G-DEEC: GATEWAY BASED MULTI-HOP DISTRIBUTED ENERGY EFFICIENT CLUSTERING PROTOCOL FOR WIRELESS SENSOR NETWORKS

International Journal on Cybernetics & Informatics (IJCI) Vol. 4, No. 5, October 2015
DOI: 10.5121/ijci.2015.4502 19
G-DEEC: GATEWAY BASED MULTI-HOP
DISTRIBUTED ENERGY EFFICIENT
CLUSTERING PROTOCOL FOR WIRELESS
SENSOR NETWORKS
Sheenam
M. Tech Research Scholar
Department of Electronics and Communication Engineering, Punjabi University, Patiala,
India
ABSTRACT
Wireless sensor network is composed of hundreds and thousands of small wireless sensor nodes which
collect information by sensing the physical environment. The sensed data is processed and communicated
to other sensor nodes and finally to Base Station. So energy efficient routing to final destination called base
station is ongoing current requirement in wireless sensor networks. Here in this research paper we propose
a multi-hop DEEC routing scheme i.e. G-DEEC for heterogeneous networks where we deploy rechargeable
intermediate nodes called gateways in-between cluster head and base station for minimizing energy
consumption by sensor nodes in each processing round thereby increasing the network lifetime and
stability of wireless sensor networks unlike DEEC.
KEYWORDS
Wireless Sensor Networks, Heterogeneous Protocol, Gateway, DEEC, Energy Consumption.
1. INTRODUCTION
Wireless sensor networks can be viewed as a move leading in direction of wireless technology
from wired one. These are network of tiny and cheap application-centric battery powered
electronic devices called sensor nodes with on board sensing, processing and communicating
capabilities connected to other nodes via Radio, infrared and optical media. The main function of
these nodes is to sense the environment for temperature, humidity, pressure, intensity, pollutant
levels, chemical concentrations etc. according to the application they are being installed for and
report this gathered information after processing to Base Station. So routing of information from
sensor nodes to Base Station with lesser consumption of battery is one of the current concerns in
this field. Processing of data in network is cheaper than data transmission. In convention routing
approaches like DT (Direct Transmission), sensor nodes directly send data to base station thereby
nodes away would require more energy for routing information [1]. In MTE (Minimum
Transmission Energy), sensor nodes near to base station die faster as they are more prone to a part
communication. So there comes the concept of hierarchical routing using clustering where one
sensor node having higher energy is considered as Cluster Head (CH). This type of

20
communication is called single hop (i.e. transfer of information from sensor nodes to CH and then
to base station) routing.
Many single hop routing protocols for homogeneous environment where each sensor nodes is
equipped with same initial energy are LEACH (Low Energy Efficient Clustering Hierarchical
LEACH), PEGASIS (Power-Efficient Gathering in Sensor Information Systems), TEEN
(Threshold Sensitive Energy Efficient Network), HEED (Hybrid Energy-Efficient Distributed
clustering) etc. And the single hop routing in heterogeneous environment where nodes are having
different initial energy is done by SEP (Stable election protocol) and DEEC (Distributed Energy
Efficient Clustering) etc. Many hierarchal routing schemes for saving the transmission distance
have already been proposed for wireless sensor networks but still Cluster Head still suffers long
distance transmissions. So here we propose a multi-hop routing protocol using intermediate
rechargeable transmission devices known as gateway nodes between cluster head and base station
as a defense mechanism for energy constraint battery powered sensor nodes prolonging the
processing time of sensor nodes and also reducing the average transmission distance between
sensor nodes and Base station.
The paper is organized as follows: Section 2 gives brief layout of related protocols in previous
years; Section 3 provides detailed theory about proposed technique and model proposed for
sensor network area. Section 4 includes the simulation results of network parameters; section 5
includes the conclusions and future scope of research.
2. RELATED WORK
Many different routing protocols have been already proposed for energy efficient routing for
increasing the lifetime and stability of networks. Hierarchical routing includes clustering with CH
selection on basis of initial energy. LEACH was the first routing protocol to introduce single-hop
routing for reducing communication overhead by introducing the concept of clustering in
homogeneous network field and selecting higher energy node as cluster head. There is
randomized rotation of CH positions so as not to drain out battery of single sensor node.
Simulation results showed reduction in energy consumption as compared to non clustered
conventional Direct Communication protocol. Clustering concept was applied to all
homogeneous protocols like LEACH [2], PEGASIS [3] and HEED [4]. CHs so formed in
clustering perform fusion of aggregated data and pass this data to BASE station. All these
homogeneous schemes perform badly in heterogeneous environment. The lower energy nodes die
more frequently over higher energy nodes as there is no criterion for discriminating the nodes on
energy basis. So here comes SEP [5] where the author considered two level heterogeneity and CH
selected on basis of initial energy in each node. Nodes with more initial energy have chance to
become CH than other nodes. Further advancement in criterion of CH selection is made in DEEC
[6] where CHs are selected on basis of ratio of residual energy and average energy of each node.
Nodes with higher residual energy are probable to be CH than other nodes. Advancements in
DEEC was done in DDEEC [7] where advance nodes will have same probability of becoming CH
as normal nodes when they are as same in energy to lower ones unlike DEEC where advance
nodes continue to become CH even after energy depletion. Further E-DEEC (Enhanced DEEC)
[8] proposed three level heterogeneity for DEEC algorithm where third kind of nodes called super
nodes are been taken in network field. Simulation results showed E-DEEC performed better than
SEP in terms of network lifetime. More over EE-TDLC [9] was proposed where two tier CH

