optimizing clustering strategy for wireless sensor networks

7/27/2019 Optimizing Clustering Strategy for Wireless Sensor Networks

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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

3) I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, Wireless sensor

networks: a survey, Computer Networks 38 (2002) 393422.

4) C.-Y. Chong, S.P. Kumar, Sensor networks: evolution, opportunities, and

challenges, Proceedings of the IEEE 91 (8) (2003) 12471256.

5) X. Cheng, D-Z. Du, L. Wang, B.B. Xu, Relay sensor placement in wireless sensor

networks, IEEE Transactions on Computers (2001). http://citeseer.ist.psu.edu/

cheng01relay.html .

6) J. Pan, Y.T. Hou, L. Cai, Y. Shi, S.X. Shen, Topology control for wireless sensor

networks, in: Proceedings of Ninth Annual International Conference on Mobile

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:

, 2006.
mailto:asauer2%[email protected]://www.elsevier.com/locate/comcomhttp://www.elsevier.com/locate/comcommailto:asauer2%[email protected]:asauer2%[email protected]


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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.

optimizing clustering strategy for wireless sensor networks

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