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REECH-ME: Regional Energy Efficient Cluster Heads based on Maximum Energy
Routing Protocol
Arslan Haider
A Bachelor thesis submitted to the Department of Electrical Engineering
COMSATS Institute of Information Technology Islamabad
In partial fulfillment of the requirements for the degree of
Bachelor of Science in Electrical (TELECOM) Engineering
Dr. Nadeem Javaid, Supervisor
Department of Electrical Engineering
COMSATS Institute of Information Technology ISLAMABAD
November 2013
Copyright © 2013 Arslan Haider
All Rights Reserved
ABSTRACT
In this paper, we propose Regional Energy Efficient Cluster Heads based on Maximum Energy
(REECH-ME) Routing Protocol for Wireless Sensor Networks (WSNs) . The main purpose of this
protocol is to improve the network lifetime and particularly the stability period of the network.
In REECH-ME, the node with the maximum energy in a region becomes Cluster Head (CH) of
that region for that particular round and the number of the cluster heads in each round remains the
same. Our technique outperforms LEACH which uses probabilistic approach for the selection of
CHs. We also implement the Uniform Random Distribution Model to find the packet drop to make
this protocol more practical. We also calculate the confidence interval of all our results which helps
us to visualize the possible deviation of our graphs from the mean value.
Keywords: [A comma-separated list of descriptive words for search purposes]
ACKNOWLEDGMENTS
[Acknowledgements should be simple, in good taste, and fit on one page]
Contents
Table of Contents vii
List of Figures ix
1 Introduction 1
2 Background and Related Work 5
2.1 Motivation....................................... 9
3 Introduction To Some Basic Protocols 11
3.1 Low Energy Adaptive Clustering Hierarchy (LEACH) . . . . . . . . . . . . . . . . 11
3.2 Threshold sensitive Energy Efficient sensor Network protocol . . . . . . . . . . . . 13
3.3 Stable Election Protocol (SEP) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.4 Distributed Energy Efficient Cluster formation Protocol (DEEC) . . . . . . . . . . 16
4 First Order Radio Model 19
5 Proposed Scheme : REECH-ME 23
5.1 NetworkModel.................................... 24
5.2 Clustering And Routing Techniques . . . . . . . . . . . . . . . . . . . . . . . . . 25
6 Simulations Results 27
6.1 ConfidenceInterval ................................. 27
6.2 NetworkLifetime .................................. 29
6.3 PacketsSenttoBS .................................. 30
6.4 PacketDrop ..................................... 32
6.5 ScalabilityAnalysis.................................. 35
6.6 Short Comparison of Protocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
7 Conclusion And Future Work 39
vii
List of Figures
2.1 Clustering in LEACH Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
4.1 RadioModel ..................................... 20
5.1 RegionsinREECH-ME................................ 25
6.1 NumberofAliveNodes................................ 30
6.2 Number of Packets Sent to BS Per Round . . . . . . . . . . . . . . . . . . . . . . 31
6.3 Number of Packets Received at Sink after Packet Drop . . . . . . . . . . . . . . . 33
6.4 Number of Packets Dropped . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
6.5 NumberofAliveNodes................................ 36
6.6 Number of Packets Sent to BS Per-Round . . . . . . . . . . . . . . . . . . . . . . 37
ix
x
LIST OF FIGURES
List of Tables
6.1 SimulationsParameters................................ 28
6.2 ComparisonTable................................... 38
xi
xii
LIST OF TABLES
Chapter 1
Introduction
WSNs are used in environmental monitoring, security, medical applications, etc. The sensor nodes
are usually randomly deployed in a specific region. These sensor nodes collect their data and send
it to the Base Station (BS) via some routing protocol. These nodes cannot be recharged from time
to time to keep them alive. They must follow a protocol which must ensure the efficient use of
their power, so that those nodes may serve as long as possible without any external assistance. A
routing technique plays a key role in their energy consumption. Many of the routing protocols use
clustering as their routing technique. So clustering plays a very important role in prolonging the
stability period and network life time. The CHs collect the data from all the nodes in their cluster,
aggregate it and then finally send it to the BS. These sensor nodes must follow a certain routing
protocol to send their data efficiently to the BS. The main objective of all routing protocols is to
minimize the energy consumption so that the network lifetime and particularly the stability period
of the network may be enhanced. By network lifetime we mean the time duration from the start of
the network till the death of the last node, whereas, stability period means the time duration from
the start of the network till the death of the first node.
A network can be reactive or proactive. In proactive network, nodes send their data to the BS
or CH only when they detect a change and keep the transmitter off when they do not detect any
1
2
Chapter 1 Introduction
change in the environment. Our proposed protocol is proactive. This approach is more energy
efficient as compared to the reactive protocols. As in reactive protocols, nodes keep sending the
data to the BS all the time. So, they quickly consume their energy as compared to the proactive
protocols. In proposed protocol, the BS is at the centre of the field, i.e, if the area of the network is
100mx100m, the BS would be at a position (50m,50m) .
By the term homogenous, we mean that initially all nodes in the network have the same amount
of energy. Similar to LEACH [1], REECH-ME is also based on the homogenous set of nodes. It
all depends on the routing technique that how efficiently it consumes this energy to increase the
life time and particularly the stability period of the network.
Clustering may be static or dynamic. In Static Clustering the clusters are not changed through-
out the network life time. Whereas in Dynamic Routing, the clusters change depending on the
network characteristics. LEACH uses Dynamic Clustering and its CHs are chosen on probabilistic
basis. So the number of its CHs and the size of the clusters may change after every round. That is
why its number of CHs is not optimum. So the number of packets sent to the BS is also not fixed
as they depend upon the number of the CHs.
In the proposed scheme, the total area is divided into 9 regions. These are named as R1, R2,
R3, ... , R9 as shown in Fig. 2. The region R1 is closest to the BS and uses Direct Communication
as its routing technique. In Direct Communication, every node sends its data directly to the BS. All
other regions, i.e R2 - R9, do not use Direct Communication. Instead, they form CHs to send their
data to the BS. REECH-ME uses Static Clustering, so clusters throughout the network lifetime
remain the same. Each region except R1 is called a cluster and each cluster has only one CH for a
particular round. Other nodes of regions R2-R9 send their data to the BS via CH of their region.
In our protocol, the CH is chosen on the basis of maximum energy. It means that in any round
the node having the maximum energy becomes the CH. So the energy utilization becomes very
efficient as well as the number of the CHs in a round becomes fixed. As there are 8 regions which
3
form clusters, so there would be 8 CHs in each round which is the optimum number.
As in any real case scenario, the number of packets received at the BS is never equal to the
number of packets sent to the BS. This is because some packets are lost due to certain factors.
Those factors may include interference, attenuation, noise, etc. That is why we use the Uniform
Random Distribution Model [5] for the calculation of packets drop. This makes REECH-ME more
practical.
