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EESCA: Energy efficient structured clustering algorithm for wireless sensor networks

Authors:
Yuvaraj Padmanaban at SAVEETHA ENGINEERING COLLEGE
Yuvaraj Padmanaban
Venkata Lakshmi Narayana Komanapalli at VIT University
Venkata Lakshmi Narayana Komanapalli
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Appropriate cluster head selection process in hierarchical cluster based routing algorithms is vital to make the wireless sensor networks energy efficient. This paper suggests a hybrid cluster head selection method with the parameters Location centrality and Nodes' lingering energy on the fixed clusters. The simulation outcome illustrates that the proposed algorithm is good at load balancing with very low control overhead and extending network lifetime compared to conventional routing algorithm Low-Energy Adaptive Clustering Hierarchy (LEACH).
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EESCA: ENERGY EFFICIENT
STRUCTURED CLUSTERING
ALGORITHM FOR WIRELESS SENSOR
NETWORKS
Presented by
Yuvaraj. P
Research Scholar
VIT University, Vellore, Tamilnadu
CAST 2016
Date: 19/12/2016
Paper Id: 478
CONTENTS
Introduction
Design challenges of WSN
Motivation of this proposal
Objectives of this proposal
Proposed algorithm (EESCA) details
Simulation Results
Conclusion
References
2
INTRODUCTION
Wireless Sensor Network (WSN) is a large
network of individual sensors (Nodes).
We can have any number of nodes as per the
application.
Nodes are deployed for a certain well –defined
purpose.
They are generally left unattended.
Inexpensive.
Battery operated.
Batteries can not be replaced or recharged.
3
INTRODUCTION CONTD..
Need for WSN
It is important to have wireless communication
where fixed platform is not suitable.
Rapid development in wireless technologies leads
to the increased number of information
transmissions wirelessly.
A wide range of sensors is available for
measuring various signals from the environment.
So, WSN is a very essential part to monitor and
control the environmental parameters for many
applications. 4
INTRODUCTION CONTD..
Example applications
Usage in tsunami forecast 5
INTRODUCTION CONTD..
Example applications
Habitat monitoring 6
INTRODUCTION CONTD..
Other applications
Identifying unauthorized movements of enemy
submarines and autonomous underwater vehicles
(AUVs).
Active volcano monitoring .
Forecasting climate changes in arctic and
Antarctic regions.
Forest-fire monitoring.
7
INTRODUCTION CONTD..
Data Gathering in WSN
Communication can be classified in to three
types.
They are Direct communication (Single hop),
Multi hop communication and Clustered
communication.
Clustered communication is accepted world wide
as better to get good energy efficiency, scalability,
load balancing, stabilized network topology,
increased connectivity, collision avoidance, and
data aggregation.
8
INTRODUCTION CONTD..
Direct Communication
9
INTRODUCTION CONTD..
Multi-hop Communication
10
INTRODUCTION CONTD..
Clustered Communication
11
DESIGN CHALLENGES OF WSN
12
Primary challenges
Reliability
Security
Performance
Energy Constraints
Self-organizing and self-healing
Implementation in real time applications
DESIGN CHALLENGES OF WSN CONTD..
13
Secondary challenges
Cost-effectiveness
Flexibility
scalability
Fault tolerance
robustness
Routing
Transmission time
MOTIVATION OF THIS PROPOSAL
Despite of the remarkable growth of WSN there
are many challenges for researchers, such as
improving energy efficiency, enhancing
scalability, enriching the performance and so on.
More advanced ways of gathering the useful
information have to be developed in various
levels to get more efficient and reliable
information with low cost to adopt for different
applications.
Low Energy Adaptive Clustering Hierarchy
(LEACH) is a famous clustering algorithm for
making the network energy efficient. 14
MOTIVATION OF THIS PROPOSAL CONTD..
Low Energy Adaptive Clustering Hierarchy
(LEACH)
The initial platform for clustering based
algorithms is set by LEACH.
