BDPS: An Efficient Spark-Based Big Data Processing Scheme for Cloud Fog-IoT Orchestration
Open accessAbstract
The 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.
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- Authors
- Hossen, R., Whaiduzzaman, M., Uddin, M. N., Islam, M. J., Faruqui, N., Barros, A., Sookhak, M., & Mahi, M. J. N.
- Affiliations
- Jagannath University (BD)
- Queensland University of Technology (AU)
- Jahangirnagar University (BD)
- Texas A&M University (US)
- Corresponding author
- Whaiduzzaman, Md
- ORCID
- Venue
- Information
- Publisher
- MDPI AG
- Published
- 2021-12-10
- Volume
- 12
- Issue
- 12
- Pages
- 517
- ISSN
- 2078-2489 (ISSN-L)
- OpenAlex
- W4200184226
- Cited by
- 22
- References
- 48
- Citations by year
- 2025: 4 · 2024: 6 · 2023: 7 · 2022: 5
- FWCI
- 2.02
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Information (publishedVersion, cc-by)
- QUT ePrints (Queensland University of Technology) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Australian Research Council (DP190100314)
- ICT Division , Bangladesh (2016-17)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Keywords
- fog computing, Internet of Things, Apache Spark, Resilient Distributed Datasets, big data processing, shortest path algorithms, depth-first search, data delivery latency, heterogeneous network architecture, network overhead
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