We also calculate the Confidence Interval of all our results. It helps us to visualize the deviation
of the graphs from the mean value. Where, the mean value is calculated by taking the results of 5
simulations, and then taking their mean.
The remainder of this paper is organized as follows. In Section II, Motivation for this protocol is
given. Section III contains a brief introduction of the radio model. Section IV shows our proposed
scheme in details. Section V elaborates all the results and comparison of DREEM-ME. Section VI
addresses the future work. Finally, Section VII concludes our research.
4
Chapter 1 Introduction
Chapter 2
Background and Related Work
Efficient energy consumption in WSNs is a very active research topic from last few years. Many
researchers have proposed different protocols to improve the network lifetime and stability region
in a WSN. Routing is the backbone of the protocol because the consumption of energy depends
upon routing[36].
DR-LEACH [4] was proposed by K. Latif et al.. In this technique, the network area is divided
into different regions. Nodes of the region which is closest to the BS use direct communication of
data. All other regions use clustering for routing of data, in which a CH is responsible for the data
aggregation and transmission. During every round, fixed number of CHs is selected. DR-LEACH
also uses multi-hop communication between clusters. In this way, energy utilization efficiency is
also increased and hence, lifetime and stability region of the network is enhanced.
S. Faisal et al. proposed Z-SEP [10] which is an extension of SEP [7]. In this protocol, the
network field is divided into 3 zones on the bases of energy levels. The Zone-0 has normal nodes
that use direct communication for data transmission. Whereas, Zone-1 and Zone-2 use clustering
based technique for data transmission. The CH selection is done by setting a threshold. Similar to
LEACH, every node generates its random number. If this random number is less than or equal to
the threshold, that node becomes CH. Nodes become members of cluster on the basis of received
5
6
Chapter 2 Background and Related Work
signal strength from CHs. CHs then assign a TDMA schedule for the nodes during which nodes
can send data to CH. This technique also proved helpful in improving network lifetime and stability
region.
Aslam et al. [21] proposed CEEC which uses three energy levels of nodes i.e. normal, advance
and super nodes. In this technique, The network area is divided in three equal regions and every
region is homogeneous, i.e., contains nodes with same energy. Base Station (BS) centrally selects
optimum number of CHs. The regions are arranged in ascending order from the BS in terms of
their initial energy. So, region of normal nodes is the closest and the region with super-nodes is the
farthest. CEEC is 100
In [22] authors used Error Control Coding (ECC) for efficient energy consumption. Z.Abbas et
al. presents the efficient encoder selection that transmits power with respect to its critical distance
which results in energy saving in WSNs. Encoder selection is performed by using critical distance
which is estimated from coding gain of that encoder. ECC in this context, becomes energy efficient
as encoders and their transmit powers are selected adaptively, that results in energy saving to these
particular encoders.
In [20] N. Javaid et al. proposed EDDEEC. It is a three level heterogeneous protocol which
assigns different probabilities to each energy level node to become CH, so, that nodes with high
energy become CHs more frequently as compared to the nodes with less energy. In EDDEEC,
authors defined a residual energy level threshold. Under that threshold, all normal, advance and
super nodes have same probability for CH selection. EDDEEC [20] is adaptive energy aware
protocol which dynamically changes the probability of nodes for the selection of CHs. This is a
balanced and efficient way to distribute equal amount of energy between sensor nodes.
HEER [18] was proposed for both homogeneous and heterogeneous environments. This pro-
tocol takes into account the initial and residual energies of the nodes for the selection of CHs.
Data transmission in HEER depends on two threshold values, i.e., Hard Threshold (HT) and Soft
7
Threshold (ST). In this technique, the nodes sense their environment repeatedly and if a parameter
from the attributes set reaches its HT value, the node switches on its transmitter and transmits data.
The Current Value (CV), on which first transmission occurs, is stored in an internal variable in the
node called Sensed Value (SV). Now the nodes will again transmit the data to their respective CH
if:
CV −SV ≥ST (2.1)
If the CV differs from SV by an amount equal to or greater than ST, only then the nodes
transmit their data. It results in a reduced number of transmissions and hence, network lifetime is
improved.
B. Manzoor et al. [19] proposed Q-LEACH for the efficient energy consumption of nodes.
According to this approach sensor nodes are deployed in a territory. In order to acquire better
clustering, the network area is divided into four regions. Through this division, optimum positions
of CHs are defined. Moreover, transmission load of other transmitting nodes is also reduced. By
doing such sort of partitioning, better coverage of the whole network is achieved.
In [22] authors improved network lifetime and stability region by adapting both open-loop and
closed-loop feedback processes. By using this approach, they divided the whole network area
into three logical regions on the basis of threshold for each region. In this way, the authors were
also able to achieve minimized packets overhead. This protocol proved very efficient in energy
consumption of nodes.
Authors in [26] compared routing protocols DSDV, DYMO and OLSR for MANETs and
VANETs. Their simulation work found that overall DSDV performs fine for throughput i.e. maxi-
mum number of packets reached their destination successfully.
H-DEEC and MH-DEEC [32] routing protocol are proposed as energy aware adaptive cluster-
ing protocols for heterogeneous WSNs. In H-DEEC, the network is divided into two parts on the
8
Chapter 2 Background and Related Work
bases of initial and residual energy. Normal nodes elect themselves as CHs and Beta nodes col-
lect data from CHs and send it to BS using multi-hopping. Unlike SEP and DEEC, H-DEEC and
MH-DEEC perform better in a heterogeneous wireless sensor field. Moreover, it also considers the
problem of locating BS outside the network.
In [29] authors introduce adopted authentication approach for protecting our Ad-hoc wireless
network by even- odd function. In this function, mobile node compute and generates random even
or odd number during signaling process. If first node generates random odd number then next node
computes and generates a random even number. There are number of attacks existing in wireless
communication in different application of communication field. This scheme will secure the whole
wireless network from the outsider attack.
In [27], Ad-LEACH is proposed for WSNs. This is an energy efficient routing protocol which
is based on legacy static clustering approach. In this scheme, CH selection mechanism is inherited
from DEEC whereas, protocol architecture is adopted from LEACH protocol. Simulation results
validate the performance efficiency of Ad-LEACH in the case of two level heterogeneous networks
as compared to LEACH and DEEC.
Based on the analysis of energy management, the main factors of energy consumption are:
sensing the data, data processing and radio communications where the radio communication is
the major part of energy consumption. In the WSNs, the realization of energy-efficiency could be
improved using different energy efficiency techniques[31].
When the sink is static, the probability of coverage holes is greater[34]. After some rounds,
there is a possibility that the energy of some part of the network becomes low and that results in a
coverage hole. Coverage holes are the greatest enemies of a WSN because we cannot monitor the
whole network area because some nodes are not functioning due to depletion of their energy.
