CUTTING DOWN ENERGY USAGE IN WIRELESS SENSOR NETWORKS USING DUTY CYCLE TECHNIQUE AND MULTI-HOP ROUTING

International Journal of Wireless & Mobile Networks (IJWMN) Vol. 8, No. 4, August 2016
DOI: 10.5121/ijwmn.2016.8402 23
CUTTING DOWN ENERGY USAGE IN WIRELESS
SENSOR NETWORKS USING DUTY CYCLE
TECHNIQUE AND MULTI-HOP ROUTING
Ali Sedighimanesh1
, Mohammad Sedighimanesh2
and Javad Baqeri3
1,2,3
Department of Electrical, Computer and It Engineering, Islamic Azad University of
Qazvin
Abstract
A wireless sensor network is composed of many sensor nodes, that have beengiven out in a
specific zoneandeach of them hadanability of collecting information from the environment and
sending collected data to the sink. The most significant issues in wireless sensor networks,
despite the recent progress is the trouble of the severe limitations of energy resources.Since that
in different applications of sensor nets, we could throw a static or mobile sink, then all aspects of
such networks should be planned with an awareness of energy.One of the most significant topics
related to these networks, is routing. One of the most widely used and efficient methods of
routing isa hierarchy (based on clustering) method.
In The present study with the objective of cutting down energy consumption and persistence of
network coverage, we have offered a novel algorithm based on clustering algorithms and multi-
hop routing.To achieve this goal, first, we layer the network environment based on the size of the
network.We will identify the optimal number of cluster heads and every cluster head based on
the mechanism of topology control will start to accept members.Likewise, we set the first layer
as gate layer and subsequently identifying the gate’s nodes, we’d turn away half of the sensors
and then stop using energy and the remaining nodes in this layer will join the gate’s nodes
because they hold a critical part in bettering the functioning of the system. Cluster heads off
following layers send the information to cluster heads in the above layer until sent data will be
sent to gate’s nodes and finally will be sent to sink. We have tested the proposed algorithm in
two situations 1) when the sink is off and 2)when a sink is on and simulation data shows that
proposed algorithm has better performance in terms of the life span of a network than LEACH
and ELEACH protocols.
Keywords:
Wireless sensor networks, Lifetime, Hierarchical clustering, Hierarchical Routing, Cluster
Topology.

