Dept. Of Electrical Engineering | California State University, Long Beach| Summer 2014
Aeon LEACH
An Efficient LEACH protocol in Heterogeneous and Homogenous
Wireless Sensor Networks
Vidhi Nagri (011451113)
vidhi.nagri@gmail.com
California State University of Long Beach
EE-697
Summer 2014
This report has been reviewed by the advisor, Dr. Mohammad Mozumdar, and approved for submission
to the committee.
Under the guidance of Dr. Mohammad Mozumdar
Aeon LEACH
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Acknowledgments
I would like to express my special thanks and words of appreciation to Dr. Mohammad
Mozumdar for the guidance and support in completing this project. You have been a
tremendous mentor for me from the start of my Masters of Science degree. Your advice
on both project as well as on my career have been priceless.
A special thanks to my family. Words cannot express how grateful I am for all the
sacrifices that you have made on my behalf. I wish to thank my family for the moral
support and providing me with the resources to continue learning. Your prayer for me
was what sustained me so far. I am also immensely happy to shower my gratitude
towards all of my friends who supported me and incented me to strive towards my goal.
Aeon LEACH
Page 2
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Table of Contents
Abstract………….………………………………………………………………………..4
Introduction………………………………………………………………………………5
Related Work and Motivation ………………………………………………………….6
Basic Terminology ………………………………………………………………………7
LEACH Protocol ………………………………………………………………………...8
Why do we need Aeon LEACH? ……………………………….………………..….….9
Radio Model for Aeon LEACH………………………………………………..………10
Aeon LEACH Phase 1……………………………………………………..………..….11
Simulation Aeon LEACH Phase 1 ………………………………………………..…..17
Protocols for Heterogeneous system…………………………………………………..20
Aeon LEACH Phase 2 ……..………………………………………..…………….…...23
Simulation Aeon LEACH Phase 2 …………………………………………………….28
Conclusion and Future work …...……………..…..…………………………………..31
References……………………………………………………………………………….32
Matlab Code…………………………………………………………………………….34
Aeon LEACH
Page 3
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Abstract
In recent years, many routing protocols have been proposed to improve the lifetime,
energy efficiency, deployment of nodes, latency, fault tolerance, robustness, and
reliability of Wireless Sensor Networks (WSN). The energy constraints and prolonging
the lifetime of the WSN is very important role of routing protocols. Different cluster
based routing protocol have proposed to improve the conventional protocols i.e. direct
transmission, multi-hop routing, static clustering and minimum-transmission-energy.
Among all cluster based protocols, Low-Energy Adaptive Clustering Hierarchy
(LEACH) is the most prominent WSN protocol. In this project, we have tried to expand
the LEACH by adding different features in LEACH for homogeneous and heterogeneous
environments. We have proposed Aeon LEACH Phase-1 by introducing proficient cluster
head selection scheme and different transmitting power levels for LEACH in
homogeneous environment. But, energy saving scheme of homogeneous environment is
not suitable for heterogeneous environment. Stable Election Protocol (SEP) is the
dynamic heterogeneous routing protocol. SEP is based on weighted election probabilities
of each node to become the cluster head according to the remaining energy in each node.
We propose Aeon LEACH Phase-2 by applying different ways of communication
(between CH to sink) for advanced and normal nodes. By showing simulation, we prove
that Aeon LEACH is more energy efficient and has longer lifetime of network than
LEACH in homogeneous and heterogeneous environments.
Keywords: heterogeneous system, homogeneous system, distributed system, data
aggregation, dynamic cluster head rotation, threshold value concept.
Aeon LEACH
Page 4
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Introduction:
Wireless Sensor Networks (WSNs) represent a new paradigm in wireless technology
drawing significant research attention from diverse fields of engineering. WSN
technology is listed in “Top 10 Emerging Technologies” that will change the world.
WSNs consist of many sensor nodes. These nodes sense the changes in the physical
parameters similar to – pressure, temperature, etc. The data sensed by these nodes are
then transmitted to the Base Station (BS) for estimation. WSNs are used for the variety of
purposes like military surveillances, habitat monitoring, forest fire detections, and
landslide detections (Figure 1).
The main task of many researchers in this field is to develop smart surroundings with the
help of WSNs containing thousands of planned or ad-hoc deployed sensors, each capable
of detecting ambient conditions like temperature, sound, movements, light, or the
presence of particular objects. It is very important to make these sensing nodes as cheap
and energy efficient as possible and trust them to obtain high quality results. Hence, to
have battery operated sensor nodes is a good option. But despite of their small sizes,
these batteries must be capable of giving a longer life to these sensing nodes. The
network protocol used must be very efficient to optimize the lifetime of the nodes.
We also need to focus on algorithms and physical circuitries that can make maximum out
of limited power source. Some of the promising routing algorithms can be categorized
into three types as direct transmission algorithms, hop to hop transmission algorithms and
cluster based algorithms. In cluster based protocols, most of the energy consumption
depends on cluster head selection, cluster formation and the algorithm developed for
routing the information.
Aeon LEACH
Page 5
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Related Work and Motivation:
In direct communication protocol, each sensor node sends its data directly to the base
station. Direct communication will require a large amount of transmit power from each
node if the base station is far. The second conventional approaches we consider is a
“minimum-energy” routing protocol. In this protocol, nodes route data through
intermediate nodes ultimately destined for the base station. Thus every node acts as a
router for other nodes in addition to sensing the environment. These protocols differ in
the way the routes are chosen.
We can divide cluster based routing protocols mainly in two parts, Protocols for
homogeneous environment and protocols for heterogeneous environment. LEACH is one
of the first cluster based routing protocol. It assigns equal probability for each node to
become cluster head. This works well for the homogeneous networks but not for the
heterogeneous networks because of the unequal energy of nodes.
SEP prolongs the lifetime of WSNs by inserting a percentage of heterogeneous nodes.
Heterogeneous WSNs consist of sensor nodes with different ability, such as different
sensing range and data computing power. By adding these nodes we can follow different
cluster selection scheme. This will give higher stability to the cluster and longer time to
survive the cluster. This scheme depends on current node energy; each node will be CH
depending on its remaining energy.
Another problem occurs in handling the huge amount of information and to pass it over
through every node of the network. To resolve this issue, we need to have an efficient
routing protocol that has low routing overhead and a good data aggregation technique to
save the limited power of sensing node.
By introducing the Aeon LEACH, we are trying to improve lifetime of the LEACH
protocol in homogeneous and heterogeneous mediums. It focuses on less power
consumption for data aggregation by using threshold value concept. We are going to use
distributed sensor nodes using dynamic cluster head rotation. Aeon LEACH can be
divided into two parts: Phase-1 and Phase-2. Initially we are assuming that all the sensor
nodes are at same energy level so that we can consider the system to be homogeneous.
When some of the nodes die, system becomes unstable and homogeneous routing
protocols are not able to take the advantage of remaining energy. After some time, the
energy levels will be different among the nodes and hence the field can be assumed as
heterogeneous system. We also assume that, all the nodes are steady.
Aeon LEACH
Page 6
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Basic Terminologies:
Stability Period:
 Time interval between start to the death of the first sensor node in the network.
Instability Period:
 Time interval between the deaths of the first node and the last node.
Throughput:
 The total amount of data sent over the network i.e. the amount of data sent from
cluster heads to base station and the amount of data sent from the nodes to base
station.
Network Lifetime:
 Time interval between the deployment of the network and the death of the last
alive node.
Epoch:
 Number of rounds after which a node is eligible for cluster head.
Data Aggregation:
 Data collected in the sensors are derived from similar phenomena and hence nodes
in a close area usually share same information. A way to reduce the energy
consumption is the data aggregation technique. Aggregation also consists of
suppressing redundancy in different data messages. When this suppression is
achieved by some signal processing techniques, this operation is called as data
fusion.
Number of cluster heads per round:
 It reflects the number of nodes which would send the aggregated information
directly to the sink.
 Number of total alive (advanced and normal) nodes per round: It reflects the total
number of nodes including the nodes that have not spent their energies at all.
Aeon LEACH
Page 7
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
LEACH Protocol:
LEACH is Low-Energy Adaptive Clustering Hierarchy, a clustering-based protocol that
minimizes energy dissipation in sensor networks.
