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The Industrial Internet of Things (IIoT) has revolutionized businesses by changing the way data are used to make products and services more efficient, reliable, and profitable. To achieve the improvement goals, the IIoT must guarantee the real-time performance of industrial applications such as motion control, by providing stringent quality of service (QoS) assurances for their (industrial applications) communication networks. An application or service may malfunction without adequate network QoS, resulting in potential product failures. Since an acceptable end-to-end delay and low jitter or packet delay variation (PDV) are closely related to quality of service (QoS), their impact is significant in ensuring the real-time performance of industrial applications. Although a communication network topology ensures certain jitter levels, its real-life performance is affected by dynamic traffic due to the changing number of devices, services, and applications present in the communication network. Hence, it is essential to study the jitter experienced by real-time traffic in the presence of background traffic and how it can be maintained within the limits to ensure a certain level of QoS. This paper presents a probabilistic network calculus approach that uses moment-generating functions to analyze the delay and PDV incurred by the traffic flows of interest in a wired packet switched multi-stage network. The presented work derives closed-form, end-to-end, probabilistic performance bounds for delay and PDV for several servers in series in the presence of background traffic. The PDV analysis conducted with the help of a Markovian traffic model for background traffic showed that the parameters from the background traffic significantly impact PDV and that PDV can be maintained under the limits by controlling the shape of the background traffic. For the studied configurations, the model parameters can change the PDV bound from 1 ms to 100 ms. The results indicated the possibility of using the model parameters as a shaper of the background traffic. Thus, the analysis can be beneficial in providing QoS assurances for real-time applications.

Synchronization is essential for correct and consistent operation of automation systems. Synchronized devices accurately time-stamp the events and enable timely communication of messages over a communication network. In absence of a common time base, critical functions of automation systems cannot be carried out in a safe fashion. Unsynchronized systems may lead to malfunctions such as false alarms, wrong decisions and erroneous outcomes resulting into serious showstopper for plant operations. Despite technical advances in synchronization, industrial automation systems have lagged compared to telecommunication and financial services in utilization of latest synchronization technology. Thus, there is a need to investigate the adoption of synchronization in industrial networks, its current state and implementation problems. We carried out an extensive literature search in a structured way to study the evolution of synchronization in automation systems. We also investigated today's industrial automation systems and their network topologies to get insight into the synchronization techniques and mechanisms being used. As an outcome of study, the paper highlights the challenges related to synchronization in existing automation networks that need to be addressed in the immediate and short-term future. 

Industrial control systems have strict requirements for time-sensitive applications and clock synchronization services. Performance of such applications is adversely impacted by packet delays and jitters. The impact is especially critical in process industries due to harsh environmental conditions. In this paper, we analyze delays and jitters to assess the performance of time-sensitive applications. To this end, we captured and analyzed round trip delay data retrieved from a paper factory. Analysis shows that a sub-millisecond level average delays and the jitters derived from the observed data are sufficient to meet the minimum 10ms update frequency required for most critical control applications. Moreover, the filtered delay variations at the end devices are less than the recommended 150us, which guarantees an adequate time synchronization accuracy in the factory network. Besides, this analysis can provide significant insights into performance bottlenecks for factory applications.

Recent advances in the industrial internet of things (IIoT) and cyber–physical systems drive Industry 4.0 and have led to remote monitoring and control applications that require factories to be connected to remote sites over wide area networks (WAN). The adequate performance of remote applications depends on the use of a clock synchronization scheme. Packet delay variations adversely impact the clock synchronization performance. This impact is significant in WAN as it comprises wired and wireless segments belonging to public and private networks, and such heterogeneity results in inconsistent delays. Highly accurate, hardware–based time synchronization solutions, global positioning system (GPS), and precision time protocol (PTP) are not preferred in WAN due to cost, environmental effects, hardware failure modes, and reliability issues. As a software–based network time protocol (NTP) overcomes these challenges but lacks accuracy, the authors propose a software–based clock synchronization method, called CoSiWiNeT, based on the random sample consensus (RANSAC) algorithm that uses an iterative technique to estimate a correct offset from observed noisy data. To evaluate the algorithm’s performance, measurements captured in a WAN deployed within two cities were used in the simulation. The results show that the performance of the new algorithm matches well with NTP and state–of–the–art methods in good network conditions; however, it outperforms them in degrading network scenarios.

Recent advances in industrial internet of things~(IIoT) and cyber-physical systems drive Industry 4.0 and lead to advanced applications. The adequate performance of time-critical automation applications depends on a clock synchronization scheme used by control systems. Network packet delay variations adversely impact the clock synchronization performance. The impact is significant in industrial sites, where software and hardware resources heavily contribute to delay variations, and where harsh environmental conditions interfere with communication network dynamics. While existing time synchronization methods for IIoT devices, e.g., Simple Network Time Protocol~(SNTP), provide adequate synchronization in good operating conditions, their performance degrades significantly with deteriorating network conditions. To overcome this issue, we propose a scalable, software-based, lightweight clock synchronization method, called CoSiNeT, for IIoT devices that maintains precise synchronization performance in a wide range of operating conditions. We have conducted measurements in local network deployments such as home and a university campus in order to evaluate the proposed algorithm performance. The results show that CoSiNeT matches well with SNTP and state-of-the-art method in good network conditions in terms of accuracy and precision; however, it outperforms them in degrading network scenarios. In our measurements, in fair network conditions, CoSiNeT improves synchronization performance by 23% and 25% compared to SNTP and state-of-the-art method. In the case of poor network conditions, it improves performance by 43% and 26%, respectively.

Time synchronization is essential for the correct and consistent operation of automation systems. An inaccurate analysis being a consequence of improper synchronization, can affect automation functions, e.g., by producing false commands and warnings. Industrial systems are evolving from the rigid automation pyramid to a flexible and reconfigurable architecture due to market evolution. The new trends in Cyber-Physical-Systems (CPS), Industry 4.0, and Internet of Things (IoT) are enabling this evolution. Citing a need to understand the future synchronization requirements, this paper envisions the architecture, communication network, and applications of future automation systems. Built on this vision, the paper derives the future needs of synchronization and analyzes them with state-of-art synchronization means. Based on the analysis, we envision the future of synchronization systems for automation systems.