EENC - Energy efficient nested clustering in UASN

Syed Hassan Ahmed, Abdul Wahid, Dongkyun Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Scopus citations

Abstract

Energy efficiency in Underwater Acoustic Sensor Network (UASN) is a key challenge for extending network lifetime. Base on analysis of energy consumption for LEACH in underwater channel, we propose a novel clustering scheme for UASN based on grouping nodes to ensure that nodes balance energy load by considering residual energy of candidate nodes. We introduce a formation of small clusters (groups) within clusters named as Nested Clustering (NC). Our Energy Efficient Nested Clustering (EENC) scheme divides each cluster into small groups and nodes in each of those small groups switch their operation modes (idle and awake) to achieve energy efficiency. Through simulation results, it is observed that our proposed EENC scheme has better network lifetime and optimized data duplication as compared to the existing clustering schemes.

Original languageEnglish
Title of host publicationProceedings of the 29th Annual ACM Symposium on Applied Computing, SAC 2014
PublisherAssociation for Computing Machinery
Pages706-710
Number of pages5
ISBN (Print)9781450324694
DOIs
StatePublished - 2014
Event29th Annual ACM Symposium on Applied Computing, SAC 2014 - Gyeongju, Korea, Republic of
Duration: 24 Mar 201428 Mar 2014

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Conference

Conference29th Annual ACM Symposium on Applied Computing, SAC 2014
Country/TerritoryKorea, Republic of
CityGyeongju
Period24/03/1428/03/14

Keywords

  • EENC
  • Energy Efficiency
  • LEACH (L)
  • Nested Clusters
  • UASN

Fingerprint

Dive into the research topics of 'EENC - Energy efficient nested clustering in UASN'. Together they form a unique fingerprint.

Cite this