The key features of LEACH are:
 Localized control and coordination for cluster set-up and its operation
 Randomized rotation of the cluster “base stations” or “cluster-heads” and the
corresponding clusters
 Compression done locally to reduce global communication
LEACH protocol has advantage over previous WSN routing protocols. It requires small
transmit distances for most of the nodes, which uses only a few nodes to transmit far
distances to the base station. LEACH outperforms classical clustering algorithms by
using adaptive clusters and rotating cluster-heads, thus allowing the distributed energy
requirements of the system among all the sensors.
In addition, LEACH is able to perform local computation in each cluster to reduce the
amount of data that has to be transmitted to the base station. This reduces the energy
dissipation, as computation is much cheaper than communication.
LEACH is following periodic process. In 1st Advertise Phase, election of cluster head and
nodes covered in that cluster is defined. The 2nd Setup Phase consists of the planning of
cluster schedule with base station. In the 3rd steady state, nodes send data to the
respective base stations.
LEACH is completely distributed and non-centralized control system. It can reduce
communication costs by up to 8x because LEACH keeps the first node alive for up to 8x
longer and the last node by up to 3x longer.
Figure 2: LEACH Protocol
Aeon LEACH
Page 8
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Why do we need Aeon LEACH?
 Aeon LEACH is the proposed protocol to use the LEACH protocol for the longer
time in the field by increasing its efficiency. It tries to improve some of the
drawbacks of LEACH protocol in WSN.
 LEACH assumes that most of the WSN fields are homogeneous system, but in
real-world situation, it is very difficult to find homogeneous system for a long time
or till the network exists. Therefore, it is very essential to cover both homogeneous
and heterogeneous environment situation while creating the protocol.
 LEACH assumes that all cluster heads pay the same energy cost, which is not
possible. The cluster head in the WSN consumes different amount of energy
depending upon the distance between n cluster head to base station and the amount
of data it is transmitting. Therefore, calculation for the energy consumptions is
wrong. Death model is incorrect.
 Compression may not be as cheap as claimed because it is unclear how much
savings are from compression assumptions and how much from adaptive
clustering. There is not any threshold decided for compression of sensed data.
 LEACH gives adaptive clustering mechanism which deals very efficiently with
energy conservations. However, LEACH doesn’t take account of residual energy
of a node. To address this, a novel technique as efficient cluster head selection is
proposed.
 LEACH uses same amplification energy for both kinds of transmissions i.e. cluster
head to base station and CM to CH. To address this, multi amplified power levels
are introduced. This is how much of the energy wasted in cluster head formation
process can be saved. Moreover, control overhead is also limited.
 LEACH does not determine optimal number of cluster heads in simulation, before
implementation. Round durations never specified or explained in LEACH
protocol.
Aeon LEACH
Page 9
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Radio model used for Aeon LEACH:
For our work, we assume a simple model where the radio dissipates
= 50 nJ/bit to
run the transmitter or receiver circuitry and
= 100 pJ/bit/
for the transmitter
amplifier to achieve an acceptable Eb/ No. We consider these parameters because they
are better than the current state-of-the-art in radio design1. Due to channel transmission,
we also assume an energy loss.
Figure 3:
First order radio model
Therefore to transmit k-bit message for a distance d using our radio model, the radio uses
+
€amp * k *
And to receive this message, radio expends:
For these values, message receiving is not a low cost operation; the protocols should thus
try to minimize not only the transmit distances but also the number of transmit and
receive operations for each message.
Aeon LEACH
Page 10
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Proposed Aeon Phase 1:
Aeon phase-1 is an advanced version of LEACH protocol in the homogeneous
environments.
Assumption is that all the nodes initially have the same energy i.e. homogenous system.
Aeon LEACH phase-1 introduces mainly two techniques to improve the LEACH
protocol in the WSNs. In this section, we will observe how these techniques will work
with existing LEACH protocol.
1. Proficient cluster head selection scheme:
Same as LEACH, Aeon LEACH also has two phases: The Set-Up phase and the
Steady-State phase. The Set-Up phase where cluster heads are chosen and Steady
State where cluster head maintained and data is transmitted between the nodes and
base station or between nodes and cluster heads.
LEACH protocol changes the cluster head at every round and once a cluster head
is formed, it will not get another chance for next 1/p rounds.
Equation for LEACH protocol:
For every round, cluster heads are replaced and whole cluster formation process is
carried out again. For this reason, we propose an efficient cluster head selection
scheme. It is the starting point in cluster head formation for every next round.
If existing cluster has not spent much energy during its tenure and has the required
threshold energy, then it will remain as cluster head for the next round too. And
thus the energy wasted in routing the packets for new cluster head and cluster
formation can be saved. If the cluster head has less energy than required threshold,
new cluster head will be selected according to LEACH algorithm.
Aeon LEACH
Page 11
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
2. Different modes of transmission:
Besides limiting energy utilization in cluster formation, Aeon LEACH introduces
two different levels of power to amplify signals according to nature of
transmission. There can be three modes of transmission in a cluster based network:
a. Intra Cluster Transmission
b. Inter Cluster Transmission
c. Transmission between Cluster Head to Base Station
Intra Cluster Transmission deals with all the communication within a cluster i.e.
cluster member senses the data and report the sensed data to the cluster head.
The transmission/ reception between two cluster heads can be called as Inter
Cluster Transmission while a cluster head transmitting its data straight to the base
station lies under the caption of Cluster Head to Base Station Transmission.
The amount of minimum amplification energy required for inter cluster or intra
cluster or cluster head to BS communication cannot be same.
The amplification energies required for each mode of transmission in Aeon
LEACH cannot be same. While in LEACH, amplification energy is same for all
modes of transmission. Use of low energy level for Intra Cluster Transmission
with respect to Cluster Head to BS Transmission could save much amount of
energy. Moreover, multi power levels also reduce the packet drop ratio, collisions
and/ or interference from other signals.
In this context, we assume that a cluster at maximum may spread into an area of
15X15
in a field of 150X150 . Energy that is enough to transmit at far ends
of a field of 150X150
must be lowered 10 times for intra-cluster transmission.
When a node acts as a cluster head, routing protocol allows it to use high power
amplification. When the same node becomes a cluster member, routing protocol
changes it to low power amplification.
At the end, soft and hard threshold schemes are also implemented in Aeon
LEACH that gives better results.
Aeon LEACH
Page 12
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Aeon LEACH Phase-1 Algorithm Details:
Figure 4: Comparison between LEACH and Aeon LEACH Phase 1
Aeon LEACH
Page 13
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
We can compare LEACH and Aeon LEACH by considering different phases.
1.
2.
3.
4.
5.
Advertisement Phase
Cluster Set-Up Phase
Schedule Creation
Data Transmission
Multiple Clusters
1. Advertisement Phase:
In Aeon LEACH if CH energy is less than threshold, cluster will select new CH. While
cluster formation is in process, each node is checked for the cluster head selection for
current round. This selection is based on the required number of cluster heads for the
network and the number of times the node being a cluster head till now. The decision is
made by the node n by choosing a number between 0 and 1. If the chosen number is less
than threshold, the node is chosen as cluster head for the current round.
Each node which is chosen as cluster-head for the current round, will broadcast an
advertisement message to all other nodes in the cluster. For this phase, the cluster head
uses a CSMAMAC protocol. All cluster-heads transmit their advertisements using the
same energy. The non-cluster head nodes must keep their receivers ON during this phase
to hear these advertisements. As soon as this phase is over, each non-cluster head node
chooses the cluster to which it will belong. This decision is done based on the received
advertisement’s signal strength.
.
During start of any round, if CH has higher energy than threshold, same node will be CH
for next round. In this way energy to choose cluster head again for round will be saved.
All connection between cluster to cluster and CH to BS will be same.
Aeon LEACH
Page 14
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
2. Cluster Set-Up Phase:
This phase will be used if CH has less energy than threshold value. New cluster will be
created in this case. After each node decides to which cluster it will belong, it should
inform the CH of that particular cluster. Each node will transmit this information back to
the CH again using a CSMA MAC protocol. All CH nodes must keep their receivers ON
during this process.
3. Schedule Creation:
Based on the entire feedback signals CH received in the previous mode, CH will get
information about nodes that would like to join the cluster. Based on this number, CH
will assign TDMA schedule to each node. Once this schedule will broadcast to every
node in the cluster, nodes will follow the same schedule for the data transmission.
In Aeon LEACH, if CH is not changed during another round, Cluster will follow the
same TDMA schedule for next round. By this way, cluster cam save the energy.
