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Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011
DOI : 10.5121/cseij.2011.1301 1
CBHRP: A CLUSTER BASED ROUTING PROTOCOL
FOR WIRELESS SENSOR NETWORK
M. G. Rashed1
, M. Hasnat Kabir2
, M. Sajjadur Rahim3
, and Sk. Enayet Ullah2
1
Department of Electronics Telecommunication Engineering,
Prime University, Dhaka, Bangladesh
golamrashed@primeuniversity.edu.bd
2
Department of Information and Communication Engineering,
University of Rajshahi, Rajshahi, Bangladesh
{hasnatkabir,enayet67}@yhaoo.com
3
School of Information Engineering, University of Padova, Italy,
sajid83@yhaoo.com
ABSTRACT
A new two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol
(CBHRP) is proposed in this paper. It is an extension of LEACH routing protocol. We introduce cluster
head-set idea for cluster-based routing where several clusters are formed with the deployed sensors to
collect information from target field. On rotation basis, a head-set member receives data from the neighbor
nodes and transmits the aggregated results to the distance base station. This protocol reduces energy
consumption quite significantly and prolongs the life time of sensor network. It is found that CBHRP
performs better than other well accepted hierarchical routing protocols like LEACH in term of energy
consumption and time requirement.
KEYWORDS
Wireless Sensor Network, Cluster, Protocols, Routing.
1. INTRODUCTION
Wireless sensor networks (WSN) have been identified as one of the most important technologies
in the 21st century for various applications such as habitat monitoring, automation, agriculture,
and security. WSN consists of several tiny sensors called nodes that are organized in spatially
distributed topography. Researchers define WNS as an important component in the field of
Ubiquitous computing [1, 2]. Proactive computing concepts apply on WSN. With the proactive
computing model, computers will anticipate our needs and sometimes take action on our behalf.
Wireless sensor networks and proactive computing can assist us to improve efficiency, have data
from places which are otherwise difficult to get or to costly to monitor [3].
The dimension of microsensor is another important design goal. The size of sensor becomes very
tiny day by day. The nodes are typically battery operated sensing devices with limited energy
resources. Due to the small size, the battery of the nodes is fixed. One of the elegant ways to turn
off the sensor hardware when they are not used [4]. But replacing the sensor nodes is difficult
when their energy is depleted [5].
Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011
2
Scalability and performance consistency are the major design attributes of sensor networks. To
allow the system to cope with additional load and to be able to cover a large area of interest
without degrading the services, networking clustering has been pursued in some routing approach
[6]. The main objectives of clustering hierarchy is to efficiently maintain the energy consumption
of sensor nodes by involving them in ad-hoc communication within a particular cluster and by
performing data aggregation and fusion in order to decrease the number of transmitted message to
the base station. Cluster formation is typically based on the reserve of sensors and sensors’
proximity to the cluster head.
The lifetime of sensor can be increased by optimized the applications, operating systems, and
communication protocols. Using existing hardware, improvement of communication protocol can
prolong the lifetime of the network. This feature of WSN has opened new era for scientists and
engineers to develop efficient routing protocol. Numerous concept of communication protocol
can be found in literature [7, 8] to reduce the energy consumption of the wireless sensor
networks. Low-Energy Adaptive Clustering Hierarchy (LEACH), is one of the best
communication protocols for wireless sensor networks [9-11]. However, improvement of LEACH
protocol is going on to make it more efficient [4,], [12-13]. Therefore, it is significant to extend
the sensor networks lifetime through proficient use of the sensor nodes energy. Our new proposed
protocol increases the lifetime effectively than that of others by reducing the energy consumption.
2. RELATED WORKS
The key responsibility of wireless sensor network is to forward the sensing data gathered by
sensor nodes in the sensing fields to the BS. One simple approach to the fulfilment of this task is
direct data transmission. In this case, each node in the network directly sends sensing data to the
BS. As observed in LEACH [9], the direct approach would work best if the BS is located close to
the sensor nodes or the cost of receiving is very high as compared to the cost of transmitting data.
However, if the BS is remote from the sensor node, the node will soon die for suffering excessive
energy consumption for delivering data. To solve this problem, some algorithms that are aimed to
save energy have been proposed one after another.
LEACH protocol is hierarchical routing algorithm that can organize nodes into clusters
collections. Each cluster controlled by cluster head. Cluster head has several duties. First one is
gathering data from member cluster and accumulates them. Second one is directly sending
accumulation data to sink. Third one is scheduling based of Time-Division Multiple Access
(TDMA). In that, each node in cluster related to its time slot could send collection data [9].
Cluster head announce time slot by uses of distribution property to all members of cluster. Main
operations of LEACH are classify in two separate phase. First phase or initialization phase has
two process; clustering and cluster head determining. Second phase mean steady-state, that this
phase concentrate to gathering, accumulation and transmit data to sink. BCDCP [10] is a dynamic
clustering protocol, which distributes the energy dissipation evenly among all sensor nodes to
improve network lifetime and average energy savings. Simulation results show that BCDCP
reduces overall energy consumption and improves network lifetime over LEACH, LEACH-C
[11], and PEGASIS. HEARP [16] is a hierarchical energy-efficient routing protocol. HEARP is
based on both LEACH and PEGASIS [17] protocols. In HEARP, network establishment begins
with the formation of clusters. Several clusters are formed with one cluster head (CH) in each
cluster. Each cluster contains several nodes called member nodes, after the clusters are formed; a
chain is established among all the CHs using a greedy algorithm. A CH is chosen as leader node
form this chain for sending data to the BS. The operation of HEARP is broken up into rounds,
where each round begins with a set-up phase, followed by data transmission phase. During the
set-up phase, at the beginning of cluster formation, HEARP makes use of the same
algorithm as LAECH. It has been found from simulation results that HEARP is better
than LEACH, in terms of energy consumption. Again in terms of latency, HEARP
Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011
3
performs better than LEACH as well as PEGASIS. HEARP saves energy because only
one node transmits data directly to the base station.
