Section: New Results

Industry 4.0 and Low-Power Wireless Meshed Networks

Deterministic Networking for the Industrial Internet of Things (IIoT)

Participants : Keoma Brun-Laguna, Thomas Watteyne, Pascale Minet.

The Internet of Things (IoT) connects tiny electronic devices able to measure a physical value (temperature, humidity, etc.) and/or to actuate on the physical world (pump, valve, etc). Due to their cost and ease of deployment, battery-powered wireless IoT networks are rapidly being adopted.

The promise of wireless communication is to offer wire-like connectivity. Major improvements have been made in that sense, but many challenges remain as industrial application have strong operational requirements. This section of the IoT application is called Industrial IoT (IIoT).

The main IIoT requirement is reliability. Every bit of information that is transmitted in the network must not be lost. Current off-the-shelf solutions offer over 99.999% reliability.

Then come latency and energy-efficiency requirements. As devices are battery-powered, they need to consume as little as possible to be able to operate during years. The next step for the IoT is to target time-critical applications.

Industrial IoT technologies are now adopted by companies over the world, and are now a proven solution. Yet, challenges remain and some of the limits of the technologies are still not fully understood. In his PhD Thesis, Keoma Brun-Laguna addresses TSCH-based Wireless Sensor Networks and studies their latency and lifetime limits under real-world conditions.

We gathered 3M network statistics 32M sensor measurements on 11 datasets with a total of 170,037 mote hours in real-world and testbeds deployments. We assembled what we believed to be the largest dataset available to the networking community.

Based on those datasets and on insights we learned from deploying networks in real-world conditions, we study the limits and trade-offs of TSCH-based Wireless Sensor Networks. We provide methods and tools to estimate the network performances of such networks in various scenarios. We highlight the trade-off between short latency and long network lifetime. We believe we assembled the right tools for protocol designer to build deterministic networking to the Industrial IoT.

Industry 4.0 and IEEE 802.15.4e TSCH networks

Participants : Pascale Minet, Ines Khoufi, Zied Soua.

By the year 2020, it is expected that the number of connected objects will exceed several billions devices. These objects will be present in everyday life for a smarter home and city as well as in future smart factories that will revolutionize the industry organization. This is actually the expected fourth industrial revolution, more known as Industry 4.0. In which, the Internet of Things (IoT) is considered as a key enabler for this major transformation. IoT will allow more intelligent monitoring and self-organizing capabilities than traditional factories. As a consequence, the production process will be more efficient and flexible with products of higher quality.

To produce better quality products and improve monitoring in Industry 4.0, strong requirements in terms of latency, robustness and power autonomy have to be met by the networks supporting the Industry 4.0 applications. The wireless TSCH (Time Slotted Channel Hopping) network specified in the e amendment of the IEEE 802.15.4 standard has many appealing properties. Its schedule of multichannel slotted data transmissions ensures the absence of collisions. Because there is no retransmission due to collisions, communication is faster. Since the devices save energy each time they do not take part in a transmission, the power autonomy of nodes is prolonged. Furthermore, channel hopping enables to mitigate multipath fading and interferences.

To increase the flexibility and the self-organizing capacities required by Industry 4.0, the networks have to be able to adapt to changes. These changes may concern the application itself, the network topology by adding or removing devices, the traffic generated by increasing or decreasing the device sampling frequency, for instance. That is why the flexibility of the schedule ruling all network communications is needed.

In 2018, we show how a TSCH network can adapt to such changes. More precisely, we propose a solution ranging from network construction to data gathering. We show how a TSCH network is autonomously built, supports data gathering and is able to adapt to changes in network topology, traffic and application requirements.

The solution proposed preserves the merits of TSCH network, that can be listed hereafter. The time-slotted multichannel medium access enables parallel transmissions on several channels, leading to shorter latency and higher throughputs. In addition, channel hopping mitigates interference and multipath effects. Furthermore, since transmissions are scheduled, a conflict-free schedule is computed by the network coordinator (i.e. the CPAN). Hence, no collision occurs during data gathering. The absence of collision leads to a higher throughput, because there is no retransmission due to collisions. It also preserves nodes power autonomy.

This simple solution is based on the coexistence of several periodic slotframes. We distinguish three slotframes, which are the Beacon Slotframe, the Data Slotframe and the Shared Slotframe. The network schedule corresponds to the superposition of the three schedules given by each slotframe, where the slotframe with the highest priority wins.

This solution ensures a collision-free dissemination over the whole network. Beacons are broadcast in sequence by increasing depth of devices. This broadcast is also used to disseminate Data Schedules (new schedule or update).

In addition, this solution is adaptive. Topology, traffic or application changes are notified to the CPAN. Depending on the changes notified, the CPAN updates the current schedule or recomputes a new one. Shared slots are used to cope with unexpected events.

We compute the theoretical bounds with regard to key performance indicators and compare them with the values obtained by NS3 simulation. Simulation results confirm the theoretical upper bounds computed for network construction and data gathering. Hence, TSCH networks are able to adapt to traffic or topology changes in a reasonable time which is a strong requirement of Industry 4.0 applications. These results have been presented at the PEMWN 2018 conference in [26]. In some further work, we will study how to improve this delay to support the most demanding applications.