4. Data Transmission:
In Aeon LEACH, this is the most important phase from the energy conservation point of
view. Here we introduce two concepts: Hard Threshold and Soft Threshold.
Hard Threshold Concept:
When a sensed value is greater than the threshold value, data packet will only be
transmitted to receiver. It will minimize the number of transmissions to save the energy
of a node. However, it transmits data always when that threshold is broken; no matter if
sensor is sensing the same value from last many rounds.
Soft Threshold Concept:
When sensed value from node is higher than the previous sensed value, node will
transmit the data to receiver. This will pass messages which have some information in it.
This will increase the network efficiency significantly. This is due to limiting number of
transmissions (concept of soft threshold) along with efficient cluster head selection
mechanism that preserve energy globally and multi power level for inter and intra cluster
communication.
In Aeon LEACH ST, number of transmissions are confirmed only when a pre-described
change in sensed data is achieved. This limits number of transmissions to preserve
residual energy of a sensor node (numbers of transmissions are inversely proportional to
energy of sensor node).
Aeon LEACH
Page 15
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
After the calculation of soft and hard threshold, nodes start data transmission.
When the clusters are created and the TDMA schedule is fixed, we can begin the data.
Assuming that nodes always have some data to send and they send it during their
allocated transmission time, each of them can be turned off until their allocated
transmission time. This results in minimizing energy dissipation in these nodes. The CH
node must keep its receiver ON until it receives all the data from all the nodes. When all
the data is received, the CH performs signal processing functions to compress all the data
into a single signal. Aeon LEACH uses different mode of transmission depending upon
the distance between transmitter and receiver.
5. Multiple Clusters:
The preceding discussion describes how the individual clusters communicate among
nodes in that cluster. Intra Cluster Transmission, Inter Cluster Transmission, Cluster
Head to Base Station Transmission.
However, radio is essentially a broadcast channel. The transmission in one cluster will
affect and hence degrade the communication in a nearby cluster.
Aeon LEACH
Page 16
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Simulations for Aeon LEACH Phase 1:
Parameters used for calculation:
Network Parameters
Network Size
Initial Energy of Sensor Nodes
Packet Size
Transceiver idle state energy consumption
Data Aggregation/ Fusion Energy consumption
Amplification Energy (Cluster to BS)d >= do
Amplification Energy (Cluster to BS) d <= do
Amplification Energy (Intra Cluster Comm.)
Amplification Energy (Intra Cluster Comm.)
Value
100X100
0.5 J
4000 bits
50 nJ/bit
5 nJ/bit/report
= 10pJ/bit/
= 0.0013pJ/bit/
/10 =
/10 =
Figure 5: i) Alive nodes of the Network Vs. No of rounds in Aeon LEACH Phase 1.
ii) Dead nodes of the Network Vs. No of rounds in Aeon LEACH Phase 1.
 In all Simulation figures,
LEACH : Red
Aeon LEACH : Green
Aeon LEACH Hard threshold : Black
Aeon Leach with Soft threshold : Blue
Aeon LEACH
Page 17
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
 Nodes will die soon in LEACH protocol as every round there will be new cluster
head selection process will be performed. Again, all the nodes will transmit with
the same energy.Aeon LEACH in green would have better performance than
LEACH because these two issues are solved. Hard threshold will minimize the no
of signals to be transmitted, because it will send only the value higher than
threshold. This can also abort the signal which has importanat data in it,as this
signal total information is lesser than threshold. Performace by using Soft
threshold is best so far. This technique minimizes the no of packets transmitted to
reciever. Again, it will only send the data if it has higher information than the
previous signal.
 Graph for the dead nodes of the network will be exactly opposite. In LEACH,
nodes will die soon as compared to Aeon LEACH with hard threshold and Aeon
LEACH with soft threshold.
Figure 6 : i) Packets transmitted to Base station in Aeon Phase 1 Vs. No of rounds
ii) Packets transmitted to Cluster Head in Aeon Phase 1 Vs. No of rounds
 Better network life time and efficient cluster head selection mechanism are two
major reasons of increased throughput in Aeon LEACH with soft threshold.
Comparing Aeon LEACH and LEACH, Aeon LEACH gives better throughput
due to same reasons i.e. increased network life time and better cluster head
selection scheme.
Aeon LEACH
Page 18
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
 One more prominent reason is dual transmitting power levels within network.
Using different amplification energies for transmissions reduces packet drop ratio
resulting in higher through put.
 Another reason that can distinguish throughput gain in all studied techniques is the
mode of operation. LEACH and Aeon LEACH both are proactive (periodical
transmissions) in nature while Aeon Leach with soft threshold and Aeon LEACH
with hard threshold are reactive (event driven).
 This also depicts that proactive (periodical transmission) routing protocols have
lower throughput than reactive (event driven) routing protocols.
Aeon LEACH
Page 19
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
WSN protocols for Heterogeneous system:
LEACH, which is a WSN protocol for homogeneous systems, is not suitable for
heterogeneous systems. Putting few heterogeneous nodes in a Wireless Sensor Network
is an effective way to increase the network’s stability and lifetime. The energy saving
schemes used for homogeneous WSNs does not work efficiently when used for
heterogeneous WSNs. Thus, a new energy efficient clustering protocol should be
designed for them. Heterogeneous WSNs are very much useful in real deployments
because they are more close to real life situations.
Figure 7: Heterogeneous model for Wireless Sensor Network
Aeon LEACH
Page 20
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
We can divide heterogeneous WSN system mainly in three parts.
1) Computational heterogeneity
2) Link heterogeneity
3) Energy heterogeneity
Computational heterogeneity:
In this type of system, some of the nodes have more energy than the other normal nodes.
The heterogeneous nodes can provide some benefits such as complex data processing and
long term storage with the use powerful computational resources. We are going to use
this approach in Aeon LEACH Phase 2.
Link heterogeneity:
Here, some of the heterogeneous nodes have higher bandwidth and longer distance
network transceiver than the normal nodes. It can provide more reliable data
transmission.
Energy heterogeneity:
This system has some of the heterogeneous nodes that are line powered or their batteries
are replaceable.
For our protocol, Computational heterogeneity is the best suitable. Because in Aeon
LEACH, we are trying to increase the lifetime of the network. By distributing powerful
calculations to advance nodes, we can increase the network lifetime. Link heterogeneity
is dealing with the quality and reliability of packets whereas; Energy heterogeneity can
be implemented in practical situations. We are not considering Link and Energy
heterogeneity from the algorithm point of view.
Aeon LEACH
Page 21
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Heterogeneous SEP Protocol:
Aeon LEACH Phase 2 is dependent on SEP (A Stable Election Protocol for clustered
Heterogeneous WSNs) protocol. SEP is based on weighted election probabilities of each
node to become cluster head according to the remaining energy in each node. SEP tries to
maximize the stability of the network. Stability can be increased by increasing the time of
last node death. Clearly, larger the stable and unstable regions are, better is the reliability
of the clustering process.
On the other hand, there is a tradeoff between reliability and the lifetime of the system.
Until the death of the last node, we still can have some feedback about the sensor field
even though this feedback may not reliable. The unreliability of the feedback stems from
the fact that there is no guarantee that there is at least one cluster head per round during
the last rounds of the operation. In our model, the absence of a cluster head prevents
reporting about the cluster to the sink at all. The throughput quantity captures the amount
of such data reporting to the sink.
In a heterogeneous WSN, LEACH doesn’t work well as it is very sensitive to the
heterogeneity.
Characteristics of SEP:
 Being aware of heterogeneity, SEP successfully outspreads the stable region by
assigning weighted probabilities of cluster-head selection by the initial energy of
initial nodes.
 Due to this outspreaded extended stable region, the throughput is also increased.
The performance of SEP is extended by distributing the additional energy of the
advanced nodes uniformly to all other nodes in the field.
 SEP is more robust than LEACH by carefully consuming this extra energy of the
advanced nodes. It yields longer stability region for higher values of extra energy.
Aeon LEACH
Page 22
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Aeon LEACH Phase 2:
In this section we present Aeon Phase 2 protocol. Here we assume that after couple of
rounds of homogeneous system, system will be no longer homogeneous. This is possible
because of data transmission is not always same from all the nodes. Nodes which are
nearer to the base station, they have to pass more data compared to the nodes which are
far away.
