BDPS: An efficient spark-based big data processing scheme for cloud Fog-IoT orchestration

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dc.contributor.authorHossen, Rakib
dc.contributor.authorWhaiduzzaman, Md
dc.contributor.authorUddin, Mohammed Nasir
dc.contributor.authorIslam, Md. Jahidul
dc.contributor.authorFaruqui, Nuruzzaman
dc.contributor.authorBarros, Alistair
dc.contributor.authorSookhak, Mehdi
dc.contributor.authorMahi, Md. Julkar Nayeen
dc.creator.orcidhttps://orcid.org/0000-0003-2822-0657en_US
dc.creator.orcidhttps://orcid.org/0000-0003-1289-6484en_US
dc.creator.orcidhttps://orcid.org/0000-0001-9306-9637en_US
dc.creator.orcidhttps://orcid.org/0000-0001-8980-6841en_US
dc.creator.orcidhttps://orcid.org/0000-0001-5822-3432en_US
dc.creator.orcidhttps://orcid.org/0000-0002-1763-2544en_US
dc.creator.orcidhttps://orcid.org/0000-0003-2822-0657
dc.creator.orcidhttps://orcid.org/0000-0003-1289-6484
dc.creator.orcidhttps://orcid.org/0000-0001-9306-9637
dc.creator.orcidhttps://orcid.org/0000-0001-8980-6841
dc.creator.orcidhttps://orcid.org/0000-0001-5822-3432
dc.creator.orcidhttps://orcid.org/0000-0002-1763-2544
dc.date.accessioned2022-04-06T20:35:21Z
dc.date.available2022-04-06T20:35:21Z
dc.date.issued2021-12-10
dc.description.abstractThe Internet of Things (IoT) has seen a surge in mobile devices with the market and technical expansion. IoT networks provide end-to-end connectivity while keeping minimal latency. To reduce delays, efficient data delivery schemes are required for dispersed fog-IoT network orchestrations. We use a Spark-based big data processing scheme (BDPS) to accelerate the distributed database (RDD) delay efficient technique in the fogs for a decentralized heterogeneous network architecture to reinforce suitable data allocations via IoTs. We propose BDPS based on Spark-RDD in fog-IoT overlay architecture to address the performance issues across the network orchestration. We evaluate data processing delays from fog-IoT integrated parts using a depth-first-search-based shortest path node finding configuration, which outperforms the existing shortest path algorithms in terms of algorithmic (i.e., depth-first search) efficiency, including the Bellman–Ford (BF) algorithm, Floyd–Warshall (FW) algorithm, Dijkstra algorithm (DA), and Apache Hadoop (AH) algorithm. The BDPS exhibits low latency in packet deliveries as well as low network overhead uplink activity through a map-reduced resilient data distribution mechanism, better than in BF, DA, FW, and AH. The overall BDPS scheme supports efficient data delivery across the fog-IoT orchestration, outperforming faster node execution while proving effective results, compared to DA, BF, FW and AH, respectively.en_US
dc.description.sponsorshipThis research is funded through the “ICT Innovation Fund (2016-17): ICT Division, Bangladesh” and also partially supported through the Australian Research Council Discovery Project: DP190100314.en_US
dc.identifier.citationHossen, R., Whaiduzzaman, M., Uddin, M.N., Islam, M., Faruqui, N., Barros, A., Sookhak, M., Mahi, M. and Nayeen, J., 2021. BDPS: An Efficient Spark-Based Big Data Processing Scheme for Cloud Fog-IoT Orchestration. Information, 12(12), p.517.en_US
dc.identifier.doihttps://doi.org/10.3390/info12120517
dc.identifier.urihttps://hdl.handle.net/1969.6/90406
dc.language.isoen_USen_US
dc.publisherMDPIen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectefficient data processingen_US
dc.subjectdepth-first searchen_US
dc.subjectmap reductionen_US
dc.subjectin-memory acceleratoren_US
dc.subjectsparken_US
dc.titleBDPS: An efficient spark-based big data processing scheme for cloud Fog-IoT orchestrationen_US
dc.typeArticleen_US

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