if a node chooses its cluster head
which is closest to the midpoint of this node
and the sink,
– the squared distance of their communication is
smallest.
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Conclusion:
•
is to actually
– minimize the distance between the cluster head
and the midpoint of a node and the sink when the
distance between the node and the sink is fixed.
• So in LEACH-SC,
– non-cluster nodes need to select the cluster head
which is closest to the midpoint between itself
and the sink as its communication cluster head in
order to optimize the communication cost.
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III. SIMULATION AND ANALYSIS
• NS-2[9] to simulate
• 100 stationary sensors and one sink.
• The nodes are supposed to be randomly
deployed within the WSN field which is a
square area of X*X.
• we set the initial energy of all nodes to 200 J.
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III. SIMULATION AND ANALYSIS
1.
2.
3.
4.
Energy Consumption with different Sink Locations
System lifetime with different sink locations
Energy consumption under different network size
System lifetime under different network size
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III. SIMULATION AND ANALYSIS
1. Energy Consumption with different Sink
Locations
– energy consumption of LEACH-SC protocol was
investigated versus that of LEACH protocol, over
various values of locations of the sink node.
– The simulation was conducted in an area of
100*100, and we evaluated the energy
consumption when sink located at (50,50),
(50,100), (50,150 ) and (50,200) respectively.
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1-Energy Consumption with different Sink
Locations
• Different
lines
represent
different sink locations with
LEACH and LEACH-SC.
• LEACH-SC protocol outperforms
the LEACH protocol in terms of
energy
consumption
with
different sink locations.
• When the sink node moves
farther away from the sensor
field,
– the performance of LEACH and
LEACH-SC
protocols
was
significantly decreased,
– but the performance of LEACH- Figure: Energy consumption versus time with
SC is always better than LEACH.
different sink locations
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(2) System lifetime with different sink
locations
• The number of nodes
remaining alive over time
was simulated for both
protocols which is shown
in Fig.
• We can see LEACH-SC
protocol extends the
network lifetime
– when compared with
LEACH protocol, no matter
what the position of the
sink is.
Figure: Number of survival nodes versus
time with different sink locations
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(3) Energy consumption under
different network size
•
•
•
•
•
We conducted the following four
experiments to evaluate the energy
consumption with different network
size.
We set a square area of the sensor
field to (50x50), (100x100), (200x200)
and (500x500) respectively.
And the sink is located in the center.
The simulation results are displayed
in Fig.
We can find that energy consumption
of LEACH-SC is conserved in all
simulation scenarios.
The curve of LEACH-SC protocol is
smoother than that of LEACH,
indicating that LEACH-SC’s energy
consumption
is
more
evenly
distributed and increased more
slowly over time.
Figure: energy consumption versus time with
different network size
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(4) System lifetime under different
network size
• We use the same simulation
scenarios as described in
recently previous slide.
• The simulation results are
shown in Fig.
– We can see in any cases, the
overall system lifetime of
LEACH-SC is prolonged when
compared to LEACH.
– We can also find that the
performance of LEACH and
LEACH-SC degrades as the
network size increases.
• But no matter what size the
network is, LEACH-SC always
outperforms the LEACH in terms
of system life and energy
dissipation
Figure: Simulation of system lifetime vs. time
with different network size
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