3. THE PROPOSED APPROACH (CBHRP)
We have proposed and designed Cluster Based Hierarchical Routing Protocol (CBHRP) as an
extension of LEACH. It is a two-layer protocol where a number of clusters cover the whole
region of the network. The presented protocol is an optimum energy efficient cluster based
hierarchical routing protocol for wireless sensor network. Here we introduce a concept of head-
set instead of only head for cluster-based routing. The head-set members are responsible for the
control and the management of network. At a time, only one member of the head-set is active
and the remaining are in sleep mode within a cluster. This protocol divides the network into a few
real clusters that are managed by a virtual cluster head. The tasks are uniformly distributed
among all the head-set members. For a given number of data collecting nodes, the head-set nodes
are systematically adjusted to reduce the energy consumption, which increases the network life. A
detail architectural description of this proposed protocol can be found in our previous work [18].
4. SIMULATION MODEL OF CBHRP
We use a similar radio model as described in [9] where for a short distance transmission, such as
within a clusters, the energy consumed by a transmit amplifier is proportional to d2. However, for
a long distance transmission, such as from a cluster head to the base station, the energy
consumption is proportional to d4 .Using given radio model, the energy consumption to transmit
an l-bits message for a long distance (CH to BS), is given by:
(1)
Similarly, the energy consumption to transmit an l-bits message for a short distance is given by:
(2)
However, the energy consumption to receive the l-bits message is given by:
(3)
Eq. (3) includes the data aggregation approach.
4.1. Election Phase for CBHRP
Consider all nodes have same energy. Therefore, the amount of consumed energy is same for the
entire cluster. For uniformly distributed clusters, each cluster contains k
n
nodes. Using Eq. (2) and
Eq. (3), the energy consumed by a cluster head is estimated as follows:
(4)
The first part of Eq. (4) represents consumed energy to transmit the advertisement message; this
energy consumption is based on short distance energy dissipation model. The second part
represents consumed energy to receive )
1
( −
k
n
messages from the normal sensor nodes of the
same cluster. Eq. (4) can be simplified as follows:
,
4
d
l
lE
E l
amp
elec
T −
+
= ε
,
2
d
l
lE
E s
amp
elec
T −
+
= ε
,
AG
elec
R lE
lE
E +
=
}
)
1
{(
}
{ 2
AG
elec
k
n
s
amp
elec
election
CH lE
lE
d
l
lE
E +
−
+
+
= −
− ε
Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011
4
(5)
Using Eq. (2) and Eq. (3), the energy consumed by non-cluster head sensor nodes are estimated as
follows:
(6)
The first part of Eq. (6) shows consumed energy to receive messages from k cluster heads; it is
assumed that a sensor node receives messages from all the cluster heads. The second part shows
consumed energy to transmit the decision to the corresponding cluster head. Eq. (6) can be
simplified as follows:
(7)
4.2. Data transfer phase for CBHRP
During data transfer phase, the nodes transmit messages to their cluster head and cluster heads
transmit an aggregated message to a distant base station. The energy consumed by a cluster head
is as follows:
(8)
The first part of Eq. (8) shows consumed energy to transmit a message to the distant base station.
The second part shows consumed energy to receive messages from the remaining ( 1
−
k
n
) nodes.
