Towards an efficient data analytics architecture for the Internet of Things

Saved in:
Bibliographic Details
Title: Towards an efficient data analytics architecture for the Internet of Things
Authors: Alturki, Badraddin
Summary: In the Internet of Things (IoT), the traditional architecture aims to process the data in the cloud. This creates several challenges such as high communication latency between the end devices and the cloud while making the network busy by sending all the raw data continuously. In this thesis, we propose an alternative architecture for the IoT which processes part of the data in the fog to avoid all raw data to be sent to the cloud. However, the cloud processes intensive data analytics. We conduct a trade-off analysis to show the advantages of applying data fusion closer to the data source and then processing the intensive data analytics algorithms in the cloud. We explore the effectiveness of the available architectures including centralised, decentralised, and distributed architecture to propose the most effective data analytics architecture for the IoT. The trade-off analysis shows the effectiveness of various service decomposition strategies leading to an understanding the various balances between Fog and IoT processing and their effectiveness in data communications reduction and result accuracy allowing achievements of 70% data communication reduction while still achieving approximately 90% accuracy. We propose a service distribution strategy called Most Efficient IoT Node (MEIN), which aims to distribute the services to either cloud nodes or fog nodes based on their capabilities while maintaining the usage of resource in IoT architecture. This strategy selects the best nodes and distributes the services on nodes based on the demands of services and capabilities of nodes.
URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.846676
Database: OpenDissertations
FullText Text:
  Availability: 0
Header DbId: ddu
DbLabel: OpenDissertations
An: ddu.oai.ethos.bl.uk.846676
AccessLevel: 6
PubType: Dissertation/ Thesis
PubTypeId: dissertation
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Towards an efficient data analytics architecture for the Internet of Things
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Alturki%2C+Badraddin%22">Alturki, Badraddin</searchLink>
– Name: Abstract
  Label: Summary
  Group: Ab
  Data: In the Internet of Things (IoT), the traditional architecture aims to process the data in the cloud. This creates several challenges such as high communication latency between the end devices and the cloud while making the network busy by sending all the raw data continuously. In this thesis, we propose an alternative architecture for the IoT which processes part of the data in the fog to avoid all raw data to be sent to the cloud. However, the cloud processes intensive data analytics. We conduct a trade-off analysis to show the advantages of applying data fusion closer to the data source and then processing the intensive data analytics algorithms in the cloud. We explore the effectiveness of the available architectures including centralised, decentralised, and distributed architecture to propose the most effective data analytics architecture for the IoT. The trade-off analysis shows the effectiveness of various service decomposition strategies leading to an understanding the various balances between Fog and IoT processing and their effectiveness in data communications reduction and result accuracy allowing achievements of 70% data communication reduction while still achieving approximately 90% accuracy. We propose a service distribution strategy called Most Efficient IoT Node (MEIN), which aims to distribute the services to either cloud nodes or fog nodes based on their capabilities while maintaining the usage of resource in IoT architecture. This strategy selects the best nodes and distributes the services on nodes based on the demands of services and capabilities of nodes.
– Name: URL
  Label: URL
  Group: URL
  Data: <link linkTarget="URL" linkTerm="https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.846676" linkWindow="_blank">https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.846676</link>
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ddu&AN=ddu.oai.ethos.bl.uk.846676
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Internet of Things (IoT) ; nodes ; data analytics ; IoT nodes ; data analytics architecture ; IoT architecture ; fog computing ; computing architecture ; fog nodes ; cloud nodes ; computing ; IoT ; data communication ; data processing ; computer science ; cloud computing
        Type: general
    Titles:
      – TitleFull: Towards an efficient data analytics architecture for the Internet of Things
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Alturki, Badraddin
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2021
ResultId 1