2.1 Motivation
9
2.1 Motivation
The main objective of a routing protocol is to efficiently utilize the energy of the nodes. This is
because these nodes are not rechargeable and in order to make them useful for a longer period of
time, routing protocols have been proposed. Routing protocols improve the lifetime of a network
and specifically the stability period of a network. Protocols [2] , [4] , [10], [13], [21], [24], [17],
[18], [19] and [20] are proposed to achieve these goals. As shown in Figure 1, LEACH uses
dynamic clustering. Hence, its clusters change after every round.
As the CH selection in LEACH is on the basis of probability, the optimum number of CHs is
not achieved. So the energy is not efficiently utilized. The area coverage in LEACH is also not
very efficient. This is because it treats the whole area as a single area and the nodes are deployed
in it at once. So some of the area is left unattended. To efficiently utilize the energy and to improve
the coverage area, many researchers have introduced some effective approaches [2] , [3] , [4] and
[10]. In these approaches, the total area is divided into small regions and these regions are treated
separately for the nodes distribution and it improves the area coverage. In our protocol, we also
use the approach of dividing the total area into smaller areas. We use the direct transmission for the
area (R1) closest to the nodes as shown in Fig. 2. We use the static clustering in all other regions.
The CH selection is based on the maximum energy of a particular node in a round. It means that
the node with the highest energy is chosen as the CH for that particular round. So the energy is
very efficiently utilized and the area coverage is also improved.
10
Chapter 2 Background and Related Work
`
X
Normal Node
`Cluster Head
`
Base Station
X
050 100
50
100
Figure 2.1 Clustering in LEACH Protocol
Chapter 3
Introduction To Some Basic Protocols
In this section, we discuss some of the basic protocols [1, 6, 7, 11] in the field of WSNs:
3.1 Low Energy Adaptive Clustering Hierarchy (LEACH)
It is one of the earliest clustering routing protocols for WSNs to increase the lifetime of WSNs.
It is based on homogeneous networks. It involves dynamic clustering which means its clusters
change in every round. CHs in each round are selected on the basis of probability instead of their
energy. LEACH also performs data fusion to compress the amount of data being sent from cluster
to base station. Thus LEACH reduces energy dissipation and increases network lifetime. LEACH
has different variants such as [35], [31] and [19].
For each round, sensors elect themselves as CH with certain probability. The status of these
CHs is broadcasted within the network. Each node then associates itself with the CH that has the
highest signal strength in that region. After the formation of a cluster, CH creates a schedule for
the nodes to transmit data. In this way, nodes transmit data to the CH in their allocated time and are
in sleep condition for the rest of the time. So, the energy dissipation of individual sensor node is
minimized in this manner. When the cluster-head receives all the data from nodes within a cluster,
11
12
Chapter 3 Introduction To Some Basic Protocols
it aggregates that data and sends compressed data to the base station. In this way, more energy is
dissipated in CHs quickly. LEACH has no fixed number of CH and a CH is self-elected in every
round. It results in different number of packets sent to the BS in every round.
The operation of LEACH is broken into rounds. Each round consists of two phases, a set-up
phase and a steady-state phase. In set-up phase, the clusters are organized and in steady-state phase
data is transmitted to the base station. Generally steady-state phase is longer than set-up phase to
minimize overhead.
At the beginning, when clusters are formed, each node decides whether it should become a CH
for the current round or not. This decision is taken by determining the suggested percentage of
CH and number of times a node has been a CH. A node n makes a decision by taking a number
between 0 and 1 randomly. If the number is less than a certain threshold T(n), the node becomes
CH for the current round. The threshold is determined as:
T(n) =
p
1−p(rmod 1
P)if n
ε
G
0 otherwise
(3.1)
Where G is set of nodes that have not been selected as CHs in previous 1/P rounds, P is sug-
gested percentage of CH, r is current round. By using this threshold, each node has the chance of
becoming a cluster-head at some stage within 1/P rounds. During initial round zero (r=0), each
node has the probability P of becoming a cluster-head. Similarly if nodes become cluster-head in
round zero, it canâ ˘
A´
Zt be cluster-head for the next 1/P rounds. The node that has elected itself as
cluster-head for the current round, broadcasts an advertisement message to all nodes within the net-
work. The non-cluster-head nodes have to keep their receivers on. This advertisement is received
by non-cluster-head during set-up phase. After receiving this message, each sensor node decides
to join a certain cluster for the current round. This decision is taken according to the strength of
received signal. So the non-cluster head will join a cluster-head whose received signal strength is
3.2 Threshold sensitive Energy Efficient sensor Network protocol
13
large. In this way the energy required for communication between non-cluster head and cluster-
head is less. In certain cases where received signal strength is same for more than one cluster-head,
a random cluster-head is selected.
Data transmission begins after formation of clusters and allocation of TDMA schedule. Each
node sends data to CH during allocated transmission time. The nodes are in sleep condition for
the rest of the time to reduce energy dissipation. The receiver of the CH must be switched on to
receive from all nodes. After receiving data from all nodes, the CH compresses it to a single signal
and transmits it to the base station.
3.2 Threshold sensitive Energy Efficient sensor Network pro-
tocol
Routing protocols for wireless sensor networks can be classified into two classes, proactive and
reactive protocols. LEACH protocol is considered as proactive protocol since it sends reports to
the base station periodically. In reactive protocols, when an event of interest occurs, it is reported
to the base station. Reactive protocols are generally used for time critical applications where quick
response to changes in the sensed parameters is required. Threshold Sensitive Energy Efficient
Sensor Network Protocol (TEEN) is a reactive protocol designed for time critical applications. In
TEEN, nodes are arranged in hierarchical clustering scheme in which certain nodes act as cluster
head (first or second level). After cluster head is elected, the user sets attributes for it. When the
cluster head receives these attributes, it broadcasts the attributes (Hard Threshold (HT) and Soft
Threshold (ST) values) to all member nodes of the cluster. The Sensor nodes sense the data and
transmit only when the sensed data exceeds HT. HT is the minimum value above which values are
noted. Sensed value (SV) is an internal variable which stores the transmitted sensed value. The
sensor again senses data and when its value exceeds the ST, which is the minimum change in sensed
14
Chapter 3 Introduction To Some Basic Protocols
value, it starts transmitting data. In this way, TEEN conserves energy since sensor nodes senses
data continuously but transmits only when data is above HT. ST further reduces transmission,
which could have otherwise occurred due to little or no change to level of sensed attributes. Since
cluster-head performs extra computations, its energy consumption is more than other nodes. This
problem is resolved by giving equal chance to every node to act as cluster-head for a fixed cluster
period. We can reset the attributes during every cluster change time. No transmission from nodes
to cluster-head occurs if the sensed value is below HT, so the cluster-head will not be aware of
death of a sensor node. By giving smaller value to ST on cost of high energy due to frequent
transmission, a clear scenario of the network can be obtained.
