Sensor data aggregation in a multi-layer Big Data framework

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

13 Scopus citations

Abstract

Sensors play a vital role in the growth of big data as they are being used in numerous data-intensive applications. This paper introduces a multilayer big data aggregation framework and a priority-based, dynamic data aggregation (PDDA) scheme. The proposed PDDA approach works at the bottom layer at sensors (i.e., data collecting node) as opposed to most existing approaches which only consider aggregating data at the upper layer at the central server side. We evaluate the performance of the proposed PDDA approach and compare it against existing traditional tree and cluster-based schemes in terms of network lifetime and data latency. Simulation results demonstrate that the proposed PDDA approach outperforms the existing approaches.

Original languageEnglish
Title of host publication7th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEEE IEMCON 2016
EditorsHimadri Nath Saha, Satyajit Chakrabarti
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509009961
DOIs
StatePublished - 16 Nov 2016
Event7th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEEE IEMCON 2016 - Vancouver, Canada
Duration: 13 Oct 201615 Oct 2016

Publication series

Name7th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEEE IEMCON 2016

Conference

Conference7th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEEE IEMCON 2016
Country/TerritoryCanada
CityVancouver
Period13/10/1615/10/16

Keywords

  • Big Data
  • Clustering
  • Data aggregation
  • Sensor
  • Tree

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