CLUSTRING IN WIRELESS
SUBMITTED IN PARTIAL FULLFILLMENT OF THE REQUIREMENT
FOR THE AWARD OF THE DEGREE OF
MASTER OF TECHNOLOGY
(Computer Science and Engineering)
Wireless Sensor Network
Objective of Clustering
Classification of Clustering
Hot Spot Problem
Energy Efficient Unequal Clustering
Comaprisons Of EEUC with Other Algorithms
WHAT IS WIRELESS SENSOR
WSN consists of spatially distributed autonomous
sensors to monitor physical or environmental
conditions, such as temperature, sound, pressure
Collaborative Network of small Wireless Sensor
devices, sensing a physical phenomenon.
Formed by hundreds or thousands of nodes that
communicate with each other and pass data along
from one to another.
ROUTING MODELS IN CLUSTERING
Single –Hop Multi-Hop
HOT SPOT PROBLEM
In single-hop communication:- Every sensor node will
directly transmit the data to the base station, so the nodes
furthest away from the base station are the most critical
In multi-hop communication:-Due to the limited
transmission range, data’s are forced to route over several
hops until they reach the final destination nodes that are
closest to the base station are burdened with heavy relay
traffic and they die first.
SOLUTION OF HOT SPOT PROBLEM
EECU:- Energy- Efficient Unequal Clustering Algorithm
In EECS a distance-based cluster formation method is
proposed to produce clusters of unequal size in single
hop networks. A weighted function is introduced to let
clusters farther away from the base station have
smaller sizes, thus some energy could be preserved
for long-distance data transmission to the base station.
ENERGY- EFFICIENT UNEQUAL CLUSTERING
EEUC partitions the nodes into Clusters of
Unequal size, and Clusters closer to the
Base Station have smaller sizes than those
farther away from the base station.
Thus Cluster heads closer to the base
station can preserve some energy for the
inter-cluster data forwarding.
ENERGY SAVING SCHEMES
IN CLUSTERING TECHNOLOGY
Cluster Formation and Rotation
Cluster Head Election and Rotation
WORKING OF EEUC
EECU Initial Diagram
BASIC BLOCK DIAGRAM
LEACH (Low Power Adaptive Clustering
HEED(Hybrid Energy Efficient Distributed )
WCA (Weighted Clustering Algorithm)
K-MEANS (K-Hop Clustering Algorithm)
It uses circular random clustering methods and each node in
the network can be a cluster head in rotation, this makes the
energy- carrying of the network balancing to each
node, extending the lifetime of the network.
BASIC BLOCK DIAGRAM
DISADVANTAGE OF LEACH
1.Applicable to only single hop communication
2.LEACH assumes all the nodes to have same initial
energy, which is not the case always in real-time
3.It cannot be applied for mobile nodes, failure of
cluster-heads creates a lot of problems
COMPARISONS OF EECU WITH
WCA:-WCA is a classical algorithm based on
node degree, the number of single-hop
MAIN DRAWBACK :- The main drawback of
WCA is that it needs to obtain the weight of the
node and require each node to save all the
information of nodes before initializing
network, so excessive amounts of computing and
communications may cause excessive
consumption in clustering directly.
K-clustering algorithm can constitute maximum k-
hop non-overlapping clusters with partial networks
topology information rather than the whole network
topology. At the same time, it can also save energy to
prolong network survival time.
PROBLEM :-The algorithm is more effective in
restricting data forwarding distance, but it still doesn’t
solve unbalanced clustering (excessive clustering
Result shows that our unequal clustering
mechanism balances the energy consumption
well among all sensor nodes and achieves an
obvious improvement on the network lifetime.
 Kazem Sohraby, Daniel Minoli, Taieb Znati “WIRELESS SENSOR NET- WORKS
Technology, Protocols, and Applications” John Wiley, New York, 2007.
 S.Mohanty and S.K.Patra,“A novel Bio-inspired Clustering algorithm for Wireless
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 O. Younis,M Krunz, S. Ramasubramanian “Node clustering in wireless sensor
networks: Recent developments and deployment challenges”, IEEE May 2006.
 Chengfa Li, Mao Ye, “An Energy-Efﬁcient Unequal Clustering Mechanism for
Wireless Sensor Networks”
 Ying Liao, Huan Qi, and Weiqun Li “Load-Balanced Clustering Algorithm With
Distributed Self-Organization for Wireless Sensor Networks ”IEEE May 2013.
 W. R. Heinzelman A. P. Chandrakasan and H. Balakrishnan “Energy- efﬁcient
communication protocol for wireless micro sensor networks”
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networks, May 2000
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for Wireless Sensor Networks”