Similar to LEACH, every node in the cluster is given a time slot for data transmission using
TDMA schedule. Soft threshold is used to on or off the sensing node while hard threshold is
activated while sensing value is being changed. Here two level of CH are being used. On the
basis of two thresholds, data transmission can be easily controlled i.e. only the required data be
transmitted. In this way it reduces the energy of transmission. Since TEEN is complement for
reacting to large changes in the sensed attributes, it is suitable for reactive scenes and time critical
applications.
3.3 Stable Election Protocol (SEP)
LEACH uses randomized rotation of cluster-head for balancing energy load among all sensors.
This approach is generally applied to heterogeneous environment. But in real life, sensor node is
not able to keep energy uniformity. Therefore the concept of heterogeneity is introduced. Stable
Election Protocol (SEP) heterogeneous aware routing protocol which is used to extend the time
period before the first node in the network dies. In SEP, each node has weighted probability to
become cluster head which depends upon the remaining energy in each node relative to average
3.3 Stable Election Protocol (SEP)
15
energy of the network.
In SEP, nodes have different amount of initial energy. â ˘
AŸmâ ˘
A´
Z describes a fraction of total
nodes â ˘
AŸnâ ˘
A´
Z, which have â ˘
AŸaâ ˘
A´
Z times more energy other nodes. These nodes are called
advance nodes and the remaining nodes having less energy are called normal nodes. In case of het-
erogeneous nodes, LEACH creates a large unstable region. This is because all remaining advance
nodes have nearly same amount of energy, so the process to elect cluster head becomes unstable
and no cluster head is elected and advance nodes become idle. SEP improves the stable region
using some fraction of advance nodes (m) and some additional energy factor (a) to differentiate
normal nodes from advance nodes. In SEP, the advance nodes have more chances to become clus-
ter head than normal nodes. In heterogeneous network with advance and normal nodes, a priori
setting of popt not affected but the systemâ ˘
A´
Zs total energy varies. If Eois initial energy of normal
node then (1+a)Eobecomes initial energy of advance nodes. So, initial energy of heterogeneous
system becomes:
n(1−m)Eo+nmEo(1+a) = nEo(1+a.m)(3.2)
SEP depends upon initial energy of the nodes. In SEP, each node has knowledge of the whole
networkâ ˘
A´
Zs energy and decides whether to become a cluster head depending on its own re-
maining energy. A weight is assigned to popt, which is equal to initial energy of each node
divided by initial energy of normal node. pnrm is weighted probability for normal node and
popt for advance nodes. For advance and normal nodes, the weighted probabilities are given as:
pnrm =popt/(1+a.m)For advance nodes, probability will be: padv =popt/(1+a.m)∗(1+a)
T(Snrm)is threshold for normal node and T(Sad v)is threshold for advance nodes and given as:
T(Snrm)=(pnrm/(1−pnrm(r∗mod(1/pnrm)))i f SnrmG′(3.3)
Where r is current round, Gâ ˘
A´
Z is set of nodes that were not cluster head in previous 1/P
adv
16
Chapter 3 Introduction To Some Basic Protocols
rounds. T(Snrm)is threshold of n(1-m) normal nodes. Now for advance nodes:
T(Sadv)=(P
adv/(1−P
adv(r∗mod(1/P
adv)))i f Sadv ∈G′′ (3.4)
Where Gâ ˘
A´
Zâ ˘
A´
Z is set of nodes that were not cluster head in previous 1/P
adv rounds. So the
total number of cluster head per round in heterogeneous network is equal to: n.(1−m)∗pnrm +
n.m∗P
adv =n.P
adv As LEACH is sensitive to heterogeneity, it goes to unstable region quickly. SEP
is aware of heterogeneity, so it extends the stable region by assigning weighted probabilities to the
nodes for cluster head election. SEP performance does not depend individually on values of m and
δ
s but on their product. The advance nodes have δ
s.m times extra initial energy. SEP improved the
networks lifetime and stability region more than LEACH and TEEN.
3.4 Distributed Energy Efficient Cluster formation Protocol (DEEC)
DEEC is designed for Multi-level heterogenous environment. The criteria for selecting cluster
head in DEEC depends upon a probability which is based on ratio between residual energy of
every node and average energy of the whole network. So nodes with high initial and residual
energy have more chances to become cluster head than nodes with low energy. Thus DEEC can
prolong the stability period by heterogeneous aware clustering algorithm.
DEEC is a proactive protocol designed for heterogeneous networks. Initial and residual energy
is taken into account for the selection of CH. The node with higher initial and residual energy has
greater probability to become a CH. In a two-level heterogeneous network, we have two categories
of nodes; normal and advanced nodes. m.N and (1-m).N is the number of normal and advanced
nodes respectively. Where N is the total number of nodes and m is the fraction of advanced nodes.
Initial energy of normal and advanced nodes is given by E0and E0.(1+a)respectively. The term
(1+a)indicates that the advanced nodes own atimes more energy than normal nodes. The total
3.4 Distributed Energy Efficient Cluster formation Protocol (DEEC)
17
initial energy of the two level heterogenous networks is given by:
Etotal =N(1−m)E0+NmE0(1+a) = NE0(1+am)(3.5)
The total initial energy of the multi-level heterogeneous networks is given by:
Etotal =E0(N+
N
∑
i=1
ai)(3.6)
The probability of a normal node to become CH is calculated by the following equation
P
i=P
opt Ei(r)/(1+am)¯
E(r)(3.7)
where ¯
E(r)is the average energy at round rof the network and Ei(r)is the residual energy at round
rof node i.
The probability of an advanced node to become a CH is given by:
P
i=P
opt (1+a)Ei(r)/(1+am)¯
E(r)(3.8)
This model can be easily extended to multi-level heterogeneous networks
P(si) = P
opt N(1+ai)/(N+
N
∑
i=1
ai)(3.9)
As we are assuming uniformly distributed node so distance of cluster members from CH is
dtoCH =M/√2
π
k(3.10)
where M is the length or width of the square region of area M×M. Average distance between base
station and CH is
dtoBS =0.765M/2 (3.11)
DEEC was also a big step forward. It achieved better stability period and network lifetime as
compared to LEACH, TEEN and SEP.
18
Chapter 3 Introduction To Some Basic Protocols
Chapter 4
First Order Radio Model
REECH-ME uses the same radio model as used by [1, 4, 6, 7]. It is a simple first order radio model
in which the radio dissipates Eelec = 50 nJ/bit for powering the transmitter or receiver circuitry and
ε
amp = 100 pJ/bit/m2for the transmitter amplifier to achieve an acceptable Eb/No as shown in Fig.