This is the reason we assume that, the nodes at a far end from the base station have more
energy and are considered as advance nodes. Nodes which are near to the base station are
normal nodes with lesser energy than advanced node.
Our protocol is extension of SEP. It follows the hybrid approach i.e. direct transmission
as well as transmission via cluster head. Depending on Energy of nodes, we can divide all
the nodes in advanced nodes with more energy than normal nodes. For Aeon Phase2
setup, we will put advance nodes in the corner for direct transmission and normal nodes
in-between through cluster head transmission.
Proposed Aeon Phase 2:
Architecture:
At the end of Aeon Phase 1, we assume that the nodes are placed randomly and with
different amount of energies in all. So we can divide the nodes based on their energies:
zone 0, Head zone 1, and Head zone 2.
We assume that the advance nodes are having fraction of more energy than the normal
nodes. Total m numbers of nodes out of n are having α time more energy than normal
nodes. We refer these nodes as advance nodes and (1-m) ×n are normal nodes.
Nodes in zone 0 have less energy and they are deployed near to the base station. These
nodes will directly transmit the data to the sink. Nodes in Zone 1,2 have α times more
energy than nodes in zone 0.
Aeon LEACH
Page 23
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Figure 8: Setup for the Advanced and normal node for Aeon phase 2
Operation:
Aeon phase 2 uses two modes of data transmission techniques.
 Direct communication
 Transmission through cluster head
Direct Communication:
Normal nodes will sense environment and gathers data of interest. After that they will
send it data to base station through direct communication.
Transmission via Cluster head:
Clustering Nodes in Head zone 1 and Head zone 2 transmit data to the base station
through clustering algorithm. Cluster head is selected among nodes in Head zone 1 and 2.
Cluster heads collect data from member nodes, aggregate them and transmit them to the
base station. Cluster head selection is very important because it collects data from
member nodes and transmits to sink. Figure shows only advanced node is creating
Aeon LEACH
Page 24
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
clusters.
clusters
Assume an n is the number of advance nodes and optimal number of
. According to SEP, optimal probability of cluster head is
Every node has to decide if it wants to be the cluster head in current round. A random
number is generated between 0 and 1. As per SEP, if the generated number is less than or
equal to threshold, that node will selected as cluster head.
Threshold is given by
if n € G
= 0
Otherwise
Where G is the set of all the nodes which have not been selected as cluster heads in the
last 1/
rounds. Equation below gives the probability for advance nodes to become
cluster head.
* (1 + α)
Also the threshold for advance nodes is given as,
T (adv) =
=0
if adv €
Otherwise
Where G' is the set of all the advance nodes that have not been selected as cluster head in
the last 1/
rounds.
Same as LEACH, Once the CH is selected then the CH will broadcast an advertisement
message to all the other nodes. Other nodes will receive the message and decide whether
to join with this CH or any other. This phase is known as cluster formation phase.
On the basis of the received signal’s strength, nodes respond to cluster head and become
member of cluster head. Cluster head then assign a TDMA schedule for the nodes during
which nodes can send data to cluster head. After the clusters formation, every node data
and sends it to the cluster head in the time slot allocated by
the cluster head to the node. Cluster head then aggregates the received data from the
nodes and sends it to the base station. This phase is called as transmission phase.
Aeon LEACH
Page 25
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Figure 9: Advance nodes select CH and send data to CH
Figure 10: CH sends data to the sink by direct communication
Aeon LEACH
Page 26
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Flow Chart for Phase 2:
Figure 11: Flow chart of Aeon Phase 2
Figure 11 briefly explain the operations of Aeon phase 2 for normal and advanced nodes.
Because of the energies of normal nodes are less than those of advance nodes, normal
nodes are not able to form a cluster. Also in receiving the data from all other nodes, the
cluster head will consume more energy. If normal nodes are allowed to become cluster
head then they will die soon making the stability period short.
Aeon LEACH
Page 27
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Simulation for Aeon Phase 2:
Table shows the parameters used for simulation.
Parameters
Initial energy Eo
Initial energy of advance nodes
Energy for data aggregation EDA
Transmitting and receiving energy Eelec
Amplification energy for short distance Efs
Amplification energy for long distance Eamp
Probability Popt
Value
0.5 J
Eo(1+α)
5 nJ/bit/signal
5 nJ/bit
10 pJ/bit/m2
0.013 pJ/bit/m4
0.1
Figure 12: Alive nodes comparison fir LEACH, SEP and Aeon Leach phase 2 Vs. Number of rounds.
Aeon LEACH
Page 28
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Figure 13: Dead nodes comparison fir LEACH, SEP and Aeon Leach phase 2 Vs. Number of rounds.
Figure 14: Packets to Base Station comparison for LEACH, SEP and Aeon Leach phase 2 Vs. Number of
rounds.
Aeon LEACH
Page 29
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
 In this simulation m=0.2 and α=1which means that we have 20 advance nodes out
of total 100 nodes. According to our proposed protocol, Head zones 1 and 2 will
contain 10 advance nodes each.
 Figure shows Aeon leach phase 2 is having higher stability than LEACH and SEP.
In LEACH, nodes will die soon, because they do not support the heterogeneity of
the system. SEP will give better result with two stage heterogeneity and weighted
cluster head selection process. Aeon LEACH phase 2 performs better than
LEACH and
 SEP, because nodes in Zone 0 (normal nodes) communicates directly to base
station while nodes in head zones 1and 2 communicates base station through
cluster head.
 In case of clustering technique, energy consumed by cluster head is in the form of
data receiving from other nodes and doing the data aggregation..
 This energy is conserved in normal nodes resulting in the increase of stability
period.
 In Fig.5, we can clearly see that, use of advance nodes increases network lifetime.
They have α time more energy than normal nodes. And hence advance nodes die
after normal nodes resulting in the increase of the instability period.
Aeon LEACH
Page 30
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Conclusion and Future Work:
In our work we have briefly describe how cluster based routing protocol LEACH can be
utilized in better way for homogeneous and heterogeneous environment. Our simulation
shows Aeon Phase 1 gives better throughput of the system compare to LEACH. We can
get better efficiency by including new CH replacement scheme and different transmission
energy. Moreover, stability of SEP can be improvised by using two different transmission
techniques direct transmission and CH to sink transmission in heterogeneous
environment implemented in Aeon Phase 2.
In future, Aeon LEACH can be improvised by adding more techniques for hierarchal
transmissions between CH to Sink. Again, It will be interesting to apply advanced node
concept with Energy heterogeneity.