24
1. INTRODUCTION
One of the most important tools for obtaining information and understanding of the environment
which has attracted vast research to itself, is wireless sensor networks. Despite the progress made
in this realm of network, sensor nodes due to small size and contingency placement, still depends
on disposable batteries for its energy supply. Also usually due to using this type of network in
harsh and non-available environments, there is no possibility for recharging or replacing the
batteries. Therefore, one of the most important issues in wireless sensor networks is the issue of
energy restrictions. Also, since the efficiency of sensor networks is highly depended on life span
and coverage of the network, so it’s vital to consider energy saving algorithms while designing
sensor networks with long life span. Because the sensor nodes work with batteries, they always
have a limited life span and recharging for the sensor nodes is always difficult[1]. Operators such
as sensing, communication and calculation use most of sensor’s energy; transmission of
information is considered as the main source of energy consumption[2]. Therefore, theuse of
routing algorithms to reduce energy consumption and proper efficiency of bandwidth is vital.
Since nearly all physical phenomena can be sensed with a variety of sensing elements, finding
applications in any environment for sensor networks is not surprising. Applications of wireless
sensor networks can be divided into two main categories: 1-Viewing or monitoring2-Tracking or
Targeting. Other areas of sensor networks are composed of military, environmental, industrial,
medicinal and etc [3]–[6]. These applications require sensor networks to be implemented mostly
in the form of wireless. Current sensor networks are used on the ground, underwater and
underground. A sensor network based on the type of networkenvironment faces with many
limitations and challenges. We own a total of five types of sensor networks: mobile wireless
sensor networks, multimedia wireless sensor networks, underwater wireless sensor networks and
ground wireless sensor networks[7].More often than not, this type of networks has an inactive or
very limited dynamic node and a central node which all clients directly (single hop) or indirectly
(multi hop) sent their information for it.In direct sending, each sensor sends data directly to the
center, therefor due to the great distance between sensors and center, a vast quantity of energy is
applied for each transmission. In contrast, designs with shorter communication distances can
prolong the lifetime of the network. Therefore, multi-hop connections in this kind of networks are
affordable and more efficient than single-hop connections. Scalability is one of the most
important factors which can be discussed in wireless sensor networks. Due to limited energy of
nodes, the function of all nodes simultaneously causes a drain of energy and reducing the lifetime
of nodes. Hence the question of energy is a crisis in the wireless sensor networks by itself.
Clustering protocol is an appropriate method for improving the lifetime of wireless sensor
networks. In aclustering method, the entire network will be divided into a few clusters. On each
cluster, one node is chosen to be Cluster head. Members of clusters will send the processed
information to cluster head viasingle-hop or multi-hop routes. Then cluster head send the
collected data through single-hop or multi-hop route to sink Fig(1) [8], [9].Clustering approach is
an efficient method for adjusting the load between sensor nodes and prolonging the lifetime of the
network. With clustering, data sent by the nodes inside the cluster are collected by cluster head or
will be sent to sink directly or via intermediary route. So nodes are capable of reducing the
communications overload which is resulted from sending the information to sink directly. The
purpose of using clustering methods in sensor networks is reducing the volume of sending
information and then reducing the required power for communication between nodes. The

clustering process creates a two level
nodes and the lower level consists of sensor nodes which a
nodes act as a gateway between the sink and sensor nodes.
the information which is received by sensor nodes and also is a place where information will be
available to end user. In addition, this structure of sensor nodes and cluster head and sink can be
repeated as many times that is neces
network [10].
Figure 1. Clustering and
1.1.Accomplished Works
According to the sensor node resources which are limited to itself and the fact that sensor usually
don’t have the ability to create a remote connection, so there should be a focus on how to desi
an effective protocol and its energy to preserve the lifetime of
applications of environment. Since the physical layer and
independent of any special software, our attention should be concentrated along the energy aware
protocol specifically network layer with energy efficient routing protocols.Yet the purpose of
routing protocols in the network
such as energy, memory and computing power.
path for energy efficient routing and helping to transfer approved data from sensor nodes to sink
node and also maximizing the lifetime of the network.Scalability as previously remarked, like
other telecommunication network, is
wireless sensor network.If all of the network load should be
routes, volume of traffic on the network will jump significantly with the elongation of the mesh
and will dismiss the network efficiency with increased time lag.So, applied that the sensors
usually haven’t the ability to create a remote connection, the purpose of this approach will limit
the expansion of the web. In order to enhance the capability of
without causing problems in quality of services, it’s
several clusters. In this routing approach, every node plays different roles in the network. A
creates a two level hierarchy which the upper level consists of cluster head
nodes and the lower level consists of sensor nodes which are members of clusters.
nodes act as a gateway between the sink and sensor nodes.Thesink is the location for processing
user. In addition, this structure of sensor nodes and cluster head and sink can be
repeated as many times that is necessary and creates multiple layers in a hierarchy wireless sensor
Clustering and data connection in wireless sensor network[10].
a remote connection, so there should be a focus on how to desi
s energy to preserve the lifetime of the entire network for special
Since the physical layer and the data connection layer
tocol specifically network layer with energy efficient routing protocols.Yet the purpose of
layer is dependent on specific programs and limitations of nodes
such as energy, memory and computing power.The primary role in the network layers is finding a
other telecommunication network, is one of the most significant parameters in designing a
.If all of the network load should be posted on one or some specific
miss the network efficiency with increased time lag.So, applied that the sensors
In order to enhance the capability of network coverage in larger regions
without causing problems in quality of services, it’s recommended to divide the network into
25
of cluster head
re members of clusters. Cluster head
location for processing
user. In addition, this structure of sensor nodes and cluster head and sink can be
wireless sensor
a remote connection, so there should be a focus on how to design
entire network for special
data connection layer are
tocol specifically network layer with energy efficient routing protocols.Yet the purpose of
layer is dependent on specific programs and limitations of nodes
network layers is finding a
one of the most significant parameters in designing a
on one or some specific
miss the network efficiency with increased time lag.So, applied that the sensors
larger regions
to divide the network into