1. Transmitter circuitry also consumes EDA = 50 nJ/bit to aggregate the data received by the normal
nodes. We also take in account the d2energy loss due to channel transmission. Thus, to transmit a
k-bit message distance d the energy is given as:
do=√
ε
f s
ε
mp
(4.1)
if d<do
ET x(k,d) = Eelec ∗k+
ε
f s ∗k∗d2(4.2)
if d≥do
ET x(k,d) = Eelec ∗k+
ε
mp ∗k∗d4(4.3)
Reception Energy:
ERx(k) = Eelec ∗k(4.4)
19
20
Chapter 4 First Order Radio Model
Where Eelec is the energy dissipated per bit to run the transmitter or receiver circuit,
ε
f s and
ε
mp depend on the transmitter amplifier. A basic radio model is shown in Fig. 1.
Transmit
Electronics Tx Amplifier
Receive Electronics
ETx (d)
EElec * k
amp * k * d2
ERx
EElec * k
k bit Packet
k bit Packet
d
Figure 4.1 Radio Model
It can be seen that same energy is required to switch on the transmitter and receiver circuitry.
This is because both use Eelec ×kenergy. So, it can be concluded that this radio model is symmetric
such that the energy required to transmit a bit of data from node A to B is the same as the energy
21
required to transmit a bit of data from node B to node A for a given SNR. We assume that all sensors
are always sensing the environment and sending the data to their CH or BS. We also assume that
nodes transmit fixed number of data to their CH and BS, i.e., kis same at all times.
22
Chapter 4 First Order Radio Model
Chapter 5
Proposed Scheme : REECH-ME
An efficient routing protocol is the one which consumes minimum energy and provides good cov-
erage area. Minimum consumption of energy leads towards better network lifetime and particularly
the stability period. Whereas good coverage area is useful in getting the required information from
the whole network area. Because if the coverage area is not good, then their would be some small
areas left unattended in the network. These unattended areas are referred to as coverage hole. The
primary objective of a routing protocol is to achieve minimum energy utilization and full coverage
area. Many researches have addressed such matters as in [2], [3] and [4]. Different approaches are
used to solve this problem, one of which was the division of the network field area into sub areas.
In the proposed technique, we divide the network area into sub areas as explained in the following
subsection. The target which we want to achieve is to improve the network coverage as well as
network lifetime and stability region. So, we have localized the whole network and divided the
network into sub-regions that helps in avoiding the coverage hole [8] and [11]. The following are
the main parts of our proposed model:
23
24
Chapter 5 Proposed Scheme : REECH-ME
5.1 Network Model
In LEACH, the CHs are elected on probabilistic basis and threshold is calculated for each node.
Cluster is formed on the basis of received signal strength from the CH and its associate nodes. In
our protocol, we divide the area in different regions as shown in fig. 3. First of all, the whole
area is divided into two concentric squares. The inner square is itself a region and is referred to
as Region 1 or R1. The outer square is divided into 8 regions, 4 of which are rectangles and 4 are
squares as shown in fig. 3. The boundaries of all regions are taken as:
• R1 - (25 - 75, 25 - 75)
• R2 - (50 - 100, 75 - 100)
• R3 - (0 - 25, 75 - 100)
• R4 - (0 - 25, 50 - 75)
• R5 - (0 - 25, 25 - 50)
• R6 - (0 - 50, 0 - 25)
• R7 - (50 - 100, 0 - 25)
• R8 - (75 - 100, 25 - 50)
• R9 - (75 - 100, 50 - 75)
Each region contains fixed number of nodes. R1 contains 20 nodes, whereas, regions R2-R9
contain 10 nodes each. The BS is located at the center of the field. Fixed number of nodes are
randomly distributed in their defined regions.
5.2 Clustering And Routing Techniques
25
`
X
`Normal Node `Cluster Head
XBase Station
0 10050 7525
25
50
75
100
R1
R3 R 2
R4
R5
R6
R7
R8
R9
R1-R 9 Regions
Figure 5.1 Regions in REECH-ME
5.2 Clustering And Routing Techniques
In R1, nodes use direct communication to send their data to the BS. All regions except R1 use
clustering as their routing technique. Unlike LEACH in which CHs are selected on probabilistic
basis, REECH-ME selects a node as the CH of that region if that node has the maximum energy
before the start of that round. Initially, all nodes have the same amount of energy and any node
26
Chapter 5 Proposed Scheme : REECH-ME
can become the CH for first round. So, a node is chosen randomly to become the CH of that
region for the first round. All other nodes send their data to CH which receives the data from all
the nodes, aggregates it and sends it to the BS. When the first round is completed, the amount of
energy in each node would not be the same. This is because the utilization of energy depends upon
the distance between the node/CH which is transmitting and the CH/sink which is receiving. The
larger the distance, the greater energy is consumed. And smaller the distance, smaller energy is
consumed. As distance for transmission and reception is different for different nodes, the energy
consumption will also be different for different nodes. For every next round, the CH is selected on
the basis of their energies. The node with the maximum energy in a region becomes the CH of that
region for that particular round.
Chapter 6
Simulations Results
In this section, we assess the performance of our protocol using MATLAB. In our protocol to-
tal area is divided into 9 regions. Region 1 uses direct communication as its routing technique.
Whereas, all other regions use clustering which is based on maximum energy of a node in that
particular region. The node with the maximum energy in a particular region becomes the CH of
that region. Normal nodes of a region send their sensed data to BS via CH of their own region. In
this way, after every round, a new node which has the maximum energy in that region is chosen as
the CH of its region. The simulation parameters are given in Table 1.
6.1 Confidence Interval
The nodes are randomly distributed in a certain region. They may be placed any where in a partic-
ular region. Any new distribution change the location of nodes in network area. In this way, the
calculations regarding their lifetime, stability, instability region, packet drop, etc. slightly vary. So,
keeping this fact in mind, we also calculated the confidence interval of all our results. Confidence
interval helps us to visualize the deviation of the graphs from the mean value. Where, the mean
value is calculated by carrying out the simulations for 5 times, and then taking their mean. We
27
28
Chapter 6 Simulations Results
Parameter Value
Network Size 100m x 100m
Node Number 100
Initial Energy of Normal
Nodes
0.5J
ET X 50nJ
ERX 50nJ
EDA 5nJ
Packet Size 4000 bits
Probability of Packet Drop 0.3
Sink Location (50m,50m)
Table 6.1 Simulations Parameters
6.2 Network Lifetime
29
calculate the confidence interval of all our graphs.
6.2 Network Lifetime
Alive nodes refer to those nodes which have sufficient energy to sense and transmit data. The
lifetime of a network depends upon the number of alive nodes. As long as there is even one alive
node in the network, its lifetime counts. So the lifetime of a network refers to the time period
from the start of the network till the death of the last node. First of all, we compare the lifetime
of LEACH with our REECH-ME. The fig. 4 shows the confidence interval of alive nodes. We
calculate the confidence interval because it helps us to visualize the deviation of the graph from its
mean value. Whereas, the mean value is calculated by carrying out 5 simulations and then taking
their mean.