Aeon LEACH
Page 31
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
References:
1. Wendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan,
Energy efficient cooperative LEACH protocol for wireless sensor networks,
Massachusetts Institute of Technology, Cambridge, MA 02139
2. Georgios Smaragdakis, Ibrahim Matta , Azer Bestavros
SEP: A Stable Election Protocol for clustered wireless sensor networks, Computer
Science Department, Boston University, Boston, MA 02215, USA
3. Li Qing *, Qingxin Zhu, Mingwen Wang
Design of a distributed energy-efficient clustering algorithm for heterogeneous
wireless sensor networks, School of Computer Science and Engineering,
University of Electronic Science and Technology of China, Chengdu 610054, PR
China
4. Brahim Elbhiri, Saadane Rachid , Sanaa El fkihi
Developed Distributed Energy-Efficient Clustering (DDEEC) for heterogeneous
wireless sensor networks
5. Ajay.K.Sharma,Department of Computer Science & Engineering
Parul Saini, Department of Computer Science & Engineering
E-DEEC- Enhanced Distributed Energy Efficient Clustering Scheme for
Heterogeneous WSN
6. T. N. Qureshi, N. Javaid, M. Malik, U. Qasim‡, Z. A. Khan§,
On Performance Evaluation of Variants of DEEC in WSNs
7. Q. Nadeem, N. Javaid, S. N. Mohammad, M. Y. Khan, S. Sarfraz, M. Gull
On Performance Evaluation of Variants of DEEC in WSNs
8. Parul Saini, Ajay K Sharma
Energy Efficient Scheme for Clustering Protocol Prolonging the Lifetime of
Heterogeneous Wireless Sensor Networks
9. K. Dasgupta, K. Kalpakis, P. Namjoshi, An Efficient Clustering-Based Heuristic
for Data Gathering and Aggregation in Sensor Networks, Proceedings of Wireless
Communication and Networking (WCNC’03), 3: 1948-1953, 2003
Aeon LEACH
Page 32
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
10. Habib M. Ammari, Sajal K. Das
Scheduling protocols for homogeneous and heterogeneous k-covered wireless
sensor networks
11. Neha Mehndiratta, Manju, Harish Bedi
Energy Efficient Homogeneous vs Heterogeneous LEACH
International Journal of Innovative Technology and Exploring Engineering
(IJITEE)
12. R Saravanakumar, S. G. Susila, J. Raja
Energy Efficient Homogeneous and Heterogeneous System for Wireless Sensor
Networks
International Journal of Computer Applications (0975-8887)
13. Femi A. Aderohunmu, Jeremiah D. Deng
Department of Information Science, University of Otago, New Zealand
An Enhanced Stable Election Protocol (SEP) for Clustered Heterogeneous WSN
14. Dilip Kumar, Trilok C. Aseri, R.B.Patel
A Novel Multihop Energy Efficient Heterogeneous Clustered Scheme for Wireless
Sensor Networks
15. Lalitesh Sehgal, Vishal Choudhary
REEH: Residual Energy Efficient Heterogeneous Clustered Hierarchy Protocol for
Wireless Sensor Networks
16. B. Krishnamachari, D. Estrin, S.B. Wicker, The Impact of Data Aggregation in
Wireless Sensor Networks, Proceedings of 22nd International Conference on
Distributed Computing Systems Workshops (ICDCSW’02), 575-578, 2002
17. V. Mhatre, C. Rosenberg, Homogeneous vs. Heterogeneous Clustered Sensor
Networks: A Comparative Study, Proceedings of IEEE International Conference
on Communications (ICC’04), 2004
18. V. Mhatre, C. Rosenberg, Homogeneous vs. Heterogeneous Clustered Sensor
Networks: A Comparative Study, Proceedings of IEEE International Conference
on Communications (ICC’04), 2004
Aeon LEACH
Page 33
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Aeon LEACH Phase 1 MATLAB code:
clear;
xm=400;
%diameters of sensor network
ym=400;
sink.x=200; %distance of base station from the network
sink.y=200;
n = 200;
%no of nodes
p=0.1;
%probibilty of a node to become cluster head
Eo=0.5;
%energy supplied to each node
ch=n/10;
ETX=50*0.000000001;
%transmiter energy per node
ERX=50*0.000000001;
%reciever energy per node
Efs=10*0.000000000001;
%amplification energy when d is less than d0
Emp=0.0013*0.000000000001; %amplification energy when d is greater than d0
Efs1=Efs/10;
% amp energy just for intra cluster communication.
Emp1=Emp/10;
%Data Aggregation Energy
EDA=5*0.000000001;
a=Eo/2;
rmax=1800;
%no of rounds
%temprature range
tempi=50;
tempf=200;
%Thresholod for transmiting data to the cluster head
h=100;
%%%%%%Hard Thres%%%%hold H(t)
s=2;
%%%%%%Soft thres%%%%hold S(t)
sv=0;
%%%%%%previously Sensed value S(v)
do=sqrt(Efs/Emp);
%distance between cluster head and base station
do1=sqrt(Efs1/Emp1);
for i=1:1:n
S(i).xd=rand(1,1)*xm; %it will distribute the nodes in x axis randomly.
XR(i)=S(i).xd;
%we store its value in xr
S(i).yd=rand(1,1)*ym; %it will distribute the nodes in y axis randomly
YR(i)=S(i).yd;
%we store its value in yr
S(i).G=0;
% as the no of node that have been cluster head is zero 0
S(i).E=Eo
%%*(1+rand*a);
%?
%ch.E=x; % initial energy of all cluster heads in network
%initially there are no cluster heads only nodes
S(i).type='N';
end
Aeon LEACH
Page 34
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
S(n+1).xd=sink.x; %assume that base station is also a node sp total no of nodes is n and
with base station it is n+1
S(n+1).yd=sink.y;
countCHs=0;
%the number of Stateflow objects in the current context.
cluster=1;
%first cluster is selected
flag_first_dead=0;
flag_teenth_dead=0;
flag_all_dead=0;
dead=0;
first_dead=0;
teenth_dead=0;
all_dead=0;
allive=n;
%counter for bit transmitted to Bases Station and to Cluster Heads
packets_TO_BS=0;
packets_TO_CH=0;
for r=0:1:rmax
cv = tempi + (tempf-tempi).*rand(1,1); %%%%%%Current sensing value C(v)
if(mod(r, round(1/p) )==0) %remainder
for i=1:1:n
S(i).G=0;
% it will assign to the nodes that have not been cluster head .
%%S(i).cl=0;
end
end
dead=0;
for i=1:1:n
if (S(i).E<=0)
dead=dead+1;
if (dead==1)
if(flag_first_dead==0)
first_dead=r;
flag_first_dead=1;
end
end
if(dead==0.1*n)
if(flag_teenth_dead==0)
Aeon LEACH
Page 35
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
teenth_dead=r;
flag_teenth_dead=1;
end
end
if(dead==n)
if(flag_all_dead==0)
all_dead=r;
flag_all_dead=1;
end
end
end
if S(i).E>0
S(i).type='N';
end
end
STATISTICS.DEAD(r+1)=dead;
STATISTICS.ALLIVE(r+1)=allive-dead;
countCHs=0;
cluster=1;
if S(i).type=='C' && S(i).E>a