26
clustering algorithm is mainly consisted of two-layer routing in which a layer is used for cluster
heads and the other for routing. This algorithm works on a large number of sensor nodes with
high density and also it’s based on the scalability of routing. The main features of this algorithm
are that it divides the receiver wireless network into several clustersusing specific laws. The main
purpose of a hierarchical protocol (c.a. Custer-based) is the use of an appropriate method for
efficient usage of energy, this is accomplished by utilizing a multi-hop sending as well as the
combining of the information of a cluster in order to reduce the amount of sent data. Hierarchical
protocols can be split into two groups. Monolayer model, in this model, all nodes play the same
role this category includes protocols such as LEACH[11], PEGASIS [12] and modified LEACH
algorithms[13], [14]. Hierarchical model, in this algorithm, each network node can start the
process of generating a cluster. According to predetermined rules, only one node can do that this
category includes protocols such as the TEEN and APTEEN[15][16], HEED[17][18],
EEHRP[19], DWEHC [20] and others.
Heinzelman[11], [12] in has proposed a routing algorithm for sensor networks called Hierarchy
LEACH. LEACH is one of the most popular hierarchical routing algorithms for sensor networks.
LEACH is a clustering protocol that includes distributed information of clusters. LEACH chooses
the number of sensors randomly as cluster head (CH) and distributed the energy between them.
The idea is that the clustering nodes was done based on the received signal from them and cluster
heads was used as routing to the sink. This results in saves energy because instead of all nodes,
cluster heads perform transferring operation. Leach is a perfectly distributed and does not need
the overall information of the network.However, LEACH uses Single hop routing so that each
node can transmit directly to the head and the base station. The optimal number for cluster heads
is approximately 5% of the total number of nodes. All processes such as diffusion and
aggregation of data is done locally within the cluster. To balance power dissipation of nodes, the
cluster heads are randomly changed. We choose a random number r (integer) between 0 and 1. A
node in the current period is cluster head if its number is less than the threshold value as follows:
1
1 ( .mod( ))
( )
0
p
IF n G
p r
T n
p
Otherwise

∈

 −
= 



(1)
where p is the percentage of cluster heads and G is a series of nodes that didn’t become a cluster
in the recent period. Nodes are randomly paired and dynamic clustering increases system lifetime.
So it cannot be used for large networks.
HEED [17] is clustering algorithm for wireless sensor networks in which four targets increase
network lifetime, clustering phase ending after a certain finite number of iterations, minimizing
the control overhead and suitable distribution of clusters are followed by the network. In this
protocol, each node as likely (CHprob) proportional to the amount of its remaining energy
Decides to be a cluster. This decision is temporary at first and after several iterations is
finalized.Nodes that have chosen as cluster head inform this issue to their neighbors. Each of the
neighbors, that didn’t become a member of the cluster already, now is the cluster member. If the