Fig. 4 shows the number of alive nodes. It can be seen that the network lifetime of our protocol
is 66% more than that of the LEACH, i.e, around 2500 and 1500 rounds respectively. The stability
period is a time duration from the start till the death of the first node. The stability period of our
protocol is 79% better than the LEACH.
REECH-ME uses maximum energy based CH selection. Whereas in LEACH, the clustering
is based on the probability. Maximum energy based clustering helps to utilize the energy of only
those nodes which have the maximum energy in their regions. So the energy of all nodes is very
efficiently utilized.
We always obtain the optimum number of CHs in a round, i.e 8 because we divide the whole
area into 9 smaller regions. And 8 regions use clustering and each region has only one CH. So the
number of clusters and CHs is always fixed. Whereas in LEACH, the number of CHs is never the
same and hence, the energy utilization is not efficient. The instability period is the time duration
between the death instants of the first node and the last node alive in the network. The instability
30
Chapter 6 Simulations Results
0 500 1000 1500 2000 2500 3000
0
10
20
30
40
50
60
70
80
90
100
Rounds
Number of Alive Nodes
Confidence Interval
LEACH
REECH−ME
Figure 6.1 Number of Alive Nodes
region in our protocol is 40% more than that of LEACH.
6.3 Packets Sent to BS
The average packets sent to the sink in LEACH are less as compared to REECH-ME as shown in
fig. 5. This is because on an average, there would be around 10 CHs (not always exactly 10) in a
6.3 Packets Sent to BS
31
0 500 1000 1500 2000 2500 3000
0
5
10
15
20
25
30
Rounds
Packets Sent To Base Station per Round
Confidence Interval
REECH−ME
LEACH
Figure 6.2 Number of Packets Sent to BS Per Round
round. And we know that the normal nodes do not send their data directly to the sink. Instead, they
send their data to the BS via the CH. So on an average, there would be around 10 packets sent per
round. Whereas in our Protocol, 20 nodes are present in the region which is closest to the sink and
they send their data directly to the sink. In all the other 8 regions, 8 nodes would be CHs in each
round. So, on an average there would be 28 packets sent per round. As the number of the dead
32
Chapter 6 Simulations Results
nodes increases, the number of packets sent to the BS decreases. In LEACH, the first node dies
in approximately 1000 rounds. So, after that round, the number of packets sent to the sink also
gradually decreases in correspondence with the number of dead nodes. Similarly, in our Protocol,
the average number of packets received also gradually decreases with the increase in number of
dead nodes.
6.4 Packet Drop
Ideally when a CH sends its data to the BS, all the packets are received successfully without any
loss, i.e, the number of packets sent to the BS are equal to the number of packets received at the
BS. But in reality it does not happen. Whenever the data is sent to BS from a CH, some of its
packets do not reach the destination. This is called Packet Drop. The reason behind this packet
drop may be the interference, attenuation, noise, etc. In our protocol, we have implemented the
uniform random distribution to calculated the packet drop. This makes our protocol more practical.
We used 0.3 as the packet drop probability value. Fig. 5 shows the number of packets sent to the
BS per round, whereas, fig. 6 shows the number of packets received at the BS. Its can be observed
that the number of packets received at the BS is less than the number of packets sent to the BS.
Thus, packet drop makes our protocol more applicable and practical as well.
Ideally, whenever the data is sent to the sink, it reaches without any packet loss. But in real
situations this ideal condition does not exist. That means that when data is sent to the sink from
the CHs, some packets are lost. To show this packet loss, we use the Uniform Random Distribu-
tion Model[5] to find the packet drops. We calculate the packet drop by taking the packet drop
probability as 0.3 and then calculate the confidence interval as shown in fig. 5, 6 and 7. Due to
the packets drop, the number of packets that is received at the sink would be less as compared
to the number of packets sent by the CHs. So in our protocol, the number of packets received at
6.4 Packet Drop
33
0 500 1000 1500 2000 2500 3000
0
5
10
15
20
25
30
Rounds
Number of Recieved Packets at BS(Packet Drop)
Confidence Interval
LEACH
REECH−ME
Figure 6.3 Number of Packets Received at Sink after Packet Drop
the BS fluctuates around 20 packets. Whereas in LEACH, the number of packets received at the
BS fluctuates around 7. The number of received packets decreases as the number of dead nodes
increases. As the stability region of LEACH is smaller as compared to our protocol, the number
of received packets starts to decrease from around 1000th round. Whereas in our protocol, this
decrement in the number of the received packets starts from around 1800th round.
34
Chapter 6 Simulations Results
0 500 1000 1500 2000 2500 3000
0
5
10
15
20
25
30
Rounds
Packets Dropped
Confidence Interval
REECH−ME
LEACH
Figure 6.4 Number of Packets Dropped
In REECH-ME the average number of packets that is sent by the nodes to the BS is 28. By
applying packet drop probability of 0.3, the average number of packets which are dropped is around
8. Similarly on an average the total number of packets which are sent to the BS from the nodes is
10. And 0.3 probability of packet drop does not allow all the packets to reach the destination , i.e.
BS. The average number of packets dropped due to this probability in LEACH is 3. This behavior
6.5 Scalability Analysis
35
can be seen in Figure 7. The number of packets dropped in REECH-ME is more as compared to the
number of packets dropped in LEACH. And the reason behind it is that in REECH-ME the average
number of packets which is sent to the BS is more than that of the LEACH. The 0.3 probability on
both the protocols will result in different number of packets dropped in both protocols.
6.5 Scalability Analysis
We also analyze the scalability of our protocol by changing the number of total nodes. We compare
the number of alive nodes and packets sent per round in each scenario. The simulation results are
shown in the fig. 8 and 9 given below: Varying the number of nodes can vary the delay of packets
reception. So, by increasing the number of nodes can increase the delay because if TDMA is used,
then most of the nodes will have to wait for their turn to send the data. This increment in delay
is crucial for time critical applications. But, in our case, we have only considered number of alive
nodes and number of packets sent to BS per round. Its can be seen that changing the number of
nodes does not effect the number of alive nodes and number of packets sent per round.
6.6 Short Comparison of Protocols
Table 2 shows a short comparison of network lifetime and stability region between TEEN, LEACH,
DEEC and REECH-ME in terms of rounds. We can see that REECH-ME outperforms others in
terms of network lifetime and stability region.
