Stochastic Approach for Energy-Efficient Clustering in WSN

Stochastic Approach for Energy-Efficient Clustering in WSN

Manpreet Kaur

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Lokesh Pawar

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Rohit Bhullar

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α Chandigarh University

σ Kurukshetra University

Stochastic Approach for Energy-Efficient Clustering in WSN

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Abstract

Wireless sensor networks are self-organizing networks in which sensor nodes with limited resource are scattered in an area of interest to gather information. WSNs need to have effective node’s energy management methods for stable and seamless communication. Power efficient clustering is done in WSN to prolong the life of the network. In WSN, many algorithms are developed to save energy of sensor nodes and to increase the lifetime of the network. This paper provides an energy efficient clustering algorithm inspired by prophet routing protocol to enhance the cluster based operation of the nodes. Adaptive learning is implemented for head selection for efficientcommunication. Simulation results confirm the efficiency of the mechanism.

References

12 Cites in Article

Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Manpreet Kaur. 2014. \u201cStochastic Approach for Energy-Efficient Clustering in WSN\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 14 (GJCST Volume 14 Issue E7): .

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GJCST Volume 14 Issue E7
Pg. 1- 8

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

and CELEACH EBCH ELEACH wsn

Submission ReceivedDecember 6, 2013
Peer Review Double Blind
Handling Editor
Accepted January 5, 2014
Published January 15, 2014

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November 12, 2014

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Article Matrices

Total Score: 103

Country: India

Subject: Global Journal of Computer Science and Technology - E: Network, Web & Security

Authors: Manpreet Kaur, Lokesh Pawar, Rohit Bhullar (PhD/Dr. count: 0)

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