Eq. (8) can be simplified as follows:
(9)
The energy, Enon-CH/frame, consumed by a non-cluster head node to transmit the sensor data to the
cluster head is given below:
(10)
In one iteration, Nf data frames are transmitted. Each cluster transmits Nf/k data frame. These data
are uniformly divided among n/k nodes. Therefore, a cluster head transmits the data frame of
(n/k-m) non-cluster head data. For simplification of equations, the fraction f1 and f2 are given as
below:
(11)
2
)
1
(
)
( d
l
lE
lE
E s
amp
k
n
AG
elec
k
n
election
CH −
− +
−
+
= ε
}
{
}
{ 2
d
l
lE
klE
klE
E s
amp
elec
AG
Elec
election
CH
non −
−
− +
+
+
= ε
2
)
1
( d
l
klE
k
lE
E s
amp
AG
elec
election
CH
non −
−
− +
+
+
= ε
)}
(
)
{(
}
{ 4
/ AG
elec
k
n
l
amp
elec
frame
CH E
E
l
m
d
l
lE
E +
−
+
+
= −
ε
AG
k
n
elec
k
n
l
amp
frame
CH E
m
l
lE
m
d
l
E )
(
)
1
(
2
/ −
+
+
−
+
= −
ε
2
/ d
l
lE
E s
amp
elec
frame
CH
non −
− +
= ε
k
m
f
k
n
1
*
1
1
1






+
−
=
Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011
5
(12)
The energy consumption in a data transfer phase of each cluster is as follows:
(13)
(14)
4.3. Initial Energy for one round in CBHRP
In each iteration, m nodes are elected as associate head for each cluster. Thus, km nodes are
elected as members of head-sets. The numbers of iterations required in one round are km
n
that are
needed to be elected for all nodes. Each iteration consists of an election phase and a data transfer
phase. Therefore, the consumed energy in an iteration is as follows:
(15)
(16)
Since, there is m nodes as cluster head within a cluster, the ECH/iteration/cluster is assigned for
all cluster heads. For single cluster head is
(17)
Similarly, there are ( m
k
n
− ) non-cluster head nodes in a cluster. The Enon-CH/iteration/cluster is
uniformly distributed among all the non-cluster head members. For single non-cluster head is
(18)
The initial energy, init
E should be sufficient for at least one round. A node becomes a member of
head-set for one time and a non-cluster head for (n/mk-1) times in one round. An estimation of
init
E is given below:
(19)
k
m
m
f
k
n
k
n
1
*
1
2






+
−
−
=
frame
CH
f
data
CH E
N
f
E /
1
=
−
frame
CH
non
f
data
CH
non E
N
f
E /
2 −
−
− =
data
CH
election
CH
cluster
iteration
CH E
E
E −
− +
=
/
/
data
CH
non
election
CH
non
cluster
iteration
CH
non E
E
E −
−
−
−
− +
=
/
/
m
E
E cluster
iteration
CH
node
CH
/
/
/ =
)
(
/
/
/
m
E
E
k
n
cluster
iteration
CH
non
node
CH
non
−
= −
−
node
CH
non
mk
n
node
CH
init E
E
E /
/ )
1
( −
−
+
=
Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011
6
Eq. (19) can be represented as follows using the value of Eq. (17) and Eq. (18)
(20)
Using Eq. (13), (14), (15), (16) Einit can be given as follows:
(21)
Using Eq. (21), Nf can be given as follows:
(22)
4.4. Required Time for one round
Sensor nodes transmit messages according to a specified schedule, which is based on TDMA. The
frame time, tframe is the integration of frame transmitted time by all the nodes of a cluster. For a
data transfer rate of Rb bits/second and message length of l bits, the time to transfer a message,
tmsg, is:
(23)
The messages are transmitted by all the non-cluster head nodes and the active member of cluster
head-set. Since at one time only one member of head-set is active, the remaining (m-1) inactive
head-sets do not transmit any frame.
The time for one frame is
The first part of Eq. (24) is due to ( m
k
n
− ) message from non-cluster head nodes. The second part
is due to the active member of the head-set.
If we assume that message transfer time is same for all the nodes, Eq. (24) can be simplified as
follows:
(25)
m
E
E
E cluster
iteration
CH
non
cluster
iteration
CH
init
/
/
/
/ −
+
=
( )






+
+





 +
= −
−
−
−
frame
CH
non
frame
CH
f
election
CH
non
election
CH
init E
f
E
f
m
N
m
E
E
E /
2
/
1
*
frame
CH
non
frame
CH
election
CH
non
election
CH
init
f
E
f
E
f
E
E
mE
N
/
2
/
1 −
−
−
−
+
−
−
=
b
msg
R
l
t =
msg
frame t
m
k
n
t )
1
( +
−
=
head
msgcluster
m
k
n
i
msgi
frame t
t
t _
1
+
= ∑
−
=
(24)
Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011
7
As Nf frames are transmitted in one epoch, time for one iteration, titeration is:
Using Eq. (23), (25), (26), the iteration time titeration can be given as:
(27)
Since there are km
n
iterations in one round, the time for one round, tround is:
(28)
4. RESULTS AND DISCUSSION
In wireless sensor network, energy is prime concerned factor. Low energy consume network is
desirable. The variation of energy consumption per round with respect to the number of clusters
and network diameter is shows in Figure 1. Graph represents that energy consumption is reduced
when the number of clusters are increased. It also shows that the optimum range of cluster is from
20 to 60. When the number of clusters are below the optimum range, for example 10, normal
sensor nodes have to send data to the distance cluster heads with high-energy dissipation. On the
other hand, when the number of cluster is excited optimum range, more transmissions is possible
to the distance base station with minimum energy dissipation.
f
frame
iteraton N
t
t ×
=
f
b
iteration N
m
k
n
R
l
t )
1
( +
−
=
km
n
t
t iteration
round ×
=
m
N
m
k
n
k
n
R
l f
b
)
1
( +
−
=
(26)
Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011
8
0
50
100
150
200
0
20
40
60
0
0.2
0.4
0.6
0.8
1
Network Diameter (m)
# Of Clusters
Einit(J)
Head-set size=4
Head-set size=2
LEACH
Figure 1. Energy consumption per round with respect to number of cluster and network
diameter.
It can be pointed out that the concept of head-set considered in the network reduces energy
consumption. In comparison with LEACH, it is clearly seen for transmission of each frame that
the energy consumption is reduced by 5 and 7 times for head-set size of 2 and 4, respectively. The
head-set reduces the election process to become a cluster head in our proposed routing model as
compared to LEACH. The number of elections for n nodes in the case of LEACH is k
n
whereas
mk
n
for CBHRP here m is the head-set size.