27
neighbor is already a member of another cluster that its residual energy of its cluster head is lower
than the residual energy of new cluster head, this neighbor joins to new cluster head. In addition,
if the neighbor is CH itself, after comparing the amount of its residual energy with the residual
energy of introducing the cluster, the decision to remain as CH or be transferred to the new
cluster. Each cluster, while others decide not to join the cluster, the value of your CHprob doubles
again as neighbors introduced a cluster. Each clusterhead, if decide not to join the other cluster,
double its value of CHprob introduced itself again as cluster head to its neighbors. If the value of
CHprob was greater than one in the node, the node appoints itself as final cluster head. In this
case, the neighbors of this node also will be the final clusters member that no change occurred in
it. At the end of this phase, if the nodes, didn’t receive any cluster introducing message, then
decide to be a cluster head itself.
Energy efficient and effective protocols for wireless sensor networks is a necessity to not only
reduce total energy consumption in the network, but also to balanced evenly distribution of
energy load among the nodes in the network to increase the network lifetime[21].Clustering
protocol is a good way to enhance the lifetime of these networks. When the main station is
mobile, different circumstances should be considered. We will discussthe proposed method in this
article, which includes employing mechanism for layered network environment with respect to
the size of the network environment, choosing the closest layer to sink as the gateway layer, how
to choose the node for the first layer in order to save energy with respect to having that first layer
of coverage is not in trouble, and theclustering and proper selection of cluster head in each
layer separately and finally multi-hop sending the data to the sink. Given that the sink is in
motion and due to the location of the sink, layered environment and transmit data to the base
station we should use a variety of mechanisms.To increase lifespan, reduce the cluster head load,
balance energy the nodes and reduce delays in data transmission process, we will use different
clustering topologies in each hop and level with different methods[22]–[24].We will discuss the
phases of the proposed algorithm and then comparing,simulating and conclusion as follows.
2.THE PROPOSED ALGORITHM PHASES
The proposed algorithm is examined in static and dynamic mode sink, in which some parameters
and assumptions are the same for two modes, also there are assumptions in whichevery one of
them should be considered separately that describing them as follows. In this section and in 5
sections, we will be discussinglayering the network environment, optimum number of cluster
heads, clustering model, symmetrizing the number of cluster and routing mode.
2.1.Layering The Network Environment
In the proposed method, using the relation (2) the network environment will be layered
commensurate with its size and distance to sink.

28
(1)
(1)
( 1)
( ) ( 1)
( )
( )
( 1) ( 1)
(.15)
(.15)
(.15)
i
i i
i
i
i i
L Y
M Y L
IF M L M
L L M
L Then
M M L
Else L L M
−
−
− −
= ×
= −
 
≥ + ×
 
= + ×
 
=  
= −
 
 
= +
 
(2)
In relation(2), y is the length of the network, M is length of network minus layers combined, and
L(I) is the size of (i) the layer. In the allocation of environment to each layer, the relationship (2)
should be checked. Layering mechanism can be started with different values at the beginning,
which this creates different values for Li. Finally, with regard to different values, this relationship
of Y=L1+L2+… +Li should be applied in our layering mechanism.
2.2.The Optimal Number Of Cluster Heads
The size of a cluster, the number of cluster heads in each cluster and selection of cluster heads are
among the most important factors in clustering. Increasing the number of cluster head cause
control information overload and questions of routing. Reducing the number of cluster heads
caused the increase in input load and early energy drain in cluster head. In the proposed method,
optimal number of cluster heads in every layer is different. After layering the environment, the
number of alive nodes in the first layer (N-1) is calculated and then the relationship 3, was used as
optimum number of cluster heads in the first layer.
(1) 1
(1) (1)
%2
( ) 2 2
opt
opt opt
K N
IF K Then K
= ×
 
 
< =
(3)
According to the above formula, if the optimum number of gateway node is a value less than 2,
value of 2 will be inserted, i.e. at least 2 gateway nodes must be fitted. in eq. (3)N1 is the number
of nodes in the first layer.
Kopt(1) determines the optimum number of gateway nodes for first layer. For the next layers, we
define every layer such a way that the optimum number of cluster heads increases with increasing
the distance to sink in which Kopt(i) is calculated through eq. (4):
( ) ( 1)
1
(%5 )
2
opt i i opt i
K N K −
 