36
Chapter 6 Simulations Results
0 500 1000 1500 2000 2500 3000
0
100
200
300
400
500
600
700
800
900
1000
Rounds
Number of Alive Nodes
300 nodes
500 nodes
700 nodes
1000 nodes
Figure 6.5 Number of Alive Nodes
6.6 Short Comparison of Protocols
37
0 500 1000 1500 2000 2500 3000
0
50
100
150
200
250
Rounds
Number of Packets Per Round
300 nodes
500 nodes
700 nodes
1000 nodes
Figure 6.6 Number of Packets Sent to BS Per-Round
38
Chapter 6 Simulations Results
Protocol Stability Period(Rounds) Lifetime(Rounds) Environment Classification
TEEN 1221 1947 Homogeneous Reactive
LEACH 910 1455 Homogeneous Proactive
DEEC 1395 2461 Heterogenous Proactive
REECH-ME 1950 2510 Homogeneous Proactive
Table 6.2 Comparison Table
Chapter 7
Conclusion And Future Work
Our proposed technique uses static clustering and CHs are selected on the basis of the maximum
energy of the nodes. This results in fixed number of CHs in each round and the optimum number of
CHs is also maintained. We implemented Packet Drop Model to make our protocol more practical.
We also implemented confidence interval to find the possible deviation of our graphs from the
mean value, where mean value is calculated by simulating our protocol 5 times and then taking its
mean. We compare the results of our protocol with that of the LEACH. REECH-ME outperforms
LEACH in network lifetime, stability period, area coverage and throughput. Thus, this scheme
enhances the desired attributes, i.e, minimum energy consumption, maximum stability period,
better lifetime and throughput allot as compared with LEACH. In future, Routing Link Matrices
can also be applied on this proposed technique. Routing can be done by adapting many different
approaches as done in [14], [15] and [16]. Application of Routing Link Matrices on the proposed
scheme can be useful in achieving efficient consumption of energy in the network. We aim to
introduce multiple QoS parameters [23]. Mobility constraints also help to achieve better network
lifetime similar to [25, 39, 40]. We can also use sink mobility to improve the energy utilization
efficiency as done in [30, 37, 38]. In future, we also aim to introduce efficient MAC protocols for
WSNs. [33].
39
40
Chapter 7 Conclusion And Future Work
Bibliography
[1] Wendi Rabiner Heinzelman, Anantha Chandrakasan and Hari Balakrishnan “Energy-Efficient
Communication Protocol for Wireless Microsensor Networks” Proceedings of the 33rd Hawaii
International Conference on System Sciences, 2000.
[2] R. Sugihara, R. Gupta, “Sensor localization with deterministic accuracy guarantee” Proceed-
ings IEEE INFOCOM, 2011 , pp. 17721780.
[3] M. Jin, S. Xia, H.Wu and X. Gu, “Scalable and fully distributed localization with mere con-
nectivity” Proceedings IEEE INFOCOM, 2011, pp. 31643172.
[4] K. Latif, A. Ahmad, N. Javaid, and Z. A. Khan “Divide-and-Rule Scheme for Energy Efficient
Routing in Wireless Sensor Networks” 4th International Conference on Ambient Systems, Net-
works and Technologies (ANT 2013).
[5] Zhou, Qili and Cao, Xu and Chen, Shouyuan and Lin, Gang “A solution to error and loss in
wireless network transfer” ,Wireless Networks and Information Systems, WNIS’09. Interna-
tional Conference on , 2009.
[6] L. Qing, Q. Zhu, M. Wang“Design of a distributed energy-efficient clustering algorithm for
heterogeneous wireless sensor networks ” Computer communications ,2006.
41
42
BIBLIOGRAPHY
[7] G. Smaragdakis, I. Matta, A. Bestavros“SEP: A Stable Election Protocol for clustered hetero-
geneous wireless sensor networks” Boston University Computer Science Department (2004).
[8] B.Mazoor, N.Javaid, O.Rehman and M.Akbar“Q-LEACH: A New Routing Protocol for WSNs”
International Workshop on Body Area Sensor Networks(BASNet-2013) in conjunction with
4th International Conference on Ambient Systems, Networks and Technologies(ANT-2013),
Helifax, Nova Scotia, Canada.
[9] T.N.Qureshi, N.Javaid, A.H.Khan, A.Iqbal, E.Akhtar and M.Ishfaq“BEENISH: Balacned
Eneery Efficient Network Integrated Super Heterogenous Protocol for WSNs” International
Workshop on Body Area Sensor Networks(BASNet-2013) in conjunction with 4th Interna-
tional Conference on Ambient Systems, Networks and Technologies(ANT-2013), Helifax,
Nova Scotia, Canada.
[10] S. Faisal, N. Javaid, A. Javaid, M. A. Khan, S. H. Bouk and Z. A. Khan“Z-SEP: Zonal-Stable
Election Protocol for Wireless Sensor Networks” Journal of Basic and Applied Scientific Re-
search (JBASR), 2013.
[11] Arati Manjeshwar, Agrawal and D.P.“TEEN: A Routing Protocol for Enhanced Efficiency
in Wireless Sensor Networks” Proceedings 15th International on Parallel and Distributed Pro-
cessing Symposium, 2000.
[12] Akshay, N.Kumar, M.P. , Harish, B. and Dhonarkar and S.“An efficient approach for sensor
deployments in wireless sensor network” International Conference on in Robotics and Com-
munication Technologies (INTERACT), 2010.
[13] Z. Chaczko, R. Klempous, J. Nikodem and M. Nikodem“Methods of Sensor Localization in
Wireless Sensor Networks” 14th Annual IEEE International Conference and Workshops om
the Engineering of Computer-Based Systems, ECBS â ˘
A´
Z07, 2007.
BIBLIOGRAPHY
43
[14] Javaid. N, Ullah, M, Djouani and K.“Identifying Design Requirements for Wireless Rout-
ing Link Met- rics” 54th IEEE International Conference on Global Communications (Globe-
com1012), Houston, USA, pp.1-5, 2011.
[15] N. Javaid, A. BiBi, K. Latif and M. Ishfaq“Investigating Quality Routing Link Metrics in
Wireless Multi-hop Networks” Springerâ ˘
A´
Zs Annals of Telecommunications, 2013.
[16] N. Javaid, A. BiBi, K. Latif, M. Ishfaq“Investigating Quality Routing Link Metrics in Wire-
less Multi-hop Networks” 2nd IEEE International Conference on Computer, Control and Com-
munications (IC4-2009), Karachi, Pakistan, pp.1-7, 2009.
[17] M. Tahir, N. Javaid, A. Iqbal, Z. A. Khan and N. Alrajeh“On Adaptive Energy Efficient
Transmission in WSNs” International Journal of Distributed Sensor Networks, Volume 2013
(2013).
[18] N. Javaid, S. N. Mohammad, K. Latif, U. Qasim and Z. A. Khan and M. A. Khan“HEER:
Hybrid Energy Efficient Reactive Protocol for Wireless Sensor Networks” 2nd IEEE Saudi In-
ternational Electronics, Communications and Photonics Conference (SIECPC ô
câ ´
Cˇ
nâ ˇ
D´
c13),
2013, Riyadh, Saudi Arabia.
