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Context aware traffic scheduling algorithm for power distribution smart grid network

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dc.citedby8
dc.contributor.authorRadzi N.A.M.en_US
dc.contributor.authorSuhaimy N.en_US
dc.contributor.authorAhmad W.S.H.M.W.en_US
dc.contributor.authorIsmail A.en_US
dc.contributor.authorAbdullah F.en_US
dc.contributor.authorJamaludin M.Z.en_US
dc.contributor.authorZakaria M.N.en_US
dc.contributor.authorid57218936786en_US
dc.contributor.authorid57218501518en_US
dc.contributor.authorid25928314500en_US
dc.contributor.authorid36023817800en_US
dc.contributor.authorid56613644500en_US
dc.contributor.authorid57216839721en_US
dc.contributor.authorid57213826693en_US
dc.date.accessioned2023-05-29T07:27:44Z
dc.date.available2023-05-29T07:27:44Z
dc.date.issued2019
dc.descriptionElectric network analysis; Electric power transmission networks; Packet switching; Quality of service; Context- awareness; Heterogeneous traffic; Power distribution network; Power distributions; Smart grid networks; Suboptimal solution; Technical challenges; Traffic scheduling; Smart power gridsen_US
dc.description.abstractT The emergence of smart grid poses technical challenges to the power distribution network because of the increasing data traffic resulting from diverse data applications. Traffic scheduling algorithms manage these heterogeneous applications by applying different priorities to each traffic type based on its quality of service (QoS). However, QoS alone cannot accurately capture complex situations wherein packets with low priority occasionally need to be served first based on their context, resulting in a suboptimal solution. This paper proposes a context aware traffic scheduling (CATSchA) algorithm to schedule the traffic such that it could adapt to varying power network conditions. The power distribution network traffic is characterized based on heterogeneous traffic demands, and then mapped into weighted quality classes. The CATSchA algorithm is implemented in a packet switched network using NS-3 simulator, and the traffic demand is fulfilled based on the algorithm's context awareness. Compared with traditional traffic scheduling algorithms, the proposed algorithm lowers the delay while maintaining the throughput and link efficiency. � 2020 BioMed Central Ltd.. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo8779637
dc.identifier.doi10.1109/ACCESS.2019.2931722
dc.identifier.epage104084
dc.identifier.scopus2-s2.0-85089340795
dc.identifier.spage104072
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85089340795&doi=10.1109%2fACCESS.2019.2931722&partnerID=40&md5=0168666eb469d3f839d85f8f8388df2d
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24835
dc.identifier.volume7
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleIEEE Access
dc.titleContext aware traffic scheduling algorithm for power distribution smart grid networken_US
dc.typeArticleen_US
dspace.entity.typePublication
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