= × +
 
  (4)
In the above relations, Ni and Kopt(i) are the number of existent nodes and the optimum number of
clusters in (i)th layer except first layer, respectively. After selecting the optimum number of the
cluster heads, we have different modes for selecting a cluster as a cluster head, in first mode, the

29
same selection structure in LEACH algorithm is used and selecting cluster head is done through a
probability function. Each node chooses a random number between 0 and 1 and if the selected
number is lower than T(n), then it’s selected as current round cluster head.
1
1 ( .mod( ))
( )
0
p
IF n G
p r
T n
p
Otherwise

∈

 −
= 



(5)
P is the probability of selection as cluster head, r is the number of the current round and G is the
set of nodes which haven’t been a cluster head in 1/p recent rounds, Ein is the primary energy of
node and E is the residual energy of a node. In the second mode, we will involve the energy in eq.
(5) too i.e the same E-LEACH algorithm will be used.
1
1 ( .mod( ))
( )
0
in
p E
IF n G
E
p r
T n
p
Otherwise
 
× ∈
 
 
−
=  
 
 
 
(6)
In above relationship, Einis the primary energy of node and E is the energy of a node.
2.3.Clustering Model
Cluster heads have a vital role in communication between layers in the clustering algorithm.
Cluster heads with collecting information from members of each cluster and also from below the
layer cluster head and sending them after compression to above layer cluster heads causes sending
the information to sink which has been done through a hierarchy of routing. To maintain the
energy of cluster heads and maintain the communications like between cluster heads close to sink,
it’s advisable that the number of members of the clusters near to sink be less tocluster heads near
the sink, allocate most of their energy to receive data from lower layers and sending data to upper
layers or sink.
2.4.Symmetrizing The Size Of Clusters
In the proposed method, clustering in each layer except the first layer is done individually and for
each layer after defining the Kopt(i), the numbers of nodes which are not cluster heads in every
layer is calculated and it’s divided to Kopt(i) and the maximum number of nodes in every cluster
head is calculated through this formula:
( )
( )
(.9)
i opt i
i
opt i
n K
C
K
 
 
−
= ×
 
 
 
 
 
  (7)

30
In the above formula, ni,Kopt(i) and Ciare denoting the number of alive nodes, the optimum number
of cluster heads and the maximum number of members of each cluster in (i)th layer respectively.
In this manner, the maximum number of members of cluster head in ith layer equal to Ci. First
each cluster head will give Cimembers and then the nodes which haven’t joined any cluster heads
will join to the nearest cluster head,this approach will reduce wasting energy of nodes. In the first
layer, after determination of the number of gateway node, we will need out the amount the first
layer minus the number of nodes. And then approximately 50% of nodes which are closer to sink
and have more energy considered as dormant nodes to prevent of early discharge of energy in the
first layer. Selecting the gateway layers for each round, was done according to the mentioned
items in order to select the best nodes to send the received information from the bottom layers to
sink.
1 (1)
2
opt
n K
K
−
 
