A Polling-Based Transmission Scheme Using a Network Traffic Uniformity Metric for Industrial IoT Applications

The Industrial Internet of Things (IIoT) applications are required to provide precise measurement functions as feedback for controlling devices. The applications traditionally use polling-based communication protocols. However, in polling-based communication over current industrial wireless network protocols such as ISA100.11a, WirelessHART have difficulty in realizing both scheduled periodic data collection at high success ratio and unpredictable on-demand communications with short latency. In this paper, a polling-based transmission scheme using a network traffic uniformity metric is proposed for IIoT applications. In the proposed scheme, a center node controls the transmission timing of all polling-based communication in accordance with a schedule that is determined by a Genetic Algorithm. Communication of both periodic and unpredictable on-demand data collection are uniformly assigned to solve the above difficulties in the schedule. Simulation results show that network traffic is generated uniformly and a center node can collect periodic data from nodes at high success ratio. The average success probability of periodical data collection is 97.4% and the lowest probability is 95.2%.

[1]  Marimuthu Palaniswami,et al.  Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..

[2]  Cees T. A. M. de Laat,et al.  Developing, Provisioning and Controlling Time Critical Applications in Cloud , 2017, ESOCC Workshops.

[3]  MengChu Zhou,et al.  Toward opportunistic services for the industrial Internet of Things , 2017, 2017 13th IEEE Conference on Automation Science and Engineering (CASE).

[5]  Xiang-Yang Li,et al.  Efficient interference-aware TDMA link scheduling for static wireless networks , 2006, MobiCom '06.

[6]  Dorothea Heiss-Czedik,et al.  An Introduction to Genetic Algorithms. , 1997, Artificial Life.

[7]  Giancarlo Fortino,et al.  Empowering smart cities through interoperable Sensor Network Enablers , 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[8]  Salvatore Cavalieri,et al.  Multicycle Polling Scheduling Algorithms for FieldBus Networks , 2004, Real-Time Systems.

[9]  Thomas Clausen,et al.  Evaluation of routing protocol for low power and Lossy Networks: LOADng and RPL , 2013, 2013 IEEE Conference on Wireless Sensor (ICWISE).

[10]  Guevara Noubir,et al.  Static and dynamic polling mechanisms for fieldbus networks , 1993, OPSR.

[11]  Andrei Gurtov,et al.  Analyzing Internet-connected industrial equipment , 2018, 2018 International Conference on Signals and Systems (ICSigSys).

[12]  Naoki Wakamiya,et al.  Priority-Based Dynamic Multichannel Transmission Scheme for Industrial Wireless Networks , 2017, Wirel. Commun. Mob. Comput..

[13]  Catherine Mulligan,et al.  From Machine-to-Machine to the Internet of Things - Introduction to a New Age of Intelligence , 2014 .

[14]  Dmitry Korzun,et al.  Secure Communication and Data Processing Challenges in the Industrial Internet , 2016, Balt. J. Mod. Comput..

[15]  Felix Wortmann,et al.  Internet of Things , 2015, Business & Information Systems Engineering.

[16]  Jian Wang,et al.  Genetic Algorithm for Optimizing Routing Design and Fleet Allocation of Freeway Service Overlapping Patrol , 2018 .

[17]  Yixin Chen,et al.  Real-Time Scheduling for WirelessHART Networks , 2010, 2010 31st IEEE Real-Time Systems Symposium.

[18]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[19]  Ingrid Moerman,et al.  A Survey of LoRaWAN for IoT: From Technology to Application , 2018, Sensors.

[20]  Chenyang Lu,et al.  Real-Time Query Scheduling for Wireless Sensor Networks , 2007, IEEE Transactions on Computers.

[21]  Aditya Bagri,et al.  Supervisory Control and Data Acquisition , 2014 .

[22]  Hongwei Ding,et al.  A Priority-based Parallel Schedule Polling MAC for Wireless Sensor Networks , 2016, J. Commun..