Figure 2. illustrates the energy consumption per round with respect to the head-set size and
distance of the base station for fixed network diameter. Here the number of clusters k=50.It is
seen from this figure that the energy consumption is increased with the distance of the base
station for a given value of head-set. The position of the base station has great influence on the
lifetime of the network. Since most of the energy is consumed by transmission from cluster-heads
to the base station, therefore, energy savings are not significant for a longer distance between the
base station and the sensor nodes.
Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011
9
150
200
250
0
5
10
15
0
0.02
0.04
0.06
0.08
0.1
0.12
Distance
Head set size
Einit
(J)
Figure 2. Energy consumption per round with respect to the distance of the BS and head set size
when the network diameter is fixed.
120
140
160
180
200
0
50
100
0
1
2
3
4
x 10
4
Distance(m)
Head-Set Size (%)
Time
for
one
iteration
(sec)
Einit=0.2 J
Einit=0.1 J
Figure 3. Iteration time with respect to distance of the BS and the head-set size.
The relationship between iteration time and the head-set size as a function of distance of base
station is shown in Figure 3. For a given number of head-set, the distance of the base station may
be varied to observe the impact in iteration time. The head-set size is given as a percentage of
cluster size. The initial energy can be used for the longest period of time when the head set size is
50% of the cluster size. Here we see that the iteration time is decreasing with increasing of head-
set size as a function of base station distance.
Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011
10
0 5 10 15 20
150
200
250
-5000
0
5000
10000
15000
20000
# of clusters, k
Distance
Time
for
one
iteration
(sec)
Head set size=5
Head set size=3
LEACH
Figure 4. Iteration time with respect to the number of clusters and the distance of the BS.
Figure 4 shows a graph that illustrates the variation in time for iteration with respect to the
number of clusters and BS distance. The time for iteration increases as the head-set size increases
for a particular number of clusters. This indicates that the head-set size should be carefully chosen
to extend the network life time.
100
110
120
130
140
150
140
160
180
200
0
1
2
3
4
5
x 10
4
Diameter
Distance
#
of
Frames
Head set size=5
Head set size=3
LEACH
Figure 5. Number of frames transmission per iteration with respect to the distance of BS and
network diameter.
Figure 5 shows the number of frames transmitted with respect to network diameter and distance
from BS. The number of data transmission is another important issue in a wireless sensor
network. It is a measuring tool of a network suitability and perfectness. Simulated results show
that the proposed method is able to transmit higher data frame in contrast to LECAH for the same
dimension and distance of BS. However, it is clearly found that the transmission rate slightly
decreases with respect to the distance of BS.
Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011
11
5. CONCLUSIONS
The proposed routing protocol (CBHRP) is designed to overcome some presents limitations of
WSNs. The results of our analysis indicate that the energy consumption can be considerably
reduced by including more sensors as cluster head in a head-set instead of using only one cluster
head within a cluster. The iteration time and data transfer rate also increases with the size of head-
set. Therefore, the overall network lifetime is prolonged. So, it can be concluded that the propose
protocol provides an energy-efficient routing scheme is suitable for a vast range of sensing
applications than that of LECAH.
References
[1] B. Warneke, M. Last, B. Liebowitz, K. Pister, (2001),” “Smart Dust: Communicating with a cubic-
millimeter computer”” IEEE Computer, p. 2-9.
[2] R. Min, M. Bhardwaj, S. Cho, E. Shih, A. Sinha, A. Wang, and A. Chandrakasan , (2001)” Low-
power wireless sensor networks”, VLSI Design-2001, Invited Paper, Bangalore.
[3] WSN, http://www.intel.com/research/exploratory/wireless_sensor.htm.
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networks”, IEEE Design & Test of Computers, S. 62-74.
[5] Choon-Sung Nam, Hee-Jin Jeong and Dong-Ryeol Shin, (2008),“The Adaptive Cluster Head
Selection in Wireless Sensor Networks” IEEE International Workshop on Semantic Computing
and Applications.
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[10] Siv A D. Murugana Than , Daniel C. F. MA, Roll Y I. Bhasin, Abraham O. Fapojuwo (2005), “A
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Architecture for Wireless Microsensor Networks” IEEE Transaction on Wireless Networking. Vol.
1, no. 4,p-660-670.
[14] M. J. Handy, M. Haase, D. Timmermann, , (2002),IEEE_MWCN2002.
[15] Fan Xiangning, Song Yulin,(2007) “Improvement on LEACH Protocol of Wireless Sensor
Network” , Pro. International Conference on Sensor Technologies and Applications, IEEE
doi:10.1109/SENSORCOMM.2007.21
[16] Shamsad Parvin,( 2007), Hierarchical Energy Aware Routing Protocol (HEARP) for Wireless
Sensor Networks, Thesis paper, Personal Communication., University of Rajshahi. Bangladesh.
[17] S. Lindsey and C. S .Raghavendra.(2002),” PEGASIS: Power-effcient gatherring in sensor
information systems .”, In Proceedings of the IEEE ero space Conf.P:1125-1130.
[18] M.G. Rashed , M. H. Kabir, M.S. Rahim, S. E. Ullah, (2010),” Cluster Based Hierarchical Routing
Protocol (CBHRP) for Wireless Sensor Networks (WSNs)” International Journal of Computer and
Network Security, Vol.2 No.5..