=  
 
(8)
In relation(8),n1,Kopt(1) and K are the number of nodes, the optimum number of cluster heads or
the gateway nodes in the first layer and mandated nodes in the current node, respectively. With
regard to this fact that more than 50% of the nodes are within the first layer of the network, there
will not be any conflict in performance and coverage of the network.
2.5.Routing Model
In the proposed method, routing is done between the cluster head from the lower layers to the
upper ones. The algorithm operates as cluster head of the lowest layer and higher layers’
exchange information. Cluster head in bottom layer will choose the most appropriate cluster head
or the best route with regard to remaining energy and distance to upper layer cluster heads and
inform itself to the chosen cluster head with a status and request message. This action was done
separately for each cluster heads. Algorithm operated similarly for all layers to the first layer
which is the closest layer to the sink. In the first layer according to relationship (3),when the
optimum number of cluster heads is obtained, half of which are closer to the sink are set too
dormant for didn’t consume energy and the rest of the nodes will wake up to sense the
environment and send their information to gateway nodes which is selected to become a cluster
head and is closer to itself. When cluster heads of lower layers receive data from their own
members or other lower layer cluster heads, they will aggregate them, and then there will be two
modes: First: If there was a gateway node in the first layer, cluster heads of bottom layer send
information to the nearest gateway node and data through the gateway node is sent to the sink.
Second mode: If there wasn’t a gateway node in the first layer (all nodes in the first layer have
been eliminated) cluster heads will send their data directly to the sink. The nodes of lower layer
may be the best choice nodes and gateway nodes. The bottom layer nodes can choose the best
gateway nodes and all the nodes will communicate with a gateway node with a high probability
and this reduces power consumption in the first layer nodes and also not clustering this layer will
cause energy storage for nodes because a Phase of cluster formation and recruitment and sending
information to cluster head and cluster aggregation is lost by cluster head, the upper layer which
is the closest layer to sink to sink will focus on sending the information from the lower layer to
sink.

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2.6.Routing Model in Mobile Sink
When the sink is mobile, layering the environment, calculating the optimal number of cluster
heads, model of clustering and symmetrizingcluster size is similar to the static sink mode, only in
time of routing, because sink is mobile, conditions of layering should change when the
coordinates of sink is changing and in thisway sink should declare its position to nodes wen it’s in
movement. To do this, we must consider boundaries and when the ink crossed them, layering is
also changes proportional to its status. The sink is moved in a jump mode. For example,wespecify
in each round that how many meters should a sink move. This is explained in Figure 2.
Figure 2. how to move the sink and changes in layeringenvironments.
In this section we will examine theagent of change in the speed sink in lifetime of wireless sensor
networks, in order to do so, we will consider assumptions to our stimulation where for this
purpose we will consider an environment of 200 × 200 by taking 100 sensor network nodes. move
speed of sink is considered as a variable of X that is calculated in each round, for example, X =
43 means that sink moves, 43 meters in each round.

32
Figure 3. Calculating the distance traveled.
X = t × (pi / 180) × r(9)
X is the distance traveled in each round, r is the radius of the relevant circle. Pi is the amount
equal to 3.14.
3. SIMULATION
In this section the results of simulation of the proposed clustering algorithm, analysis and
comparing the results with previous clustering protocols will be discussed. The simulation was
carried out using MATLAB software. Given that we have a mobile sink, thenat firstwe will
consider a basic station, which in each round its position varies based on the speed of the sink.
The position of the initial parameters of wireless sensor networks for the simulation of100 nodes
is shown in Table 1.
Table 1. wireless sensor network basic parameters.
Parameter value
Area Size 200×200 m2
Initial energy in each Node 0.5 (J)
Ecpu 7(nJ/bit)
Eelec 50 (nJ/bit)