21
selections are proposed. At first tier data is transmitted from sensor nodes to primary CH selected
on basis of residual energy then in second tier data is transmitted from primary CH to secondary
CH selected from primary CHs then to base station or directly to base station depending to
whichever is nearest. G-SEP [10] is advancement over SEP where CH is selected not only on
initial energy basis as in SEP but with residual energy. SEARCH [11] is also a kind of
advancement over DEEC which achieves decrease in time of transmission by frequent updating
of G value i.e. available number of nodes for becoming CH. The unfavorable situation exists in
LEACH, SEP and DEEC where G value reduced to zero which is not updated until next round of
transmission. So SEACH achieves better results in comparison to LEACH, SEP and DEEC.
Further EEHC (Energy Efficient Heterogeneous Clustered Scheme) [12] for Wireless Sensor
Networks, where the effect of heterogeneity of nodes in terms of their energy in WSNs that are
hierarchically clustered has been studied. An energy efficient heterogeneous clustered system for
WSNs based on weighted election probabilities of each node to become a cluster head according
to their residual energy in each node is proposed. Simulation results showed the proposed
heterogeneous clustering approach is more effective in prolonging the network lifetime compared
with LEACH. In [13] author proposed TDEEC (Threshold Distributed Energy Efficient
Clustering) protocol by following thoughts of DEEC and modifying the threshold value based on
which the node decide to become CH or not as shown in equation below
{
* ( )+
}
In [14] authors‟ proposed heterogeneous SEP protocol (H-SEP) for increasing lifetime of
heterogeneous wireless sensor networks. They discussed two types of sensor nodes i.e. normal
and advanced. H-SEP increases the network lifetime and it is energy efficient than SEP. More
packets are sent to the base station. In this 2-level heterogeneity is introduced in terms of the node
energy. A significant improvement was observed in the lifetime because the number of rounds is
more with 2-level H-SEP in comparison with SEP protocol. In [15] authors proposed Balanced
and Centralized Distributed Energy Efficient Clustering (BCDEEC) for heterogeneous wireless
sensor a network which is an extension of DEEC where each advanced node select itself to be
gateway. BS is located at center of network field. Probability is such chosen that expected
number of gateways is and probability of Nm advanced nodes becoming gateways
is . Simulation results showed improvement in stability period compared to DEEC and
SEP.
In [16] authors proposed performance evaluation of cluster-based routing protocols used in
heterogeneous wireless sensor networks, authors analyzes the performance of Distributed energy
efficient clustering (DEEC) protocol in terms of energy consumption, network lifetime and
energy balancing. A new clustering protocol called Clustering Technique for Routing in wireless
sensor networks (CTRWSN) has been proposed for prolonging the network lifetime. Simulation
results shows that the lifetime of the proposed routing protocol is 40% longer than DEEC and
showed that energy is well balanced as compared to DEEC.

