2013 3rd IEEE International Advance Computing Conference (IACC) 2013
DOI: 10.1109/iadcc.2013.6514208
|View full text |Cite
|
Sign up to set email alerts
|

Grouping of clusters for efficient data aggregation (GCEDA) in wireless sensor network

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
12
0

Year Published

2014
2014
2021
2021

Publication Types

Select...
7
1

Relationship

0
8

Authors

Journals

citations
Cited by 32 publications
(12 citation statements)
references
References 12 publications
0
12
0
Order By: Relevance
“…It degrades with imperfect data aggregation. Grouping of Clusters for Efficient Data Aggregation (GCEDA) [15] shows that, energy consumption improves by 14.94 %, if the number of clusters are grouped according to semantic conditions for the inter-cluster aggregations.…”
Section: Related Workmentioning
confidence: 99%
“…It degrades with imperfect data aggregation. Grouping of Clusters for Efficient Data Aggregation (GCEDA) [15] shows that, energy consumption improves by 14.94 %, if the number of clusters are grouped according to semantic conditions for the inter-cluster aggregations.…”
Section: Related Workmentioning
confidence: 99%
“…Reduced energy consumption in transmission [4] of aggregated data indicates profit of the increase in a lifetime of the network. EERDAT use that energy has been reduced effectively and reliability has been maintained as the size of the cluster is altered based upon the loss ratio [5].…”
Section: Related Workmentioning
confidence: 99%
“…Many WSNs data aggregation at the base station by individual nodes causes flooding of the data which consequences in maximum energy consumption. [4] 3. Also most of data aggregation methods are either based upon the clustering or treebased approach but the use of hybrid data aggregation has been ignored by the most of the researchers.…”
Section: Research Gaps and Research Motivationmentioning
confidence: 99%
“…Mantri et al 16 proposed a group-based data aggregation method. In this method, node grouping is based on available data and correlation in the intra-cluster.…”
Section: Related Workmentioning
confidence: 99%