It has introduced a simple way of selecting a set
of CHs for each round. 5% of total sensor nodes
are selected as CHs for optimum performance.
Each sensor node calculates a probability
threshold value based on optimum % of CHs and
rotation of CH role for fixed preset-rounds.
15
MOTIVATION OF THIS PROPOSAL CONTD..
LEACH contd..
Then a random number is generated between 0
and 1 and it is compared with that threshold
value. If the random value is lesser than the
threshold value, the node can act as aCH.
LEACH uses local data compression to send only
the consolidated data to the BS and load is
uniformly distributed among the nodes.
Since it uses a pure random process, the energy
of the nodes is not considered and scalability is
limited.
16
MOTIVATION OF THIS PROPOSAL CONTD..
Cluster based routing algorithms are proved very
useful for achieving better energy efficiency.
A cluster head gathers all information from the
nodes and aggregates them. An aggregated data
alone is sent to the BS.
A suitable cluster head selection and a rotation of
cluster heads in right intervals can make the
wireless sensor network energy efficient.
Although many algorithms have been proposed
like LEACH in the literature for improving the
energy efficiency of WSN, still there is a scope for
improvement. 17
OBJECTIVES OF THIS PROPOSAL
Improving the life time of the network
Balanced Cluster formation
Flexibility and scalability
Self-organizing and self-healing
Efficient Routing
18
PROPOSED ALGORITHM (EESCA) DETAILS
Network model
Network consists of N sensors deployed randomly
over the area of interest. For wireless
communication, the popular first order radio
model is used.
Necessary energy to transmit a bit data to a
distance d is:
The essential energy to receive a k bit data is:
19
EESCA DETAILS CONTD..
Key assumptions
All the nodes can send the data directly to BS.
Nodes are equipped with equal resources and
hence are homogenous in nature.
They can determine other nodes’ distances by
considering signal strength received.
Information is sent to the destination every
round.
The nodes can vary power levels based on the
communication distance.
They don’t contain GPS or any other
arrangement to know the location. 20
EESCA DETAILS CONTD..
The algorithm works in two phases namely setup
phase and steady state phase.
Based on geographical locations the clusters are
divided in the setup phase. The cluster heads for
the clusters are selected periodically.
The nodes send sensed information to the cluster
head and the cluster head sends the aggregated
data to the base station in the steady state phase.
This algorithm selects the cluster head in hybrid
modes based on cluster head centrality and
nodes’lingering energy.
21
EESCA DETAILS CONTD..
Cluster formation process in mode 1
22
EESCA DETAILS CONTD..
Cluster formation process in mode 2
In mode 2, cluster head selection process is based
on the lingering energy in the nodes.
Node which has the higher lingering energy acts
as the cluster head for the corresponding rounds.
23
EESCA DETAILS CONTD..
Cluster configuration
The cluster head from each cluster sends CH-
MSG which includes its ID and one secret code.
The non-cluster head nodes send JOIN-MSG to
respective cluster heads.
Using ENERGY-MSG, the information about the
lingering energies of the nodes is gathered by the
other nodes.
After the cluster formation, a TDMA schedule is
framed for the time bound data transmission.
The cluster heads of the bottom clusters send the
data to BS through the cluster heads in the
middle using multi-hop communication. 24
SIMULATION RESULTS
Simulation parameters
25
S.
No
Parameter
Scene 1
Scene 2
1
N
100
100
2
Area
100 × 100
200 × 200
3
Location of BS
(50,175)
(100,150)
4
Packet size
4000 bits
4000 bits
5
Einitial
0.5 J
0.5 J
6
ETX
50 nJ/bit
50 nJ/bit
7
d0
87 m
87 m
8
εmp
0.0013 pJ/bit/m4
0.0013 pJ/bit/m4
9
εfs
10 pJ/bit/m2
10 pJ/bit/m2
10
EDA
5 nJ/bit/message
5 nJ/bit/message
SIMULATION RESULTS CONTD..
