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dc.contributor.authorAng, KLM
dc.contributor.authorSeng, JKP
dc.contributor.authorZungeru, AM
dc.date.accessioned2020-01-17T02:50:52Z
dc.date.available2020-01-17T02:50:52Z
dc.date.issued2018
dc.identifier.issn1932-8184
dc.identifier.doi10.1109/JSYST.2016.2630691
dc.identifier.urihttp://hdl.handle.net/10072/390579
dc.description.abstractBig sensor-based data environment and the emergence of large-scale wireless sensor networks (LS-WSNs), which are spread over wide geographic areas and contain thousands of sensor nodes, require new techniques for energy-efficient data collection. Recent approaches for data collection in WSNs have focused on techniques using mobile data collectors (MDCs) or sinks. Compared to traditional methods using static sinks, the MDC techniques give two advantages for data collection in LS-WSNs. These techniques can handle data collection over spatially separated geographical regions, and have been shown to require lower node energy consumption. Two common models for data collection using MDCs have been proposed: data collection using data mule (MULE), and sensor network with mobile access point (SENMA). The MULE and SENMA approaches can be characterized as representative of the multihop and the single-hop approaches for mobile data collection in WSNs. Although the basic architectures for MULE and SENMA have been well studied, the emergence of LS-WSNs which require partitioning the network into multiple groups and clusters prior to data collection has not been particularly addressed. This paper presents analytical approaches to determine the node energy consumption for LS-WSN MDC schemes and gives models for determining the optimal number of clusters for minimizing the energy consumption. The paper also addresses the tradeoffs when the LS-WSN MULE and SENMA models perform well.
dc.description.peerreviewedYes
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofpagefrom616
dc.relation.ispartofpageto626
dc.relation.ispartofissue1
dc.relation.ispartofjournalIEEE Systems Journal
dc.relation.ispartofvolume12
dc.subject.fieldofresearchElectrical and Electronic Engineering
dc.subject.fieldofresearchcode0906
dc.titleOptimizing Energy Consumption for Big Data Collection in Large-Scale Wireless Sensor Networks With Mobile Collectors
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationAng, KLM; Seng, JKP; Zungeru, AM, Optimizing Energy Consumption for Big Data Collection in Large-Scale Wireless Sensor Networks With Mobile Collectors, IEEE Systems Journal, 2018, 12 (1), pp. 616-626
dc.date.updated2020-01-17T02:49:25Z
gro.hasfulltextNo Full Text
gro.griffith.authorAng, Li-minn (Kenneth)


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