22
In [17] authors proposed Extended Stable Election Protocol which considers three levels of
heterogeneity in terms of nodes initial energy termed as normal, intermediate and advance nodes
in wireless sensor networks. In SEP-E assume a case where „b‟ intermediate nodes equipped with
„μ‟ times and „m‟ advance nodes equipped with „α‟ times more energy than normal nodes
respectively and modified their epoch (no of time a node to be CH in a round) for intermediate
and advance nodes by modifying their election probabilities to be cluster head, to balance energy
consumption of sensor nodes. Simulation settings and results showed that Enhanced SEP
performs well than LEACH. It shows 1.94 times and 2.09 times improvement in terms of FDN
and throughput.
In [18] authors introduced gateway based homogeneous energy-efficient routing protocol (M-
GEAR) for Wireless Sensor Networks (WSNs). The sensor nodes are divided into four logical
regions on the basis of their location in the sensing field and Base Station (BS) is installed out of
the sensing field and a gateway node at the centre of the sensing area. If the distance of a sensor
node from BS or gateway is less than predefined distance threshold, the node uses direct
communication and the rest of nodes are divided into two equal regions whose distance is beyond
the threshold distance. Cluster heads (CHs) are selected in each region which is independent of
the other region. Results showed that proposed M-GEAR outperforms LEACH in terms of
network life time by 40% and also in terms of throughput by a factor of 5.
In [19] authors proposed an improved algorithm called DEEC with Isolated Nodes (DEEC-WIN)
where the mechanism of nodes joining a cluster is improved. Some nodes nearer to base station
communicate directly without being part of any cluster. Simulation results showed DEEC-WIN
consumes less energy in comparison to LEACH and DEEC which helps to extend the network
lifetime.
In [20] authors proposed an Away Cluster Head Scheme (ACH) for energy efficient clustering
protocols which make clusters even in number of nodes in each cluster so energy dissipation in
each round is comparable and cluster head will be considered as normal node if the distance from
nearest CH is less than 12m. Simulation results showed DEEC-ACH performs well than DEEC as
the adjacent and very close nodes are made CHs in DEEC.
In [21] authors proposed Cluster Head Re-election Protocol (CRP) for heterogeneous wireless
sensor networks where re-election of cluster heads is done from the elected ones having
maximum residual energy which is taken as final cluster head. Simulation results shows 46%
decrease in average residual energy as compared to LEACH and SEP.
In [22] authors proposed the new clustering algorithm based on multitier network topology to
prolong the lifetime of wireless sensor network called Multitier Algorithm Protocol (MAP) where
nodes of same energy transmit data through two tier CHs located at tier 1 around BS and tier 2
around tier 1 before they reach the Base station located at centre of network. CHs are selected
based on fuzzy logic. Simulation results showed there are still 95 alive nodes up to 8000 iteration
where SEP and DEEC with zero alive node up to 5000 iteration, thus prolonging the lifetime of
network.
In [23] authors proposed a modified energy efficient protocol named as EM-SEP. In the research,
author modified CH selection criteria by balancing energy consumption to increase lifetime of the

23
network and also to increase stability period of WSN. Even authors worked on the concept if
there is more than one SN available to become CH then it would pick the node having highest
energy. Simulation results showed that EM- SEP performs 5% in terms of stability period and 5%
in lifetime of network than SEP.
3. NETWORK MODEL OF PROPOSED PROTOCOL (G-DEEC)
In this research, we consider a 100m*100m network field with n sensors deployed randomly in
sensor field. Some assumptions for the proposed model shown in figure 1 are as:
 BS (50,125) is deployed away from network field. Sensor nodes and base station are
stationary after deployment.
 BS is aware about its position in network field and about location of sensor nodes with the
help of GPS (Global positioning system).
 9 gateway nodes are deployed at pre-planned distance in network field.
 Gateway nodes deployed systematically are stationary.
 We use heterogeneous nodes with different initial energy values.
 Sensor nodes deployed randomly over the sensor field.
Figure1. Network model of G-DEEC (100m*100m field)
○ Normal nodes
◊ Advanced nodes
× Base Station
* Gateway nodes
Here we used first order radio energy dissipation model proposed as in LEACH [2] shown in
figure 2 where the transmitter dissipates energy to make the electronic circuit and power amplifier
work. According to the propagation model the energy consumed in transmitting L-bit message
with achievable value of signal to noise ratio over distance d between transmitter and receiver is
given as

