doi.org

Minimum weighted clustering algorithm for wireless sensor networks | Proceedings of the 19th Panhellenic Conference on Informatics

Abstract

Extending network lifetime is a primary design objective for a wireless sensor network (WSN). Efficient clustering among sensor nodes seems a promising solution to evenly balance energy consumption and thus extend node and network lifetime. One of the most dominant clustering algorithms for energy efficient cluster formation is LEACH, because it balances node energy consumption. However, stochastic cluster head election of LEACH poses problems. In this paper, we propose a new clustering algorithm, named Minimum Weighted Clustering Algorithm (MWCLA) and compare its effectiveness with LEACH. MWCLA functions as follows: 1) Selects cluster heads based on cost criterion and quantifies the suitability of candidate cluster head by applying weights and 2) Rotates cluster head roles among nodes in a deterministic way, based on residual energy levels. In our simulations, we compare MWCLA with LEACH in terms of network lifetime and we highlight the cases where MWCLA is better in balancing node energy consumption, improving the efficiency in energy dissipation for communication and prolonging network lifetime. Our comparisons are based on three metrics: FND (First Node Dies), HND (Half Node Dies) and LND (Last Node Dies). MWCLA succeeds a network lifetime extension of 20% - 30% as compared to LEACH.

References

[1]

I. F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, "Wireless Sensor Network: A Survey", in Computer Networks, vol. 38, issue. 4, pp. 393--422, Mar. 2002

[2]

W. Heinzelman, A. Chandrakasan and H. Balakrishnan, "Energy - Efficient Communication Protocol for Wireless Microsensor Networks", in 33rd International Conference on System Sciences, Jan 2000

[3]

J. Chen, "Improvement of LEACH Routing Algorithm Based on Use of Balanced Energy in Wireless Sensor Networks", in Advanced Intelligent Computing Lecture Notes in Computer Science, vol. 6838, pp. 71--76, 2012

[4]

Q. Liao, H. Zhu, "An Energy Balanced Clustering Algorithm Based on LEACH Protocol", in 2nd International Conference on Systems Engineering and Modelling (ICSEM-13), Jan 2013

[5]

M. Handy, M. Haase, D. Timmermann, "Low Energy Adaptive Clustering Hierarchy with Deterministic Cluster-Head Selection", in 4th International Workshop on Mobile and Wireless Communications, pp.368--372, 2002

[6]

H. Abdulsalam and L. Kamel, "W-LEACH: Weighted Low Energy Adaptive Clustering Hierarchy Aggregation Algorithm for Data Streams in Wireless Sensor Networks (ICDMW)", in IEEE International Conference on Data Mining Workshops, pp. 1--8, Dec 2010

[7]

N. Tan, L. Han, H. Viet and M. Jo, "An Improved LEACH Routing Protocol for Energy-Efficiency of Wireless Sensor Networks", in Smart Computing Review, vol. 2, no. 5, Oct 2012

Information & Contributors

Information

Published In

cover image ACM Other conferences

PCI '15: Proceedings of the 19th Panhellenic Conference on Informatics

October 2015

438 pages

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 October 2015

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. balanced energy consumption
  2. clustering algorithm
  3. network lifetime
  4. wireless sensor networks

Qualifiers

  • Research-article

Conference

PCI '15

Acceptance Rates

PCI '15 Paper Acceptance Rate 64 of 148 submissions, 43%;

Overall Acceptance Rate 190 of 390 submissions, 49%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)0

Reflects downloads up to 11 Feb 2025

Other Metrics

Citations

  • Papastergiou GXenakis AChatzimisios PChaikalis K(2022)Sensor Placement for Lifetime Extension by Applying Neural Network Configuration under Coverage and Energy Constraints2022 Global Information Infrastructure and Networking Symposium (GIIS)10.1109/GIIS56506.2022.9936998(111-116)Online publication date: 26-Sep-2022

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in

Full Access

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media