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CBHRP: A Cluster Based Routing Protocol for Wireless Sensor Network

  • 1. Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011 DOI : 10.5121/cseij.2011.1301 1 CBHRP: A CLUSTER BASED ROUTING PROTOCOL FOR WIRELESS SENSOR NETWORK M. G. Rashed1 , M. Hasnat Kabir2 , M. Sajjadur Rahim3 , and Sk. Enayet Ullah2 1 Department of Electronics Telecommunication Engineering, Prime University, Dhaka, Bangladesh golamrashed@primeuniversity.edu.bd 2 Department of Information and Communication Engineering, University of Rajshahi, Rajshahi, Bangladesh {hasnatkabir,enayet67}@yhaoo.com 3 School of Information Engineering, University of Padova, Italy, sajid83@yhaoo.com ABSTRACT A new two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol (CBHRP) is proposed in this paper. It is an extension of LEACH routing protocol. We introduce cluster head-set idea for cluster-based routing where several clusters are formed with the deployed sensors to collect information from target field. On rotation basis, a head-set member receives data from the neighbor nodes and transmits the aggregated results to the distance base station. This protocol reduces energy consumption quite significantly and prolongs the life time of sensor network. It is found that CBHRP performs better than other well accepted hierarchical routing protocols like LEACH in term of energy consumption and time requirement. KEYWORDS Wireless Sensor Network, Cluster, Protocols, Routing. 1. INTRODUCTION Wireless sensor networks (WSN) have been identified as one of the most important technologies in the 21st century for various applications such as habitat monitoring, automation, agriculture, and security. WSN consists of several tiny sensors called nodes that are organized in spatially distributed topography. Researchers define WNS as an important component in the field of Ubiquitous computing [1, 2]. Proactive computing concepts apply on WSN. With the proactive computing model, computers will anticipate our needs and sometimes take action on our behalf. Wireless sensor networks and proactive computing can assist us to improve efficiency, have data from places which are otherwise difficult to get or to costly to monitor [3]. The dimension of microsensor is another important design goal. The size of sensor becomes very tiny day by day. The nodes are typically battery operated sensing devices with limited energy resources. Due to the small size, the battery of the nodes is fixed. One of the elegant ways to turn off the sensor hardware when they are not used [4]. But replacing the sensor nodes is difficult when their energy is depleted [5].
  • 2. Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011 2 Scalability and performance consistency are the major design attributes of sensor networks. To allow the system to cope with additional load and to be able to cover a large area of interest without degrading the services, networking clustering has been pursued in some routing approach [6]. The main objectives of clustering hierarchy is to efficiently maintain the energy consumption of sensor nodes by involving them in ad-hoc communication within a particular cluster and by performing data aggregation and fusion in order to decrease the number of transmitted message to the base station. Cluster formation is typically based on the reserve of sensors and sensors’ proximity to the cluster head. The lifetime of sensor can be increased by optimized the applications, operating systems, and communication protocols. Using existing hardware, improvement of communication protocol can prolong the lifetime of the network. This feature of WSN has opened new era for scientists and engineers to develop efficient routing protocol. Numerous concept of communication protocol can be found in literature [7, 8] to reduce the energy consumption of the wireless sensor networks. Low-Energy Adaptive Clustering Hierarchy (LEACH), is one of the best communication protocols for wireless sensor networks [9-11]. However, improvement of LEACH protocol is going on to make it more efficient [4,], [12-13]. Therefore, it is significant to extend the sensor networks lifetime through proficient use of the sensor nodes energy. Our new proposed protocol increases the lifetime effectively than that of others by reducing the energy consumption. 2. RELATED WORKS The key responsibility of wireless sensor network is to forward the sensing data gathered by sensor nodes in the sensing fields to the BS. One simple approach to the fulfilment of this task is direct data transmission. In this case, each node in the network directly sends sensing data to the BS. As observed in LEACH [9], the direct approach would work best if the BS is located close to the sensor nodes or the cost of receiving is very high as compared to the cost of transmitting data. However, if the BS is remote from the sensor node, the node will soon die for suffering excessive energy consumption for delivering data. To solve this problem, some algorithms that are aimed to save energy have been proposed one after another. LEACH protocol is hierarchical routing algorithm that can organize nodes into clusters collections. Each cluster controlled by cluster head. Cluster head has several duties. First one is gathering data from member cluster and accumulates them. Second one is directly sending accumulation data to sink. Third one is scheduling based of Time-Division Multiple Access (TDMA). In that, each node in cluster related to its time slot could send collection data [9]. Cluster head announce time slot by uses of distribution property to all members of cluster. Main operations of LEACH are classify in two separate phase. First phase or initialization phase has two process; clustering and cluster head determining. Second phase mean steady-state, that this phase concentrate to gathering, accumulation and transmit data to sink. BCDCP [10] is a dynamic clustering protocol, which distributes the energy dissipation evenly among all sensor nodes to improve network lifetime and average energy savings. Simulation results show that BCDCP reduces overall energy