24
{ (1)
Figure 2. Radio dissipation model
Where is measure of energy consumed by electronic circuit in sending data from transmitter
side to receiver side. In this model both free space ( power loss) and multipath fading
( power loss) channels are used depending on distance between two communicating ends.
Here is minimum (threshold) distance between communicating ends called as threshold
distance calculated as
√ (2)
4. G-DEEC Protocol
In this section, we present the detailed proposed protocol G-DEEC. Sensor nodes with two level
of heterogeneity are considered i.e. m1 fraction of nodes called advance nodes are given „α1 %
additional energy as compared to normal nodes unlike DEEC where m fraction are provided with
% additional energy. Sensor nodes are randomly distributed over the field with some
intermediate nodes called gateway deployed on field at pre-determined distance covering the
whole network field so that head of each cluster formed is near to that gateway so as to reduce the
transmission distance from cluster head to base station with the help of these gateway nodes. Here
we deploy 9 gateway nodes which are taken approximately on basis of number of cluster heads
formed. 4 gateways are placed at four corners of sensor field and 4 gateways at center of four
boundaries and one at center of field. Moreover the gateway nodes deployed are rechargeable
proving to be back-up for exhausted network power sources. The function of gateway nodes to
collect aggregated data from CHs and fuses this data and forward to base station. Sensor nodes
near to gateway can transfer data directly to gateway nodes. At a time only one CH will transfer
data to gateway node and incase of failure of one gateway node, other nearby gateway node can
be used for data forwarding. The CH selection is done on basis of weighted election probabilities.
The weighted election probability for normal nodes is as:
Transmitter TX
Amplifier
Receiver
L- bit (l, d)
L-bit
d

25
α
(3)
The weighted election probability for advance nodes is as:
(4)
Where is residual energy of node and is average energy given as:
( )
(5)
Where, n is total number of nodes, is total energy, r is current round and R is total rounds of
the network lifetime. Average energy is just used as reference energy for each node. It is the ideal
required energy that each node should own in current round to keep the network alive to greatest
extent. After election of CH having maximum energy; a single CH is selected per round for
transmitting data. For this, a random number is generated and then comparing random number
with threshold value. If random number is less than threshold value then it becomes CH for that
particular round. The threshold is calculated differently for normal and advance nodes. Threshold
function for normal nodes given as:
{ * ( )+
} (6)
Where r is ongoing round number, g‟ is set of possible normal nodes that have not been cluster
head in last ⁄ rounds.
Threshold function for advanced nodes given as:
{
[ ( )]
} (7)
Where r is ongoing round number, g‟‟ is set of possible advance nodes that have not been cluster
head in last ⁄ rounds.

26
5. PERFORMANCE EVALUATION
5.1 Network parameters
Table I: Network Parameters
n 100
E0 (Initial energy
of normal nodes)
0.5J
l ( Message Size ) 4000 bits
50nJ/bit
EDA 5nJ/bit/signal
10pJ/bit/m2
0.0013pJ/bit/m4
d0 70 m
r (No. of Rounds) 2000
m1 30%
α1 300%
m 20%
350%
Simulation of our proposed protocol is done in MATLAB. We consider a 100m*100m field with
n sensor nodes deployed randomly and 9 rechargeable gateway nodes. We ignore the effects of
signal inference and collision. Radio characteristics and other parameters are given in Table I
above.
5.2 Performance parameters
5.2.1 Network lifetime: It is defines as time interval till the network is operational which is
calculated based on number of half dead nodes and alive nodes.
5.2.1.1 Half dead Nodes- It is defined when sensor nodes had spent half of their total energy i.e.
it is partially dead and partially alive (i.e. energy & 0). These partially alive nodes can
still be part of network operation and thereby increases the lifetime of network. Greater the
number of half dead nodes, better the lifetime of network.
5.2.1.2 Alive Nodes- It is defined as sensor nodes that still have not used all of their energy even
after processing (i.e. energy 0). Greater the number of alive nodes more is the lifetime of the
network.

