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OPTIMIZING CLUSTERING STRATEGY
FOR WIRELESS
SENSOR NETWORKS12MICT21 Avish Shah
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A sensor network is a network of low-powered, energy-constrained
nodes equipped with sensor(s), processors, memory and
wireless communication devices. [2]
Introduction :
Recent technological advances in the field of micro-electro-mechanical
systems (MEMS) have made the development of tiny, low-cost,
low-powered and multi-functional sensor nodes technically and
economically feasible [3,4].
A great deal of research has focused on energy conservation in
sensor networks so that the lifetime of the network is maximized.
One approach is to introduce some special nodes, known as relay
nodes, in sensor networks [5,6,7].
Defination :
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Fig. 1. General Sensor Network Architecture [1]
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DATA GATHERING CLUSTERING MODEL
Fig. 1. An example of
hierarchical sensor
network. [8]
Cardinality into Account
In [8], the authors define
cardinality of a cluster as the
number of sensor nodesassociated with the cluster and
provide a heuristic that
attempts to minimize the
variance of the cardinality of
each cluster in the system. The
idea is to distribute the sensornodes as evenly as possible,
over all the clusters.
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key attributes that designers must carefully consider
Cost of Clustering
Selection of Clusterheads and Clusters
Real-Time Operation
Synchronization
Data Aggregation:
Repair Mechanisms
Quality of Service (QoS)
limited energy in sensor nodes must be considered as proper clustering
can reduce the overall energy usage in a network. [1]
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OVERVIEW OF PROPOSED ALGORITHMS
Fig. 2. Classification of Proposed Clustering Schemes [1]
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Linked Cluster Algorithm (LCA)
Linked Cluster Algorithm 2
Highest-Connectivity Cluster Algorithm
Max-Min D-Cluster Algorithm
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Weighted Clustering Algorithm (WCA)
Clusterhead election procedure
Complexity due to distributiveness
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LEACH - Low-Energy Adaptive Clustering Hierarchy
Two-Level Hierarchy LEACH TL- LEACH
Energy Efficient Clustering Scheme(or EECS)
Hybrid Energy-Efficient Distributed Clusterin (or HEED)
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Power-Efficient GAthering in Sensor
Information Systems (or PEGASIS)
GROUP
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PERFORMANCE OF PROPOSED ALGORITHMS [1]
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ILP-S and ILP-M.
Network model
(i) for each sensor node, a label i; 1 < i < n
(ii) for each relay node, a label j; n < j < m+n
(iii) for the base station, a label n +m + 1.
In our model, data gathering is proactive
i.e., data are collected and forwarded to the base station
periodically, following a predefined schedule.We refer to each period of data gathering as a round [9].
measure the lifetime of the network:
we use the N-of-N metric [6] to measure the network lifetime.
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where N lifetime
denotes the lifetime of the network in terms of rounds,
E initial
denotes the initial energy of each relay node and
F max
is themaximum energy dissipated by any relay node in a
round.
the lifetime of the network is defined by the ratio
of the initial energy to the maximum energy dissipated by any relaynode in a round[2].
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The ILP formulation for single hop routing (ILP-S) [2]
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The ILP formulation multi-hop routing (ILP-M) [2]
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Assumptions in ILP Formulations:
o Assumes once deployed network will Stationary.
o Needs GPS which is not available in some Sensor networks.
o N-of-N metric to compute lifetime.
Future Works:
What if Network is Mobile ?
What if GPS not available.?
Consider other metric to compute Lifetime.
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1) A Survey of Clustering Algorithms for Wireless
Sensor Networks
D. J. Dechene, A. El Jardali, M. Luccini, and A. Sauer.
Department of Electrical and Computer Engineering
The University Of Western Ontario
London, Ontario, Canada
{ddechene, aeljarda, mluccini, asauer2}@uwo.ca - 2012
2) Clustering strategies for improving the lifetime of two-tiered sensor networks
Ataul Bari, Arunita Jaekel *, Subir Bandyopadhyay 2008
journal homepage: www.elsevier.com/locate/comcom
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Computing and Networking, 2003, pp. 286299.
7) T. Stathopoulos, L. Girod, J. Heideman, D. Estrin, K. Weeks, Centralized routing
for resource-constrained wireless sensor networks (SYS 5). Available from:
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mailto:asauer2%[email protected]://www.elsevier.com/locate/comcomhttp://www.elsevier.com/locate/comcommailto:asauer2%[email protected]:asauer2%[email protected]7/27/2019 Optimizing Clustering Strategy for Wireless Sensor Networks
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8) G. Gupta, M. Younis, Load-balanced clustering of wireless sensor networks, in: IEEE
International Conference on Communications, vol. 3, 2003, pp.18481852.
9) A. Bari, A. Jaekel, S. Bandyopadhyay, Optimal placement and routing strategies for resilient
two-tiered sensor networks, Wireless Communications and Mobile Computing, Wiley, 2008,doi:10.1002/wcm.639.