Simulation results
26
S.
No
Protocol
Last Node dies at
Round
Scene 1
Scene 2
Scene 1
Scene 2
1
LEACH
727
338
1205
1021
2
EESCA
992
710
1215
1300
SIMULATION RESULTS CONTD..
Random Node placement
27
SIMULATION RESULTS CONTD..
Cluster formations in LEACH
28
SIMULATION RESULTS CONTD..
Cluster formations in EESCA
29
SIMULATION RESULTS CONTD..
Network lifetime comparison of LEACH and
EESCA (Scene 1)
30
SIMULATION RESULTS CONTD..
Network lifetime comparison of LEACH and
EESCA (Scene 2)
31
CONCLUSION
Energy efficiency is a primary thing to be
considered while adopting the wireless sensor
networks for real time applications.
We have proposed a hybrid cluster head selection
algorithm EESCA, to make the network efficient.
The proposed algorithm is very simple and it
reduces the control overhead and thereby
decreases the energy expenditure considerably.
Simulation results show that EESCA achieves
good load balancing and the improved energy
efficiency compared to the conventional LEACH.
32
REFERENCES
I.F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci,
“Wireless sensor networks: a survey”, Computer Networks,
Elsevier, Vol. 38, Issue. 4, 2002,pp.393-422.
W. Dargie and C. Poellabaur, “Fundamentals of Wireless
Sensor Networks: Theory and Practice”, Wiley Series on
Wireless Communications and Mobile Computing, New York,
2010.
J. Heidemann, M. Stojanovic, and M. Zorzi, “Underwater
sensor networks: Applications, advances and challenges”, Phil.
Trans. R. Soc. A, The Royal Socity, Vol. 370, Issue.1958,2012,
pp.158-175.
R. Lara, D. Benitez, A. Caamano, M. Zennaro, and J.L. Rojo-
Alverez, “On Real-Time Performance Evaluation of Volcano-
Monitoring Systems With Wireless Sensor Networks”, IEEE
Sensors, Vol. 15, Issue. 6, 2015,pp.3514-3523.
F. Wang and J. Liu, “Networked Wireless Sensor Data
Collection: Issues, Challenges, and Approaches”, IEEE
Communications Surveys & Tutorials, Vol. 13, Issue. 4, 2011,
pp.673-687.
33
REFERENCES CONTD..
M. Mehdi Afsar and M.H. Tayarani-N, “Clustering in sensor
networks: A literature survey”, Journal of Network and Computer
Applications, Elsevier, Vol. 46,2014,pp.198-226.
A. Abbasi and M. Younis, “A survey on clustering algorithms for
wireless sensor networks”, Computer Communications, Elsevier, Vol.
30,Issue.14-15,2007,pp.2826-2841.
W.B. Heinzelman, A.P. Chandrakasan, and H. Balakrishnan, “An
application-specific protocol architecture for wireless microsensor
networks”, IEEE Transactions on Wireless Communications, Vol. 1,
Issue. 4, 2002,pp.660-670.
O. Younis and S. Fahmy, “HEED: a hybrid, energy-efficient,
distributed clustering approach for ad hoc sensor networks”, IEEE
Transactions on Mobile Computing, Vol. 3, Issue. 4, 2004,pp.366-379.
M. Sabet and H.R. Naji, “A decentralized energy efficient hierarchical
cluster-based routing algorithm for wireless sensor networks”,
International Journal of Electronics and Communications, Elsevier,
Vol. 69,Issue. 5, 2015,pp.790-799.
M. Tarhani, Y.S. Kavian, and S. Siavoshi, “SEECH: Scalable Energy
Efficient Clustering Hierarchy Protocol in Wireless Sensor Networks”,
IEEE Sensors Journal, Vol. 14,Issue.11,2014,pp.3944-3954.34
THANK YOU
35
... Depending on not only energy but also data positioning CH is elected. The procedure of CH election is completed through hybrid way depending on position and remaining power in EESCA [6]. ...
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