27
5.2.1.3 Dead Nodes- Sensor nodes are considered dead after they consume all of its initial energy
(i.e. energy < 0) provided to them i.e. they are of no use in network processing. Lesser the
number of dead nodes more is the lifetime of the network.
5.2.2 Stability Period (First Node Dead):
It is defined as the time interval between start of network operation till the death of first sensor
node. Later the first dead node comes, greater the stability period.
5.2.3 Residual Energy: It is defined as measure of total remaining energy in the network. It is
used to analyze the energy consumption of sensor nodes in each round. Lesser the energy
consumption better is the protocol.
5.3 Simulation Results and Analysis
5.3.1 Network lifetime: Simulation results for number of half dead nodes, alive nodes and dead
nodes are considered for analyzing the lifetime improvement. In DEEC, 20 % of nodes are given
350% additional energy whereas in proposed G-DEEC, 30% of nodes are given 300 % additional
energy. In figure 3, we show the results for number of half dead nodes. Nodes are considered
dead after consumption of full 0.5 joule initial energy but they are half dead when they have not
consumed their all of initial energy. At round 2000, number of half dead nodes are 0 whereas they
are coming out to be 30 in case of proposed G-DEEC. More the number of half dead nodes more
is the network lifetime.
In figure 4, we show the simulation results of number of alive nodes. At round 2000, number of
alive nodes are 20 in DEEC whereas this number has increased to 61 in case of proposed G-
DEEC. Greater the number of alive nodes greater is the lifetime of network.
Figure 3 and 4 figure shows the increment in number of half dead nodes and number of alive
nodes in proposed G-DEEC, making the network to be operational for longer time as compare to
single hop DEEC. Half Dead Nodes shows 30 % improvement w.r.t. initial 100 nodes whereas
alive nodes shows 41 % improvement w.r.t initial 100 deployed nodes. Both parameters
combined shows 35.5% improvement in network lifetime.

28
Figure 3. Number of Half Dead Nodes
.
Figure 4. Number of alive nodes
Figure 5 shows the plot of number of dead nodes at round 2000. The number of dead nodes at
round 2000 is 80 in old DEEC whereas they are coming to be 39 in proposed G-DEEC. There is
decrement in number of dead nodes making the network processing time longer thereby
increasing the network lifetime of sensor network. Both the plots of alive nodes and dead nodes
are vice-versa to each other.

29
Figure 5. Number of dead nodes
TABLE II Improvement table of network lifetime in G-DEEC
Operation at 2000 iteration DEEC
(Improvement
w.r.t. initial
values)
G-DEEC
(Improvement
w.r.t. initial
values)
Overall
Improvement
Number of Half Dead Nodes 0 (0%) 30 (30%) 30%
Number of Alive Nodes 20 (20%) 61 (61%) 41%
Number of Dead Nodes 80 (20%) 39 (61%) 41%
5.3.2 Stability Period (First Node Dead): Simulation results of first node dead are shown in
figure 6. The first node coming to be dead at about 1178 in DEEC whereas it is becoming dead at
1438 in proposed G-DEEC. The first node in proposed G-DEEC dies after 260 processing rounds
as compared to DEEC. This leads to increase in stability of network by 13%.

30
Figure 6. Interval plot of first node dead
5.3.3 Residual Energy: The plot of energy consumption per round is considered in figure 7. At
round 1500, energy remained per round is about zero joules in DEEC whereas it is about 0.1
joules in proposed G-DEEC. Thereby energy consumption is reduced in proposed protocol as
shown in figure7. So network will remain operational for longer time with same battery power in
proposed G-DEEC protocol as compared to old DEEC protocol. So the rechargeable gateways
proved to be beneficent in reducing the energy consumption of sensor nodes.

31
Figure7. Analysis of remaining energy
TABLE III Improvement table of stability and residual energy in G-DEEC
Operation at 2000 iteration DEEC
(Improvement
w.r.t. initial
values)
G-DEEC
(Improvement
w.r.t. initial
values)
Overall
Improvement
First Dead Node (Stability Period) 1178 (58.9%) 1438 (71.9%) 13%
Residual energy (joules) at round 0 (0%) 0.1 (20%) 20%
6. CONCLUSIONS AND FUTURE SCOPE
In this research, an energy aware energy efficient G-DEEC has been proposed. Number of half
dead nodes, number of alive nodes and number of dead nodes in proposed G-DEEC protocol
shows 30%, 41 %, 41% overall improvement respectively with respect to DEEC, thus showing
37.33% overall improvement on an average. The first sensor node dying much later in proposed
G-DEEC as compared to DEEC showing 13% overall improvement in stability of network. There
is 20% overall improvement in residual energy. This work can further be extended to multi-level
heterogeneity i.e. inclusion of super nodes and other intermediate nodes of different energy and
can also be implemented on ETX metric scheme.

32
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AUTHORS
SHEENAM received her Bachelor‟s of Technology in Electronics and Communication
Engineering from Swami Vivekanand Institute of Engineering &Technology, Banur
affiliated to Punjab Technical University, Jalandhar, Punjab, India in 2012, and completed
her degree in Masters of Technology in Electronics and Communication Engineering from
Punjabi University, Patiala, Punjab, India in 2015. She yet has published two papers on
wireless sensor networks. Her research interests include routing and energy management in
wireless sensor networks etc.

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