On the Performance of Data Distribution Methods for Wireless Industrial Networks

The vast amounts of data generated in wireless industrial networked deployments introduce significant challenges on the data distribution process to consumer nodes within the timeframes imposed by the requirements of the Industry 4.0 paradigm. Using technological and methodological enablers, we can compose centralized or decentralized data distribution methods, which are able to help meeting the data requirements of the industrial applications. In this paper, 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. Although there have been several comparisons of relevant methods in the recent literature, 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. We implement the presented methods in OMNeT++ and we evaluate their performance via a detailed 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 increased data delivery success rate and low data access latency.

[1]  Song Han,et al.  WirelessHART and IEEE 802.15.4e , 2014, 2014 IEEE International Conference on Industrial Technology (ICIT).

[2]  Chen Zhang,et al.  MERPL: A more memory-efficient storing mode in RPL , 2013, 2013 19th IEEE International Conference on Networks (ICON).

[3]  Song Han,et al.  WirelessHART: Applying Wireless Technology in Real-Time Industrial Process Control , 2008, 2008 IEEE Real-Time and Embedded Technology and Applications Symposium.

[4]  Marco Conti,et al.  Performance Analysis of Latency-Aware Data Management in Industrial IoT Networks † , 2018, Sensors.

[5]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[6]  Nader Moayeri,et al.  A simulation framework for industrial wireless networks and process control systems , 2016, 2016 IEEE World Conference on Factory Communication Systems (WFCS).

[7]  Siarhei Kuryla,et al.  RPL: IPv6 Routing Protocol for Low power and Lossy Networks , 2010 .

[8]  Marcelo S. Alencar,et al.  Survey and systematic mapping of industrial Wireless Sensor Networks , 2017, J. Netw. Comput. Appl..

[9]  T. Lennvall,et al.  A comparison of WirelessHART and ZigBee for industrial applications , 2008, 2008 IEEE International Workshop on Factory Communication Systems.

[10]  Luiz Affonso Guedes,et al.  Routing and Scheduling Algorithms for WirelessHART Networks: A Survey , 2015, Sensors.

[11]  Huijun Gao,et al.  Data-Based Techniques Focused on Modern Industry: An Overview , 2015, IEEE Transactions on Industrial Electronics.

[12]  Marco Conti,et al.  Maximizing industrial IoT network lifetime under latency constraints through edge data distribution , 2018, 2018 IEEE Industrial Cyber-Physical Systems (ICPS).

[13]  Andrzej Duda,et al.  Performance comparison of the RPL and LOADng routing protocols in a Home Automation scenario , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[14]  Andreas Willig,et al.  Wireless HART TDMA Protocol Performance Evaluation Using Response Surface Methodology , 2011, 2011 International Conference on Broadband and Wireless Computing, Communication and Applications.

[15]  Marco Conti,et al.  Emerging Trends in Hybrid Wireless Communication and Data Management for the Industry 4.0 , 2018 .

[16]  Martin Heusse,et al.  Experimental Comparison of Routing Protocols for Wireless Sensors Networks: Routing Overhead and Asymmetric Links , 2017, ITC.

[17]  S. Carlsen,et al.  WirelessHART Versus ISA100.11a: The Format War Hits the Factory Floor , 2011, IEEE Industrial Electronics Magazine.