Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Mar 25;22(7):2533.
doi: 10.3390/s22072533.

Toward a Detailed Evaluation of Wireless Industrial Data Distribution Approaches

Theofanis P Raptis  1 , Andrea Formica  2 , Elena Pagani  2 , Andrea Passarella  1 , Marco Conti  1
Affiliations

Toward a Detailed Evaluation of Wireless Industrial Data Distribution Approaches

Theofanis P Raptis et al. Sensors (Basel). .

Abstract

Data distribution is a cornerstone of efficient automation for intelligent machines in Industry 4.0. Although in the recent literature there have been several comparisons of relevant methods, we identify that most of those comparisons are either theoretical or based on abstract simulation tools, unable to uncover the specific, detailed impacts of the methods to the underlying networking infrastructure. In this respect, as a first contribution of this paper, we develop more detailed and fine-tuned solutions for robust data distribution in smart factories on stationary and mobile scenarios of wireless industrial networking. Using the technological enablers of WirelessHART, RPL and the methodological enabler of proxy selection as building blocks, we compose the protocol stacks of four different methods (both centralized and decentralized) for data distribution in wireless industrial networks over the IEEE 802.15.4 physical layer. We implement the presented methods in the highly detailed OMNeT++ simulation environment and we evaluate their performance via an extensive simulation analysis. Interestingly enough, we demonstrate that the careful selection of a limited set of proxies for data caching in the network can lead to an increased data delivery success rate and low data access latency. Next, we describe two test cases demonstrated in an industrial smart factory environment. First, we show the collaboration between robotic elements and wireless data services. Second, we show the integration with an industrial fog node which controls the shop-floor devices. We report selected results in much larger scales, obtained via simulations.

Keywords: Industry 4.0; OMNeT++; RPL; WirelessHART; data distribution.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Square grid topology scheme.
Figure 2
Figure 2
Flowchart representing the adopted methodology.
Figure 3
Figure 3
Superframe slot numbers.
Figure 4
Figure 4
Performance for variable number of nodes. (a) Success rate; (b) Average latency; (c) Maximum latency; (d) Maximum average latency; (e) Number of proxies.
Figure 5
Figure 5
Traffic heatmaps. (a) C1 (RPL in non-storing mode); (b) D1 (RPL in storing mode); (c) D2 (proxy selection algorithm).
Figure 6
Figure 6
Performance for variable number of consumers. (a) Success rate; (b) average latency; (c) maximum latency; (d) maximum average latency.
Figure 7
Figure 7
First test case set-up. (a) Backbone network operational; (b) backbone network not operational.
Figure 8
Figure 8
Second test case set-up.
Figure 9
Figure 9
Scalability performance in simulations.
See this image and copyright information in PMC

References

    1. Raptis T.P., Passarella A., Conti M. Data Management in Industry 4.0: State of the Art and Open Challenges. IEEE Access. 2019;1:97052–97093. doi: 10.1109/ACCESS.2019.2929296. - DOI
    1. Yan J., Meng Y., Lu L., Li L. Industrial Big Data in an Industry 4.0 Environment: Challenges, Schemes, and Applications for Predictive Maintenance. IEEE Access. 2017;5:23484–23491. doi: 10.1109/ACCESS.2017.2765544. - DOI
    1. Raptis T.P., Passarella A., Conti M. Distributed Data Access in Industrial Edge Networks. IEEE J. Sel. Areas Commun. 2020;38:915–927. doi: 10.1109/JSAC.2020.2980917. - DOI
    1. Zhang L., Luo Y., Tao F., Li B.H., Ren L., Zhang X., Guo H., Cheng Y., Hu A., Liu Y. Cloud manufacturing: A new manufacturing paradigm. Enterp. Inf. Syst. 2014;8:167–187. doi: 10.1080/17517575.2012.683812. - DOI
    1. Chekired D.A., Khoukhi L., Mouftah H.T. Industrial IoT Data Scheduling Based on Hierarchical Fog Computing: A Key for Enabling Smart Factory. IEEE Trans. Ind. Inform. 2018;14:4590–4602. doi: 10.1109/TII.2018.2843802. - DOI