consumption and improves network lifetime over LEACH, LEACH-C [11], and PEGASIS. HEARP [16] is a hierarchical energy-efficient routing protocol. HEARP is based on both LEACH and PEGASIS [17] protocols. In HEARP, network establishment begins with the formation of clusters. Several clusters are formed with one cluster head (CH) in each cluster. Each cluster contains several nodes called member nodes, after the clusters are formed; a chain is established among all the CHs using a greedy algorithm. A CH is chosen as leader node form this chain for sending data to the BS. The operation of HEARP is broken up into rounds, where each round begins with a set-up phase, followed by data transmission phase. During the set-up phase, at the beginning of cluster formation, HEARP makes use of the same algorithm as LAECH. It has been found from simulation results that HEARP is better than LEACH, in terms of energy consumption. Again in terms of latency, HEARP
  • 3. Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011 3 performs better than LEACH as well as PEGASIS. HEARP saves energy because only one node transmits data directly to the base station. 3. THE PROPOSED APPROACH (CBHRP) We have proposed and designed Cluster Based Hierarchical Routing Protocol (CBHRP) as an extension of LEACH. It is a two-layer protocol where a number of clusters cover the whole region of the network. The presented protocol is an optimum energy efficient cluster based hierarchical routing protocol for wireless sensor network. Here we introduce a concept of head- set instead of only head for cluster-based routing. The head-set members are responsible for the control and the management of network. At a time, only one member of the head-set is active and the remaining are in sleep mode within a cluster. This protocol divides the network into a few real clusters that are managed by a virtual cluster head. The tasks are uniformly distributed among all the head-set members. For a given number of data collecting nodes, the head-set nodes are systematically adjusted to reduce the energy consumption, which increases the network life. A detail architectural description of this proposed protocol can be found in our previous work [18]. 4. SIMULATION MODEL OF CBHRP We use a similar radio model as described in [9] where for a short distance transmission, such as within a clusters, the energy consumed by a transmit amplifier is proportional to d2. However, for a long distance transmission, such as from a cluster head to the base station, the energy consumption is proportional to d4 .Using given radio model, the energy consumption to transmit an l-bits message for a long distance (CH to BS), is given by: (1) Similarly, the energy consumption to transmit an l-bits message for a short distance is given by: (2) However, the energy consumption to receive the l-bits message is given by: (3) Eq. (3) includes the data aggregation approach. 4.1. Election Phase for CBHRP Consider all nodes have same energy. Therefore, the amount of consumed energy is same for the entire cluster. For uniformly distributed clusters, each cluster contains k n nodes. Using Eq. (2) and Eq. (3), the energy consumed by a cluster head is estimated as follows: (4) The first part of Eq. (4) represents consumed energy to transmit the advertisement message; this energy consumption is based on short distance energy dissipation model. The second part represents consumed energy to receive ) 1 ( − k n messages from the normal sensor nodes of the same cluster. Eq. (4) can be simplified as follows: , 4 d l lE E l amp elec T − + = ε , 2 d l lE E s amp elec T − + = ε , AG elec R lE lE E + = } ) 1 {( } { 2 AG elec k n s amp elec election CH lE lE d l lE E + − + + = − − ε
  • 4. Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011 4 (5) Using Eq. (2) and Eq. (3), the energy consumed by non-cluster head sensor nodes are estimated as follows: (6) The first part of Eq. (6) shows consumed energy to receive messages from k cluster heads; it is assumed that a sensor node receives messages from all the cluster heads. The second part shows consumed energy to transmit the decision to the corresponding cluster head. Eq. (6) can be simplified as follows: (7) 4.2. Data transfer phase for CBHRP During data transfer phase, the nodes transmit messages to their cluster head and cluster heads transmit an aggregated message to a distant base station. The energy consumed by a cluster head is as follows: (8) The first part of Eq. (8) shows consumed energy to transmit a message to the distant base station. The second part shows consumed energy to receive messages from the remaining ( 1 − k n ) nodes. Eq. (8) can be simplified as follows: (9) The energy, Enon-CH/frame, consumed by a non-cluster head node to transmit the sensor data to the cluster head is given below: (10) In one iteration, Nf data frames are transmitted. Each cluster transmits Nf/k data frame. These data are uniformly divided among n/k nodes. Therefore, a cluster head transmits the data frame of (n/k-m) non-cluster head data. For simplification of equations, the fraction f1 and f2 are given as below: (11) 2 ) 1 ( ) ( d l lE lE E s amp k n AG elec k n election CH − − + − + = ε } { } { 2 d l lE klE klE E s amp elec AG Elec election CH non − − − + + + = ε 2 ) 1 ( d l klE k lE E s amp AG elec election CH non − − − + + + = ε )} ( ) {( } { 4 / AG elec k n l amp elec frame CH E E l m d l lE E + − + + = − ε AG k n elec k n l amp frame CH E m l lE m d l E ) ( ) 1 ( 2 / − + + − + = − ε 2 / d l lE E s amp elec frame CH non − − + = ε k m f k n 1 * 1 1 1       + − =