for j=1:1:ch
countCHs=countCHs+1;
S(i).type='C';
S(i).G=round(1/p)-1;
C(cluster).xd=S(i).xd;
C(cluster).yd=S(i).yd;
distance=sqrt( (S(i).xd-(S(n+1).xd) )^2 + (S(i).yd-(S(n+1).yd) )^2 );
C(cluster).distance=distance;
C(cluster).id=i;
X(cluster)=S(i).xd;
Y(cluster)=S(i).yd;
cluster=cluster+1;
distance;
% if (cv >= h)
%test = cv-sv;
%if (test >= s)
if (distance>do)
S(i).E=S(i).E- ( (ETX+EDA)*(4000) +
Emp*4000*(distance*distance*distance*distance ));
end
Aeon LEACH
Page 36
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
if (distance<=do)
S(i).E=S(i).E- ( (ETX+EDA)*(4000) + Efs*4000*(distance * distance ));
end
%end
%packets_TO_BS=packets_TO_BS+1;
%PACKETS_TO_BS(r+1)=packets_TO_BS;
%
packets_TO_CH=packets_TO_CH+1;
end
else
for i=1:1:n
if(S(i).E>0)
temp_rand=rand;
if ( (S(i).G)<=0)
if(temp_rand<= (p/(1-p*mod(r,round(1/p)))))
countCHs=countCHs+1;
packets_TO_BS=packets_TO_BS+1;
PACKETS_TO_BS(r+1)=packets_TO_BS;
S(i).type='C';
S(i).G=round(1/p)-1;
C(cluster).xd=S(i).xd;
C(cluster).yd=S(i).yd;
distance=sqrt( (S(i).xd-(S(n+1).xd) )^2 + (S(i).yd-(S(n+1).yd) )^2 );
C(cluster).distance=distance;
C(cluster).id=i;
X(cluster)=S(i).xd;
Y(cluster)=S(i).yd;
cluster=cluster+1;
% if (cv >= h)
%test = cv-sv;
%if (test >= s)
distance;
if (distance>do)
S(i).E=S(i).E- ( (ETX+EDA)*(4000) +
Emp*4000*(distance*distance*distance*distance ));
end
if (distance<=do)
S(i).E=S(i).E- ( (ETX+EDA)*(4000) + Efs*4000*(distance * distance ));
end
end
Aeon LEACH
Page 37
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
end
% end
% S(i).G=S(i).G-1;
end
end
end
STATISTICS.COUNTCHS(r+1)=countCHs;
for i=1:1:n
if ( S(i).type=='N' && S(i).E>0 )
if(cluster-1>=1)
min_dis=Inf;
min_dis_cluster=0;
for c=1:1:cluster-1
temp=min(min_dis,sqrt( (S(i).xd-C(c).xd)^2 + (S(i).yd-C(c).yd)^2 ) );
if ( temp<min_dis )
min_dis=temp;
min_dis_cluster=c;
end
end
% if (cv >= h)
%test = cv-sv;
%if (test >= s)
min_dis;
if (min_dis>do1)
S(i).E=S(i).E- ( ETX*(4000) + Emp1*4000*( min_dis *min_dis * min_dis *
min_dis));
end
if (min_dis<=do1)
S(i).E=S(i).E- ( ETX*(4000) + Efs1*4000*( min_dis * min_dis));
end
S(C(min_dis_cluster).id).E =S(C(min_dis_cluster).id).E- ( (ERX +
EDA)*4000 );
packets_TO_CH=packets_TO_CH+1;
%end
%sv
S(i).min_dis=min_dis;
S(i).min_dis_cluster=min_dis_cluster;
else
min_dis=sqrt( (S(i).xd-S(n+1).xd)^2 + (S(i).yd-S(n+1).yd)^2 );
if (min_dis>do)
Aeon LEACH
Page 38
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
S(i).E=S(i).E- ( ETX*(4000) + Emp*4000*( min_dis *min_dis * min_dis *
min_dis));
end
if (min_dis<=do)
S(i).E=S(i).E- ( ETX*(4000) + Efs*4000*( min_dis * min_dis));
end
packets_TO_BS=packets_TO_BS+1;
sv=cv;
end
end
end
STATISTICS.PACKETS_TO_CH(r+1)=packets_TO_CH;
STATISTICS.PACKETS_TO_BS(r+1)=packets_TO_BS;
end
first_dead;
teenth_dead;
all_dead;
STATISTICS.DEAD(r+1)
STATISTICS.ALLIVE(r+1)
STATISTICS.PACKETS_TO_CH(r+1)
STATISTICS.PACKETS_TO_BS(r+1)
STATISTICS.COUNTCHS(r+1)
r=0:rmax;
figure (1);
plot(r/10,STATISTICS.DEAD);
xlabel('Rounds');
ylabel('Dead Nodes');
title('Aeon LEACH');
figure (2);
plot(r/10,STATISTICS.PACKETS_TO_BS);
xlabel('Rounds');
ylabel('Packets to BS');
title('Aeon LEACH');
figure (3);
plot(r/10,STATISTICS.COUNTCHS);
xlabel('Rounds');
ylabel('Number of Cluster Heads');
title('Aeon LEACH');
figure (4);
plot(r/10,STATISTICS.PACKETS_TO_CH);
xlabel('Rounds');
Aeon LEACH
Page 39
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
ylabel('Packets to CH')
title('Aeon LEACH');
figure (5);
plot(r/10,STATISTICS.ALLIVE);
xlabel('Rounds');
ylabel('Allive nodes')
title('Aeon LEACH');
%subplot(2,2,1);
%plot(r,STATISTICS.DEAD);
%xlabel('Rounds');
%ylabel('Dead Nodes ');
%subplot(2,2,2);
%plot(r,STATISTICS.PACKETS_TO_CH);
%xlabel('Rounds');
%ylabel('Packets to CH');
%legend('Aeon LEACH ST'); %,'LEACH'
%subplot(2,2,3);
%plot(r,STATISTICS.PACKETS_TO_BS);
%xlabel('Rounds');
%ylabel('Packets to BS');
%subplot(2,2,4);
%plot(r,STATISTICS.COUNTCHS);
%xlabel('Rounds');
%ylabel('Number of Cluster Heads');
%title('\bf LEACH');%
Aeon LEACH
Page 40
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Aeon LEACH Phase 2 MATLAB code:
clear;
%Field Dimensions - x and y maximum (in meters)
xm=100;
ym=100;
%x and y Coordinates of the Sink
sink.x=50;
sink.y=50;
%Number of Nodes in the field
n=100;
%Optimal Election Probability of a node
%to become cluster head
p=0.1;
%Energy Model (all values in Joules)
%Initial Energy
Eo=0.5;
%Eelec=Etx=Erx
ETX=50*0.000000001;
ERX=50*0.000000001;
%Transmit Amplifiers types
Efs=10*0.000000000001;
Emp=0.0013*0.000000000001;
%Data Aggregation Energy
EDA=5*0.000000001;
yd1=33;
%Values for Hetereogeneity
%Percentage of nodes than are advanced
m=0.1;
%\alpha times advance nodes have energy greater than normal nodes
a=2;
%maximum number of rounds
rmax=1500;
%Computation of do
do=sqrt(Efs/Emp);
Aeon LEACH
Page 41
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
Et=0;
%Creation of the random Sensor Network
%figure(1);
for i=1:1:n
S(i).xd=rand(1,1)*xm;
XR(i)=S(i).xd;
S(i).yd=rand(1,1)*ym;
YR(i)=S(i).yd;
S(i).G=0;
%initially there are no cluster heads only nodes
S(i).type='N';
temp_rnd0=i;
%Random Election of Normal Nodes
if (temp_rnd0>=m*n+1)
S(i).E=Eo;
E(i)=S(i).E;
S(i).ENERGY=0;
% plot(S(i).xd,S(i).yd,'o');
% hold on;
end
%Random Election of Advanced Nodes
if (temp_rnd0<m*n+1)
S(i).E=Eo*(1+a);
E(i)=S(i).E;
S(i).ENERGY=1;
% plot(S(i).xd,S(i).yd,'+');
% hold on;
end
Et=Et+S(i).E;
end
S(n+1).xd=sink.x;
S(n+1).yd=sink.y;
%plot(S(n+1).xd,S(n+1).yd,'x');
%First Iteration
%figure(1);
%counter for CHs
countCHs=0;
%counter for CHs per round
Aeon LEACH
Page 42
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
rcountCHs=0;
cluster=1;
countCHs;
rcountCHs=rcountCHs+countCHs;
flag_first_dead=0;
allive=n;
packets_TO_BS=0;
packets_TO_CH=0;
for r=0:1:rmax
r
%Election Probability for Normal Nodes
pnrm=( p/ (1+a*m) );
%Election Probability for Advanced Nodes
padv= ( p*(1+a)/(1+a*m) );
%Operation for heterogeneous epoch
if(mod(r, round(1/pnrm) )==0)
for i=1:1:n
S(i).G=0;
S(i).cl=0;
end
end
%Operations for sub-epochs
if(mod(r, round(1/padv) )==0)
for i=1:1:n
if(S(i).ENERGY==1)
S(i).G=0;
S(i).cl=0;
end