33
Eamp 0.659 (nJ/m2
)
Packet Size 4000Bit
The initial position of the sink 100×300 m2
The Following assumptions are considered in the simulation:
• Network environment, is the square of the number of sensors specified.
• Sensors have been released randomly.
• Sensors are aware of their location.
• ID is the unique for each sensor.
• Each node senses the data alternately and always has a data to send.
• The volume of sensed data by node is the same.
• Perform data compression to minimize the amount of data
• Sink is mobile and runs at a constant speed around the environment.
We considered the speed of sink based on each round so that the speed of 10 meters per round is
specified.
3.1. Energy Model
Energy consumption in wireless sensor network consists of three parts: data, data acquisition and
data processing. Energy model is brought in e.q. (10) [22, 24].
ቐ
P୘ሺKሻ = Eୣ୪ୣୡ ∗ K + Eୟ୫୮ ∗ dγ
∗ K
PୖሺKሻ = Eୣ୪ୣୡ ∗ k
Pୡ୮୳ሺKሻ = Eୡ୮୳ ∗ k
(10)
PR and Pcpu represent the energy consumption of sending, receiving and processing of K bits data.
Eelec, Eamp and Ecpu represent the energy consumption (NJ / bit) for sending any bits on the radio
radius, the energy to send with a radius of more than Eelec and energy per bit is required for
processing. According to equation (10) the total energy consumed by k is like in relation(11).
P୘୭୲ୟ୪ = Pୗୣ୬ୢ + Pୖୣୡୣ୧୴ୣ + P୔୰୭ୡୣୱୱ
P‫کل‬ = k൫2Eୣ୪ୣୡ + Eୡ୮୳ + Eୟ୫୮ × dγ
൯ (11)
In (11) eq.we see that, energy consumption has a direct relationship with the data length. If the
send data isless, we will use less energy. If Transmission distance is less than the threshold,
energy consumption will berelated to d2
. If the transmission distance is greater than the threshold,
it is associated with d4
. Therefore, the less the transmission distance is, energy consumption can
be reduced.

International Journal of Wireless Mobile Networks (IJWMN) Vol. 8, No. 4, August 2016
34
3.2.Simulation Results
In this section simulation, we will compare the results of the proposed algorithms and ELEACH
and LEACH algorithms. MATLAB software is used as asimulator. The results are evaluated
based on two modes: first mode in static sink and second, in mobile sink, results are described
separately as follows.
3.2.1.Static Sink
The sink is static in the outfield in this mode.
Figure 4. Compare of lifetime between the proposed methods and LEACH and ELEACH protocols.
Figure 5. Comparison of number of dead sensor nodes between the proposed methods and LEACH and
ELEACH protocols.

35
As seen in the figure, our proposed methods have improved 49 percent in death of first node than
LEACH and 34% than ELEACH and has a 69% improvement in death of last node than LEACH
and 34% percent than ELEACH. In Table (2) the impact of increasing the number of nodes of
sensor in networks, according to the assumptions in table (1)is discussed.
Table 2. impacts of the number of nodes on networks lifetime in satatic sink.
We can see in Table (2), with an increase of nodes in the environment network also increases the
network lifetime. Because the number of nodes is directly proportional to the network's lifetime,
the more numbers of nodes is the longer lifetime of the network.
In the following table the impacts of the size of environment on the network's lifetime were
compared and assume that the numbers of nodes in different environment is equal to 100 nodes.
Table 3. impact of the size of environment in network lifetime in static sink.

36
According to Table 4.3, if the size of the environment become larger and the number of sensor
nodes does not change, the network lifetime will be decreased.
3.2.2. Mobile sink
The sink in this mode, is moving in a specified direction around the environment.
Figure 6. Comparing the lifespan of the proposed methods and LEACH and ELEACH protocols.
Figure 7. Comparing the number of dead sensor nodes in the proposed methods and LEACH and ELEACH
protocols.

37
As seen in the figure, in proposed methods compared with other protocols, there has
been an improvement by 51 in the death of the first nodethan the LEACH and 38% in
the death of the last node than the ELEACH and 74% than the LEACH and 52% than
the ELEACH. The impact of increasing the number of sensors nodes on networks,
according to assumptions in Table (4) was investigated in table (1).
Table 4. Effects of number of nodes in network lifetime in mobile sink.
by observing table (4) we found that triggering a sink in this case results in increase the lifetime
of the network. In the case of mobile sink, our proposed methods have a better performance than
traditional methods, here, the increase in the number of nodes will increase the network lifetime.
The following table compares the impact of changes in the size of environment of network on the
lifetime of the network, like static sink. It is assumed that the number of nodes in different
environment is equal to 100 nodes.
Table 5. The influence of the size of environment on the network lifetime in mobile sink.