  • 5. Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011 5 (12) The energy consumption in a data transfer phase of each cluster is as follows: (13) (14) 4.3. Initial Energy for one round in CBHRP In each iteration, m nodes are elected as associate head for each cluster. Thus, km nodes are elected as members of head-sets. The numbers of iterations required in one round are km n that are needed to be elected for all nodes. Each iteration consists of an election phase and a data transfer phase. Therefore, the consumed energy in an iteration is as follows: (15) (16) Since, there is m nodes as cluster head within a cluster, the ECH/iteration/cluster is assigned for all cluster heads. For single cluster head is (17) Similarly, there are ( m k n − ) non-cluster head nodes in a cluster. The Enon-CH/iteration/cluster is uniformly distributed among all the non-cluster head members. For single non-cluster head is (18) The initial energy, init E should be sufficient for at least one round. A node becomes a member of head-set for one time and a non-cluster head for (n/mk-1) times in one round. An estimation of init E is given below: (19) k m m f k n k n 1 * 1 2       + − − = frame CH f data CH E N f E / 1 = − frame CH non f data CH non E N f E / 2 − − − = data CH election CH cluster iteration CH E E E − − + = / / data CH non election CH non cluster iteration CH non E E E − − − − − + = / / m E E cluster iteration CH node CH / / / = ) ( / / / m E E k n cluster iteration CH non node CH non − = − − node CH non mk n node CH init E E E / / ) 1 ( − − + =
  • 6. Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011 6 Eq. (19) can be represented as follows using the value of Eq. (17) and Eq. (18) (20) Using Eq. (13), (14), (15), (16) Einit can be given as follows: (21) Using Eq. (21), Nf can be given as follows: (22) 4.4. Required Time for one round Sensor nodes transmit messages according to a specified schedule, which is based on TDMA. The frame time, tframe is the integration of frame transmitted time by all the nodes of a cluster. For a data transfer rate of Rb bits/second and message length of l bits, the time to transfer a message, tmsg, is: (23) The messages are transmitted by all the non-cluster head nodes and the active member of cluster head-set. Since at one time only one member of head-set is active, the remaining (m-1) inactive head-sets do not transmit any frame. The time for one frame is The first part of Eq. (24) is due to ( m k n − ) message from non-cluster head nodes. The second part is due to the active member of the head-set. If we assume that message transfer time is same for all the nodes, Eq. (24) can be simplified as follows: (25) m E E E cluster iteration CH non cluster iteration CH init / / / / − + = ( )       + +       + = − − − − frame CH non frame CH f election CH non election CH init E f E f m N m E E E / 2 / 1 * frame CH non frame CH election CH non election CH init f E f E f E E mE N / 2 / 1 − − − − + − − = b msg R l t = msg frame t m k n t ) 1 ( + − = head msgcluster m k n i msgi frame t t t _ 1 + = ∑ − = (24)
  • 7. Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011 7 As Nf frames are transmitted in one epoch, time for one iteration, titeration is: Using Eq. (23), (25), (26), the iteration time titeration can be given as: (27) Since there are km n iterations in one round, the time for one round, tround is: (28) 4. RESULTS AND DISCUSSION In wireless sensor network, energy is prime concerned factor. Low energy consume network is desirable. The variation of energy consumption per round with respect to the number of clusters and network diameter is shows in Figure 1. Graph represents that energy consumption is reduced when the number of clusters are increased. It also shows that the optimum range of cluster is from 20 to 60. When the number of clusters are below the optimum range, for example 10, normal sensor nodes have to send data to the distance cluster heads with high-energy dissipation. On the other hand, when the number of cluster is excited optimum range, more transmissions is possible to the distance base station with minimum energy dissipation. f frame iteraton N t t × = f b iteration N m k n R l t ) 1 ( + − = km n t t iteration round × = m N m k n k n R l f b ) 1 ( + − = (26)
  • 8. Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011 8 0 50 100 150 200 0 20 40 60 0 0.2 0.4 0.6 0.8 1 Network Diameter (m) # Of Clusters Einit(J) Head-set size=4 Head-set size=2 LEACH Figure 1. Energy consumption per round with respect to number of cluster and network diameter. It can be pointed out that the concept of head-set considered in the network reduces energy consumption. In comparison with LEACH, it is clearly seen for transmission of each frame that the energy consumption is reduced by 5 and 7 times for head-set size of 2 and 4, respectively. The head-set reduces the election process to become a cluster head in our proposed routing model as compared to LEACH. The number of elections for n nodes in the case of LEACH is k n whereas mk n for CBHRP here m is the head-set size. Figure 2. illustrates the energy consumption per round with respect to the head-set size and distance of the base station for fixed network diameter. Here the number of clusters k=50.It is seen from this figure that the energy consumption is increased with the distance of the base station for a given value of head-set. The position of the base station has great influence on the lifetime of the network. Since most of the energy is consumed by transmission from cluster-heads to the base station, therefore, energy savings are not significant for a longer distance between the base station and the sensor nodes.
  • 9. Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011 9 150 200 250 0 5 10 15 0 0.02 0.04 0.06 0.08 0.1 0.12 Distance Head set size Einit (J) Figure 2. Energy consumption per round with respect to the distance of the BS and head set size when the network diameter is fixed. 120 140 160 180 200 0 50 100 0 1 2 3 4 x 10 4 Distance(m) Head-Set Size (%) Time for one iteration (sec) Einit=0.2 J Einit=0.1 J Figure 3. Iteration time with respect to distance of the BS and the head-set size. The relationship between iteration time and the head-set size as a function of distance of base station is shown in Figure 3. For a given number of head-set, the distance of the base station may be varied to observe the impact in iteration time. The head-set size is given as a percentage of cluster size. The initial energy can be used for the longest period of time when the head set size is 50% of the cluster size. Here we see that the iteration time is decreasing with increasing of head- set size as a function of base station distance.
