A Fog-Based Architecture for Latency-Sensitive Monitoring Applications in Industrial Internet of Things

In industrial wireless sensors networks (IWSNs) deployments, data management and processing tasks are often delegated to centralized computing facilities. Albeit providing an abundance of resources, these solutions impose several drawbacks, stemming from the higher latency they may introduce, as wel...

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Bibliographic Details
Published in:IEEE internet of things journal 2023-02, Vol.10 (3), p.1908-1918
Main Authors: Benomar, Zakaria, Campobello, Giuseppe, Segreto, Antonino, Battaglia, Filippo, Longo, Francesco, Merlino, Giovanni, Puliafito, Antonio
Format: Article
Language:English
Subjects:
Algorithms
Block ciphering
Cloud computing
Computer architecture
Cybersecurity
Data management
Encryption
Energy consumption
fog computing
Industrial applications
Industrial Internet of Things (IIoT)
industrial wireless sensors network (IWSN)
Internet of Things
Internet of Things (IoT)
Monitoring
Network latency
Protocols
Sensors
Singular value decomposition
Temperature measurement
Wireless sensor networks
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Summary:In industrial wireless sensors networks (IWSNs) deployments, data management and processing tasks are often delegated to centralized computing facilities. Albeit providing an abundance of resources, these solutions impose several drawbacks, stemming from the higher latency they may introduce, as well as from security/privacy issues. To deal with these shortcomings, in this article, we propose an architecture designed for industrial monitoring duties, based on the Fog computing paradigm. In particular, we devised a Fog layer to host a data aggregation algorithm based on singular value decomposition (SVD). Considering a real-world case study about a distributed monitoring system for industrial motors, the benefits of the proposed solution in terms of network performances, i.e., latency and packet delivery ratio, are analyzed using the OMNET++ simulator. Besides, the system implements a set of security mechanisms at different levels (i.e., IWSN, Fog, and Cloud). In particular, we propose a new lightweight and energy-efficient ciphering algorithm for resource-constrained industrial motes. According to our experiments, the new algorithm reduces energy consumption by a factor of three compared to Advanced Encryption Standard-128.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2021.3138691