end
end
%hold off;
%Number of dead nodes
dead=0;
Aeon LEACH
Page 43
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
%Number of dead Advanced Nodes
dead_a=0;
%Number of dead Normal Nodes
dead_n=0;
%figure(1);
for i=1:1:n
%checking if there is a dead node
if (S(i).E<=0)
%plot(S(i).xd,S(i).yd,'red .');
dead=dead+1;
if(S(i).ENERGY==1)
dead_a=dead_a+1;
end
if(S(i).ENERGY==0)
dead_n=dead_n+1;
end
%hold on;
end
if S(i).E>0
S(i).type='N';
if (S(i).ENERGY==0)
%plot(S(i).xd,S(i).yd,'o');
end
if (S(i).ENERGY==1)
%plot(S(i).xd,S(i).yd,'+');
end
%hold on;
end
STATISTICS.DEAD(r+1)=dead;
STATISTICS.ALLIVE(r+1)=allive-dead;
end
%plot(S(n+1).xd,S(n+1).yd,'x');
%When the first node dies
if (dead==1)
if(flag_first_dead==0)
first_dead=r
Aeon LEACH
Page 44
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
flag_first_dead=1;
end
end
countCHs=0;
cluster=1;
for i=1:1:n
if(S(i).E>0)
temp_rand=rand;
if ( (S(i).G)<=0)
%Election of Cluster Heads for normal nodes
if( ( S(i).ENERGY==0 && ( temp_rand <= ( pnrm / ( 1 - pnrm *
mod(r,round(1/pnrm)) )) ) ) )
countCHs=countCHs+1;
packets_TO_BS=packets_TO_BS+1;
PACKETS_TO_BS(r+1)=packets_TO_BS;
S(i).type='C';
S(i).G=100;
C(cluster).xd=S(i).xd;
C(cluster).yd=S(i).yd;
%plot(S(i).xd,S(i).yd,'k*');
distance=sqrt( (S(i).xd-(S(n+1).xd) )^2 + (S(i).yd-(S(n+1).yd) )^2 );
C(cluster).distance=distance;
C(cluster).id=i;
X(cluster)=S(i).xd;
Y(cluster)=S(i).yd;
cluster=cluster+1;
%Calculation of Energy dissipated
distance;
if (distance>do)
S(i).E=S(i).E- ( (ETX+EDA)*(4000) + Emp*4000*(
distance*distance*distance*distance ));
end
if (distance<=do)
S(i).E=S(i).E- ( (ETX+EDA)*(4000) + Efs*4000*( distance * distance ));
end
end
Aeon LEACH
Page 45
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
%Election of Cluster Heads for Advanced nodes
if( ( S(i).ENERGY==1 && ( temp_rand <= ( padv / ( 1 - padv *
mod(r,round(1/padv)) )) ) ) )
countCHs=countCHs+1;
packets_TO_BS=packets_TO_BS+1;
%PACKETS_TO_BS(r+1)=packets_TO_BS;
S(i).type='C';
S(i).G=100;
C(cluster).xd=S(i).xd;
C(cluster).yd=S(i).yd;
%plot(S(i).xd,S(i).yd,'k*');
distance=sqrt( (S(i).xd-(S(n+1).xd) )^2 + (S(i).yd-(S(n+1).yd) )^2 );
C(cluster).distance=distance;
C(cluster).id=i;
X(cluster)=S(i).xd;
Y(cluster)=S(i).yd;
cluster=cluster+1;
%Calculation of Energy dissipated
distance;
if (distance>do)
S(i).E=S(i).E- ( (ETX+EDA)*(4000) + Emp*4000*(
distance*distance*distance*distance ));
end
if (distance<=do)
S(i).E=S(i).E- ( (ETX+EDA)*(4000) + Efs*4000*( distance * distance ));
end
end
end
end
end
packets_TO_BS=packets_TO_BS+1;
STATISTICS.packets_TO_BS(r+1)=packets_TO_BS;
Aeon LEACH
Page 46
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
%Election of Associated Cluster Head for Normal Nodes
for i=1:1:n
if ( S(i).type=='N' && S(i).E>0 )
if(cluster-1>=1)
min_dis=sqrt( (S(i).xd-S(n+1).xd)^2 + (S(i).yd-S(n+1).yd)^2 );
min_dis_cluster=1;
for c=1:1:cluster-1
temp=min(min_dis,sqrt( (S(i).xd-C(c).xd)^2 + (S(i).yd-C(c).yd)^2 ) );
if ( temp<min_dis )
min_dis=temp;
min_dis_cluster=c;
end
end
%Energy dissipated by associated Cluster Head
min_dis;
if (min_dis>do)
S(i).E=S(i).E- ( ETX*(4000) + Emp*4000*( min_dis * min_dis * min_dis *
min_dis));
end
if (min_dis<=do)
S(i).E=S(i).E- ( ETX*(4000) + Efs*4000*( min_dis * min_dis));
end
%Energy dissipated
if(min_dis>0)
S(C(min_dis_cluster).id).E = S(C(min_dis_cluster).id).E- ( (ERX +
EDA)*4000 );
PACKETS_TO_CH(r+1)=n-dead-cluster+1;
end
S(i).min_dis=min_dis;
S(i).min_dis_cluster=min_dis_cluster;
end
end
end
%hold on;
countCHs;
rcountCHs=rcountCHs+countCHs;
end
Aeon LEACH
Page 47
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
%figure(1);
for i=1:1:n
if (i<=5)
S2(i).xd=rand(1,1)*xm;
S2(i).yd=rand(1,1)*yd1;
S2(i).E=Eo*(1+a);
S2(i).ENERGY=1;
S2(i).type='A';
%plot(S2(i).xd,S2(i).yd,'og');
%hold on
end
if (i>10 && i<=100)
S2(i).xd=rand(1,1)*xm;
S2(i).yd=33+rand(1,1)*yd1;
S2(i).E=Eo;
S2(i).ENERGY=0;
S2(i).type='N';
%plot(S2(i).xd,S2(i).yd,'ob');
%hold on
end
if(i<=10 && i>5)
S2(i).xd=rand(1,1)*xm;
S2(i).yd=66+rand(1,1)*yd1;
S2(i).E=Eo*(1+a);
S2(i).ENERGY=1;
S2(i).type='A';
%plot(S2(i).xd,S2(i).yd,'og');
%hold on
end
end
S2(n+1).xd=sink.x;
S2(n+1).yd=sink.y;
%%plot(S2(n+1).xd,S2(n+1).yd,'green x');
%figure(1);
flag_first_dead2=0;
allive2=n;
%counter for bit transmitted to Bases Station and to Cluster Heads
packets_TO_BS12=0;
Aeon LEACH
Page 48
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
packets_TO_BS22=0;
packets_TO_BS2=0;
packets_TO_CH2=0;
for r=0:1:rmax
r
%Election Probability for Advanced Nodes
padv= ( p*(1+a)/(1+(a*m)) );
%Operations for sub-epochs
if(mod(r, round(1/padv) )==0)
for i=1:1:n
if(S2(i).ENERGY==1)
S2(i).G=0;
%S2(i).cl=0;
end
end
end
%hold off;
%figure(1);
dead2=0;
%Number of dead Advanced Nodes
dead_a2=0;
%Number of dead Normal Nodes
dead_n2=0;
for i=1:1:n
%checking if there is a dead node
if (S2(i).E<=0)
%%plot(S2(i).xd,S2(i).yd,'red .');
dead2=dead2+1;
if(S2(i).ENERGY==1)
dead_a2=dead_a2+1;
end
if(S2(i).ENERGY==0)
dead_n2=dead_n2+1;
Aeon LEACH
Page 49
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
end
%hold on;
end
if (S2(i).E>0)
S2(i).type='N';
if (S2(i).ENERGY==0)
%plot(S2(i).xd,S2(i).yd,'ob');
end
if (S2(i).ENERGY==1)
%plot(S2(i).xd,S2(i).yd,'og');
end
%hold on;
end
%plot(S2(n+1).xd,S2(n+1).yd,'green x');
STATISTICS.DEAD2(r+1)=dead2;
STATISTICS.ALLIVE2(r+1)=allive2-dead2;
end
%When the first node dies
if (dead2==1)
if(flag_first_dead2==0)
first_dead2=r
flag_first_dead2=1;
end
end
for(i=1:1:n)
if(S2(i).E>=0)
if(S2(i).type=='N')
distance=sqrt( (S2(i).xd-(S2(n+1).xd) )^2 + (S2(i).yd-(S2(n+1).yd) )^2 );
if (distance>do)
S2(i).E=S2(i).E- ( (ETX+EDA)*(4000) + Emp*4000*(
distance*distance*distance*distance ));
end
if (distance<=do)
S2(i).E=S2(i).E- ( (ETX+EDA)*(4000) + Efs*4000*( distance * distance ));
end
packets_TO_BS12=packets_TO_BS12+1;
end
end
end
Aeon LEACH
Page 50
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
countCHs2=0;
cluster2=1;
for i=1:1:n
if(S2(i).E>=0)
if(S2(i).G<=0)
if(S2(i).type=='A')
temp_rand=rand;
if( ( S2(i).ENERGY==1 && ( temp_rand <= ( padv / ( 1 - padv *
mod(r,round(1/padv)) )) ) ) )
countCHs2=countCHs2+1;