  • 10. Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011 10 0 5 10 15 20 150 200 250 -5000 0 5000 10000 15000 20000 # of clusters, k Distance Time for one iteration (sec) Head set size=5 Head set size=3 LEACH Figure 4. Iteration time with respect to the number of clusters and the distance of the BS. Figure 4 shows a graph that illustrates the variation in time for iteration with respect to the number of clusters and BS distance. The time for iteration increases as the head-set size increases for a particular number of clusters. This indicates that the head-set size should be carefully chosen to extend the network life time. 100 110 120 130 140 150 140 160 180 200 0 1 2 3 4 5 x 10 4 Diameter Distance # of Frames Head set size=5 Head set size=3 LEACH Figure 5. Number of frames transmission per iteration with respect to the distance of BS and network diameter. Figure 5 shows the number of frames transmitted with respect to network diameter and distance from BS. The number of data transmission is another important issue in a wireless sensor network. It is a measuring tool of a network suitability and perfectness. Simulated results show that the proposed method is able to transmit higher data frame in contrast to LECAH for the same dimension and distance of BS. However, it is clearly found that the transmission rate slightly decreases with respect to the distance of BS.
  • 11. Computer Science & Engineering: An International Journal (CSEIJ), Vol.1, No.3, August 2011 11 5. CONCLUSIONS The proposed routing protocol (CBHRP) is designed to overcome some presents limitations of WSNs. The results of our analysis indicate that the energy consumption can be considerably reduced by including more sensors as cluster head in a head-set instead of using only one cluster head within a cluster. The iteration time and data transfer rate also increases with the size of head- set. Therefore, the overall network lifetime is prolonged. So, it can be concluded that the propose protocol provides an energy-efficient routing scheme is suitable for a vast range of sensing applications than that of LECAH. References [1] B. Warneke, M. Last, B. Liebowitz, K. Pister, (2001),” “Smart Dust: Communicating with a cubic- millimeter computer”” IEEE Computer, p. 2-9. [2] R. Min, M. Bhardwaj, S. Cho, E. Shih, A. Sinha, A. Wang, and A. Chandrakasan , (2001)” Low- power wireless sensor networks”, VLSI Design-2001, Invited Paper, Bangalore. [3] WSN, http://www.intel.com/research/exploratory/wireless_sensor.htm. [4] A. Sinha, and A. Chandrakasan,(2001) ,” Dynamic power management in wireless sensor networks”, IEEE Design & Test of Computers, S. 62-74. [5] Choon-Sung Nam, Hee-Jin Jeong and Dong-Ryeol Shin, (2008),“The Adaptive Cluster Head Selection in Wireless Sensor Networks” IEEE International Workshop on Semantic Computing and Applications. [6] Peng Jiang, Yu Wen, Jianzhong Wang, Xingfa Shen, Anke Xue (2006), “A study of routing protocols in Wireless Sensor Networks”, Proceedings of the 6th World Congress on Intelligent Control and Automation, pp. 266-270, Dalian, China. [7] L. Zhong, R. Shah, C. Guo, and J. Rabaey,(2001) “An Ultra-Low power and distributed access protocol for broadband wireless sensor networks”, IEEEBroadband Wireless Summit, Las Vegas. [8] V. Rodoplu, T. H. Meng,(1999), IEEE Jour. Selected Areas Comm.,pp. 1333-1344. [9] W. Heinzelman, A. Chandrakasan, H. Balakrishnan(2000) “Energy-efficient communication protocol for wireless microsensor Networks “ Proceedings of the 33rd International Conference on System Sciences (HICSS '00). [10] Siv A D. Murugana Than , Daniel C. F. MA, Roll Y I. Bhasin, Abraham O. Fapojuwo (2005), “A Centralized Energy-Efficient Routing Protocol for Wireless Sensor Networks”, IEEE Radio Communication.PP. 8-13. [11] W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan,(2002) “An ApplicationSpecific Protocol Architecture for Wireless Microsensor Networks,” IEEE Trans. Wireless Commun. , vol. 1, no. 4, pp. 660–70. [12] W. Heinzelman, A. Sinha, A. Wang, A. Chandrakasan,(2000) “Energy scalable algorithms and protocols for wireless microsensor networks”Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP '00). [13] W. Heinzelman, A. Chandrakasan, H. Balakrishnan,(2002)” An Application-Specific Protocol Architecture for Wireless Microsensor Networks” IEEE Transaction on Wireless Networking. Vol. 1, no. 4,p-660-670. [14] M. J. Handy, M. Haase, D. Timmermann, , (2002),IEEE_MWCN2002. [15] Fan Xiangning, Song Yulin,(2007) “Improvement on LEACH Protocol of Wireless Sensor Network” , Pro. International Conference on Sensor Technologies and Applications, IEEE doi:10.1109/SENSORCOMM.2007.21 [16] Shamsad Parvin,( 2007), Hierarchical Energy Aware Routing Protocol (HEARP) for Wireless Sensor Networks, Thesis paper, Personal Communication., University of Rajshahi. Bangladesh. [17] S. Lindsey and C. S .Raghavendra.(2002),” PEGASIS: Power-effcient gatherring in sensor information systems .”, In Proceedings of the IEEE ero space Conf.P:1125-1130. [18] M.G. Rashed , M. H. Kabir, M.S. Rahim, S. E. Ullah, (2010),” Cluster Based Hierarchical Routing Protocol (CBHRP) for Wireless Sensor Networks (WSNs)” International Journal of Computer and Network Security, Vol.2 No.5..