38
According to Table (3) and (5), the size ofthe network environmentis correlated with the lifetime
of the network, the larger the size of the larger environment, the decreased lifetime of network.
3.2.3. Change Of Pace In Sinks
This section examines the impact of sink’s speed on lifetime of networks. We will set the sink
speed in three modes, assuming that the size of simulated environment is equal to 100 × 100 and
100 nodes.
Table 6. The impact of changing the speed of sink on network lifetime.
According to Table (6)increase in sink speed will reduce the network lifetime, then sink speed is
directly related to energy consumption in network sensor. Therefore, the increase in sink speed
increases energy consumption of sensors and ultimately reduces the lifetime of the network.
4.CONCLUSION AND RECOMMENDATIONS
Problem of routing based on clustering in wireless sensor network aimed at reducing energy
consumption and maintaining net coverage was investigated in the current study. To achieve this
goal, we attempt to layered the environment based on the size of the network environment, so we
can have a dynamic layering in terms of network environments size. This protocol is, in fact, a
routing approach based on layering environment, where every independent layer starts clustering
and sends information to the top layer to reach the sink, in fact, using layering and multi-hop
routing algorithms, we will reduce energy loss during data transmission. Also in each layer in the
protocol, the optimum number of nodes and summarization of the sizes of the cluster is done
independently. Similarly, by moving a sink in each round when the sink is spinning the
environment, layers varies according to different situations of the sink.

39
Based on the comparisons carried out in different modes, it can be said that increase in node
sizes,the size of the environment, homogeneous or heterogeneous of environment has a
tremendous impact on the lifetime of sensor networks. In a way that increases in the sizes of
nodes will prolong the lifetime of the network. Increase in size of environment reduces the
lifetime of the network and the heterogeneity of the environment will increase the lifetime of
environment.
The most important innovation of this research, is a specific mechanism based on layered
environments that reduce energy consumption in sensors which are further away from the sink
which applying this mechanism had a significant effect in reduction of energy consumption and
balance networks and increasing longevity and maintaining network coverage.The second
innovation is a cluster topology control method so that the numbers of members of each cluster
head are almost evenly distributed and also has a tremendous impact on energy consumption of
cluster head. The other innovation in this research is providing a way to control the nodes in the
first layer of coverage so that the network coverage maintains and power of nodes which hasn’t
chosen as gateway nodes is not lost. This has done with marinating of nodes.
As future research work that can be done to get the protocol presented in this study, the following
suggestions are presented:
- Applying other useful parameters for the formation of clusters.
- Applying different structure for layering the environment that considers how large or small first
layers it is, by taking the environment.
- Use of different criteria for selecting the cluster and improvement of the proposed cost function.
- Apply the appropriate parameters for the gateway nodes.
- Choose a useful mechanism for cluster heads to select the best cluster head of top layer to send
information.
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Authors
Ali Sedighimanesh is a graduate student in the School of Electrical and Computer
Engineering, University of Science and Technology, Qazvin Islamic azad University
(QIAU),Iran. he received a Bachelor degree from University of Science and Technology
Parand, iran. His research areas are wireless communications and Network. and a Master
degree from QIAU. His current research interests include wireless and mobile
communications, cooperative communications, optimization theory on communications.
Mohammad Sedighimanesh is a graduate student in the School of Electrical and Computer
Engineering, University of Science and Technology, Qazvin Islamic azad
University(QIAU),Iran. he received a Bachelor degree from University of Science and
Technology Zanjan, iran. His research areas are wireless communications and Network. and
a Master degree from QIAU. His current research interests include wireless and mobile
communications, cooperative communications, optimization theory on communications.
Javad Baqeri is a graduate student in the School of Electrical and Computer Engineering,
University of Science and Technology, Qazvin Islamic azad University(QIAU),Iran. he
received a Bachelor degree from University of Science and Technology Shomal, iran. His
research areas are wireless communications and Network. and a Master degree from QIAU.
His current research interests include wireless and mobile communications, cooperative
communications, optimization theory on communications.

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