packets_TO_BS22=packets_TO_BS22+1;
S2(i).type='C';
S2(i).G=(1/padv)-1;
C(cluster2).xd=S2(i).xd;
C(cluster2).yd=S2(i).yd;
%plot(S2(i).xd,S2(i).yd,'k*');
distance=sqrt( (S2(i).xd-(S2(n+1).xd) )^2 + (S2(i).yd-(S2(n+1).yd) )^2 );
C(cluster2).distance=distance;
C(cluster2).id=i;
X(cluster2)=S2(i).xd;
Y(cluster2)=S2(i).yd;
cluster2=cluster2+1;
%
Calculation of Energy dissipated
distance;
if (distance>do)
S2(i).E=S2(i).E- ( (ETX+EDA)*(4000) + Emp*4000*(
distance*distance*distance*distance ));
end
if (distance<=do)
S2(i).E=S2(i).E- ( (ETX+EDA)*(4000) + Efs*4000*( distance *
distance ));
end
end
Aeon LEACH
Page 51
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
end
end
for i=1:1:n
if ( S2(i).type=='A' && S2(i).E>0 )
if(cluster2-1>=1)
min_dis=inf;
min_dis_clustera=1;
for c=1:1:cluster2-1
temp=min(min_dis,sqrt( (S2(i).xd-C(c).xd)^2 + (S2(i).yd-C(c).yd)^2 )
);
if ( temp<min_dis )
min_dis=temp;
min_dis_cluster2=c;
end
end
%Energy dissipated by Cluster menmber for transmission of packet
% min_dis;
if (min_dis>do)
S2(i).E=S2(i).E- ( ETX*(4000) + Emp*4000*( min_dis * min_dis *
min_dis * min_dis));
end
if (min_dis<=do)
S2(i).E=S2(i).E- ( ETX*(4000) + Efs*4000*( min_dis * min_dis));
end
%Energy dissipated by clustre head in receving
if(min_dis>0)
S2(C(min_dis_cluster2).id).E = S2(C(min_dis_cluster2).id).E- ( (ERX
+ EDA)*4000 );
PACKETS_TO_CH(r+1)=n-dead-cluster2+1;
end
S2(i).min_dis=min_dis;
S2(i).min_dis_cluster2=min_dis_cluster2;
end
end
end
end
Aeon LEACH
Page 52
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
CLUSTERHS(r+1)=cluster2+1;
STATISTICS.CLUSTERHEADS2(r+1)=cluster2+1;
end
packets_TO_BS2=packets_TO_BS12+packets_TO_BS22;
STATISTICS.PACKETS_TO_BS2(r+1)=packets_TO_BS2;
end
for i=1:1:n
S3(i).xd=rand(1,1)*xm;
XR(i)=S3(i).xd;
S3(i).yd=rand(1,1)*ym;
YR(i)=S3(i).yd;
S3(i).G=0;
%initially there are no cluster heads only nodes
S3(i).type='N';
temp_rnd0=i;
%Random Election of Normal Nodes
if (temp_rnd0>=m*n+1)
S3(i).E=Eo;
S3(i).ENERGY=0;
%plot(S3(i).xd,S3(i).yd,'o');
%hold on;
end
%Random Election of Advanced Nodes
if (temp_rnd0<m*n+1)
S3(i).E=Eo*(1+a)
S3(i).ENERGY=1;
%plot(S3(i).xd,S3(i).yd,'+');
%hold on;
end
end
S3(n+1).xd=sink.x;
S3(n+1).yd=sink.y;
%plot(S3(n+1).xd,S3(n+1).yd,'x');
Aeon LEACH
Page 53
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
%First Iteration
%figure(1);
%counter for CHs
countCHs3=0;
%counter for CHs per round
rcountCHs3=0;
cluster3=1;
countCHs3;
rcountCHs3=rcountCHs3+countCHs3;
flag_first_dead3=0;
allive3=n;
packets_TO_BS3=0;
packets_TO_CH3=0;
for r=0:1:rmax
r
%Operation for epoch
if(mod(r, round(1/p) )==0)
for i=1:1:n
S3(i).G=0;
S3(i).cl=0;
end
end
%hold off;
%Number of dead nodes
dead3=0;
%Number of dead3 Advanced Nodes
dead_a3=0;
%Number of dead Normal Nodes
dead_n3=0;
%figure(1);
for i=1:1:n
%checking if there is a dead node
if (S3(i).E<=0)
%plot(S3(i).xd,S3(i).yd,'red .');
dead3=dead3+1;
Aeon LEACH
Page 54
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
if(S3(i).ENERGY==1)
dead_a3=dead_a3+1;
end
if(S3(i).ENERGY==0)
dead_n3=dead_n3+1;
end
%hold on;
end
if S3(i).E>0
S3(i).type='N';
if (S3(i).ENERGY==0)
%plot(S3(i).xd,S3(i).yd,'o');
end
if (S3(i).ENERGY==1)
%plot(S3(i).xd,S3(i).yd,'+');
end
%hold on;
end
STATISTICS.DEAD3(r+1)=dead3;
STATISTICS.ALLIVE3(r+1)=allive3-dead3;
end
%plot(S(n+1).xd,S(n+1).yd,'x');
%When the first node dies
if (dead3==1)
if(flag_first_dead3==0)
first_dead3=r
flag_first_dead3=1;
end
end
countCHs3=0;
cluster3=1;
for i=1:1:n
if(S3(i).E>0)
temp_rand=rand;
if ( (S3(i).G)<=0)
%Election of cluster3 Heads
if(temp_rand<= (p/(1-p*mod(r,round(1/p)))))
countCHs3=countCHs3+1;
Aeon LEACH
Page 55
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
packets_TO_BS3=packets_TO_BS3+2;
% PACKETS_TO_BS3(r+1)=packets_TO_BS3;
S3(i).type='C';
S3(i).G=round(1/p)-1;
C(cluster3).xd=S3(i).xd;
C(cluster3).yd=S3(i).yd;
%plot(S3(i).xd,S3(i).yd,'k*');
distance=sqrt( (S3(i).xd-(S3(n+1).xd) )^2 + (S3(i).yd-(S3(n+1).yd) )^2 );
C(cluster3).distance=distance;
C(cluster3).id=i;
X(cluster3)=S3(i).xd;
Y(cluster3)=S3(i).yd;
cluster3=cluster3+1;
%Calculation of Energy dissipated
distance;
if (distance>do)
S3(i).E=S3(i).E- ( (ETX+EDA)*(4000) + Emp*4000*(
distance*distance*distance*distance ));
end
if (distance<=do)
S3(i).E=S3(i).E- ( (ETX+EDA)*(4000) + Efs*4000*( distance * distance
));
end
end
end
end
end
STATISTICS.CLUSTERHEADS3(r+1)=cluster3-1;
CLUSTERHS(r+1)=cluster3-1;
%Election of Associated Cluster Head for Normal Nodes
for i=1:1:n
if ( S3(i).type=='N' && S3(i).E>0 )
if(cluster3-1>=1)
min_dis=sqrt( (S3(i).xd-S3(n+1).xd)^2 + (S3(i).yd-S3(n+1).yd)^2 );
min_dis_cluster=1;
for c=1:1:cluster3-1
temp=min(min_dis,sqrt( (S3(i).xd-C(c).xd)^2 + (S3(i).yd-C(c).yd)^2 ) );
Aeon LEACH
Page 56
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
if ( temp<min_dis )
min_dis=temp;
min_dis_cluster=c;
end
end
%Energy dissipated by associated Cluster Head
min_dis;
if (min_dis>do)
S3(i).E=S3(i).E- ( ETX*(4000) + Emp*4000*( min_dis * min_dis * min_dis
* min_dis));
end
if (min_dis<=do)
S3(i).E=S3(i).E- ( ETX*(4000) + Efs*4000*( min_dis * min_dis));
end
%Energy dissipated
if(min_dis>0)
S3(C(min_dis_cluster).id).E = S3(C(min_dis_cluster).id).E- ( (ERX +
EDA)*4000 );
PACKETS_TO_CH3(r+1)=n-dead3-cluster3+1;
end
S3(i).min_dis=min_dis;
S3(i).min_dis_cluster=min_dis_cluster;
end
end
end
%hold on;
packets_TO_BS3=packets_TO_BS3+1;
STATISTICS.packets_TO_BS3(r+1)=packets_TO_BS3;
countCHs3;
rcountCHs3=rcountCHs3+countCHs3;
end
figure(2);
r=0:rmax;
plot(r,STATISTICS.ALLIVE3(r+1),'-b',r,STATISTICS.ALLIVE2(r+1),'-g')
legend('LEACH m=0.1,a=2','Aeon Leach 2 m=0.1,a=2');
xlabel('Rounds');
ylabel('Allive Nodes');
Aeon LEACH
Page 57
Vidhi Nagri | Dept. of Electrical Engineering |California State University, Long Beach | Summer 2014
figure(3);
plot(r,STATISTICS.DEAD3(r+1),'-b',r,STATISTICS.DEAD2(r+1),'-g')
legend('LEACH m=0.1,a=2','Aeon Leach 2 m=0.1,a=2');
xlabel('Rounds');
ylabel('Dead Nodes');
figure(4);
plot(r,STATISTICS.packets_TO_BS(r+1),r,STATISTICS.PACKETS_TO_BS2(r+1),'-g')
legend('LEACH m=0.2,a=1','Aeon Leach 2 m=0.2,a=1');
xlabel('Rounds');
ylabel('Packets to BS');
Aeon LEACH
Page 58