[19] B. Manzoor, N. Javaid, O. Rehman, M. Akbar, Q. Nadeem, A. Iqbal and M. Ishfaq“Q-
LEACH: A New Routing Protocol for WSNs” International Workshop on Body Area Sensor
Networks (BASNet-2013) in conjunction with 4th International Conference on Ambient Sys-
tems, Networks and Technologies (ANT 2013), 2013, Halifax, Nova Scotia, Canada.
[20] N. Javaid, T. N. Qureshi, A. H. Khan, A. Iqbal, E. Akhtar and M. Ishfaq“EDDEEC: En-
hanced Developed Distributed Energy-Efficient Clustering for Heterogeneous Wireless Sensor
Networks” The 4th International Conference on Ambient Systems, Networks and Technolo-
gies (ANT 2013), 2013, Halifax, Nova Scotia, Canada.
44
BIBLIOGRAPHY
[21] Aslam, M., Shah, T., Javaid, N., Rahim, A., Rahman, Z., Khan, Z. A.“CEEC: Central-
ized energy efficient clustering a new routing protocol for WSNs” Sensor, Mesh and Ad Hoc
Communications and Networks (SECON), 2012 9th Annual IEEE Communications Society
Conference on , vol., no., pp.103,105, 18-21 June 2012.
[22] M. Tahir, N. Javaid, A. Iqbal, Z. A. Khan, N. Alrajeh“On Adaptive Energy Efficient Trans-
mission in WSNs” International Journal of Distributed Sensor Networks, Volume 2013 (2013)
[23] S. H. Bouk, I. Sasase, N. Javaid“Multiple QoS Metrics Gateway Selection Scheme in Mobile
Ad-Hoc Networks (MANETs)” Journal of Communications and Networks
[24] N. Javaid, M. Ilahi, R. D. Khan, L. Ali, U. Qasim, Z. A. Khan“Evaluating Wireless Reactive
Routing Protocols with Linear Programming Model for Wireless Ad-hoc Networks” J. Basic.
Appl. Sci. Res.
[25] N. Javaid, R. D. Khan, M. Ilahi, L. Ali, Z. A. Khan, U. Qasim“Wireless Proactive Routing
Protocols under Mobility and Scalability Constraints” J. Basic. Appl. Sci. Res.
[26] S. Wasiq, N. Javaid, M. Ilahi, R. D. Khan, U. Qasim, Z. A. Khan“Evaluating and Comparing
Probability of Path Loss in DSDV, OLSR and DYMO at 802.11 and 802.11p” J. Basic. Appl.
Sci. Res.
[27] A. Iqbal, M. Akbar, N. Javaid, S.H. Bouk, M. Ilahi, R. D. Khan“Advanced LEACH: A Static
Clustering-based Heterogeneous Routing Protocol for WSNs” J. Basic. Appl. Sci. Res.
[28] N. Javaid, M. Yaqoob, M. Y. Khan, M. A. Khan, A. Javaid, Z. A. Khan“Analyzing Delay
in Wireless Multi-hop Heterogeneous Body Area Networks” accepted in Research Journal of
Applied Sciences, Engineering and Technology, 2013.
BIBLIOGRAPHY
45
[29] M.Nasir Iqbal, Junaid A.Khan, Farooq Umer, Nadeem Javaid, Izhar ul Haq, Mustafa
Shakir“Security Enhancement of Proactive Protocols in Mobile Ad-hoc Networks” J. Basic.
Appl. Sci. Res
[30] N. Javaid, Q. Ain, M. A. Khan, A. Javaid, Z. A. Khan, U. Qasim“On Sink Mobility Trajectory
in Clustering Routing Protocols in WSNs” accepted in Journal of Basic and Applied Scientific
Research (JBASR), 2013
[31] M. Tahir, N. Javaid, M. A. Khan, S. Rehman, A. Javaid, Z. A. Khan“Energy Efficient Trans-
mission in Wireless Sensor Networks” accepted in Research Journal of Applied Sciences, En-
gineering and Technology, 2013.
[32] M. Y. Khan, N. Javaid, M. A. Khan, A. Javaid, Z. A. Khan, U. Qasim“Hybrid DEEC: To-
wards Efficient Energy Utilization in Wireless Sensor Networks” World Applied Sciences Jour-
nal.
[33] N. Javaid, S. Hayat, M. Shakir, M. A. Khan, S. H. Bouk, Z. A. Khan“Energy Efficient MAC
Protocols in Wireless Body Area Sensor Networks-A Survey” J. Basic Appl. Sci. Res. 2013
[34] M. B. Rasheedl, N. Javaid, A. Javaid, M. A. Khan, S. H. Bouk, Z. A. Khan“Improving
Network Efficiency by Removing Energy Holes in WSNs” J. Basic Appl. Sci. Res.
[35] D. Mahmood, N. Javaid, S. Mahmood, S. Qureshi, A. M. Memon, T. Zaman“MODLEACH: A
Variant of LEACH for WSNs” 8th IEEE International Conference on Broadband and Wireless
Computing, Communication and Applications (BWCCA’13), Compiegne, France.
[36] Y. Khan, N. Javaid, M. J. Khan, Y. Ahmad, M. H. Zubair, S. A. Shah“LPCH and UDLPCH:
Location-aware Routing Techniques in WSNs” 8th IEEE International Conference on Broad-
band and Wireless Computing, Communication and Applications (BWCCA’13), Compiegne,
France.
46
BIBLIOGRAPHY
[37] Mohsin Raza Jafri, Nadeem Javaid, Akmal Javaid, Zahoor Ali Khan“Maximizing the Lifetime
of Multi-chain PEGASIS using Sink Mobility” World Applied Sciences Journal 21 (9): 1283-
1289, 2013.
[38] M. Akbar, N. Javaid, A. A. Khan, Z. A. Khan, U. Qasim“On Modeling Geometric Joint Sink
Mobility with Delay-tolerant Cluster-less Wireless Sensor Networks” 4th IEEE Technically
Co-Sponsored International Conference on Smart Communications in Network Technologies
(SaCoNet’13) 2013, Paris, France.
[39] Javaid, N.; Bibi, A.; Bouk, S. H.; Javaid, A.; Sasase, I.“Modeling enhancements in DSR,
FSR, OLSR under mobility and scalability constraints in VANETs” Communications (ICC),
2012 IEEE International Conference on , vol., no., pp.6504,6508, 10-15 June 2012.
[40] Javaid, N.; Yousaf, M.; Ahmad, A.; Naveed, A.; Djouani, K. “ Evaluating impact of mobility
on wireless routing protocols” Wireless Technology and Applications (ISWTA), 2011 IEEE
Symposium on , vol., no., pp.84,89, 25-28 Sept. 2011.
