In a smart factory enabled by Industry 4.0 and IIoT, data collection on assets and operations and real-time analytics allow enterprises to attain unprecedented levels of efficiency and productivity. The proliferation of devices and systems converging within the same network, however, requires prioritizing communication streams to ensure proper and efficient data flow. That’s what IoT communication protocols are for.
IoT communication protocols serve as the foundation for IoT device-to-device and device-to-cloud communication by establishing a common framework for seamless interaction. A robust communication protocol can simplify IoT management from the ground up, encompassing edge-stage operations and device and fleet management, as is the case with MQTT (Message Queuing Telemetry Transport). By smoothly merging IIoT and MQTT for bidirectional data flow in manufacturing operations, manufacturers can make a significant change to their processes, strengthen their market position, and strive for unprecedented levels of efficiency and productivity.
MQTT: Efficiency and Reliability for IIoT Data Exchange
MQTT is a lightweight, bi-directional messaging protocol optimized for efficiency, speed, and reliability. It is particularly suitable for use under constrained conditions – including unreliable network connections, restricted bandwidth, or limited battery power – since its design minimizes protocol overhead and optimizes bandwidth usage. The lightweightness and efficiency of MQTT make it well-suited for remote monitoring, especially in M2M connections, since it possible to significantly increase the amount of data being monitored or controlled.
MQTT follows the publish-subscribe paradigm: connected devices, referred to as clients, can either publish or subscribe to topics, enabling efficient data exchange without direct client-to-client communication. It is the MQTT broker who receives and forwards messages, acting as a central hub and managing communication flow. As an event-driven protocol, clients only publish when necessary and brokers only send out to subscribers when new data arrives, minimizing network traffic and resource consumption. The decoupling of publishers and subscribers, together with the ability to retain session information in cases of temporary disconnects, ensures the flow of communication even under unreliable network connections.
Despite its lightweight nature, MQTT also provides a mechanism for ensuring message delivery. Clients can configure different Quality of Service (QoS) levels to meet various message delivery requirements, adjusting to network reliability and application needs. Because of this, it also finds application in complex scenarios where real-time communication and data integrity are paramount.
These features make the MQTT a particularly suitable protocol for IIoT infrastructures. Allowing to effortlessly shuttle data to and from a multitude of distributed factory machines, systems, and applications across the enterprise, MQTT enables real-time monitoring, analytics, and control. Additionally, MQTT is scalable: whether a deployment involves a few sensors or thousands of devices, MQTT can handle the scaling requirements without compromising performance. QoS configurable levels are also particularly suitable for IIoT use cases, requiring low-latency communication and data integrity for real-time monitoring and control. The choice of QoS level might depend on the specific reliability and real-time constraints of applications. For example, monitoring and reporting non-critical sensor data may use QoS 0 – not providing any mechanism to ensure successful message delivery – while mission-critical applications may rely on QoS 2, guaranteeing that a message is delivered exactly once, to ensure precise and reliable control.
Fortifying IIoT infrastructures with MQTT Security
As IIoT applications grow in size and complexity, MQTT protocol’s native security features contribute to making it an ideal method to move data through the layers of any IIoT implementation, safeguarding systems from potential threats and attacks.
When it comes to MQTT security, three concepts are fundamental: authentication, encryption, and authorization.
- Client Authentication: MQTT employs client authentication to ensure that only authorized clients can establish connections with the broker. Password authentication is the most common method, where an MQTT client provides a username and password during the connection process. The broker checks these credentials against stored data, denying access if there’s no match.
- Data Encryption: MQTT can be configured to use Transport Layer Security (TLS) or Secure Sockets Layer (SSL) to encrypt data in transit. TLS/SSL ensures that data in transit is protected from eavesdropping and tampering.
- Authorization Controls: MQTT brokers offer granular access control through Access Control Lists (ACLs) and custom authorization rules. These mechanisms determine which authenticated clients can publish or subscribe to specific topics, ensuring that data is shared only with authorized parties.
To ensure the highest level of security, it is important that MQTT brokers and clients are also configured correctly. This includes securing administrative interfaces and keeping the broker software and firmware on IoT devices up to date with security patches and updates to address known vulnerabilities. Comprehensive security measures should also extend across the entire IoT system, for example implementing firewalls and network segmentation to minimize potential attack points. This end-to-end approach guarantees that data remains protected throughout its journey, from the device at the edge to the cloud-based applications processing it.
Modernizing the Manufacturing Industry with MQTT
Originally designed for industrial use in the oil and gas industry, MQTT now finds application in a wide array of commercial and industrial use cases. Whenever network stability is uncertain, the need to conserve bandwidth is essential, low-powered hardware is in use, or a network architecture involves several client devices requiring access to the same data in nearly real-time, MQTT steps in.
Due to the many benefits it has over competing network protocols, it has quickly emerged as the protocol of choice in manufacturing. MQTT eases access to data and combines with ML and AI applications, allowing companies to extract new value from data from their plants and processes to achieve their business goals. Here are some of the key considerations related to MQTT that are critical to fulfilling an enterprise IIoT strategy.
- Interoperabiliy – MQTT’s open standard nature means it can work with various software and hardware solutions, connecting devices and systems from different manufacturers and technologies. Most importantly, MQTT is agnostic to data types and can handle a wide range of data – including machine and process data, maintenance records and other information – each encoded in its own language and coming in at different rates. This promotes interoperability in complex industrial setups, fostering seamless communication between multiple manufacturing assets and applications and providing an enterprise-wide solution architecture.
- Scaling the flow of manufacturing data – MQTT’s publish-subscribe model seamless scale as the number of IIoT devices and data sources grows, with mechanisms for handling large volumes of data and ensuring reliable message delivery. This ensures on the one hand the protocol’s operability as the IoT infrastructure grows; on the other hand, it enables advanced downtime measurement algorithms that need high volumes of data to accurately track and reduce machinery downtime.
- Real-time data analysis – To ensure the effectiveness of infrastructure monitoring, data must be collected and analyzed in real-time. Without real-time inputs, the tracking algorithm’s output might be influenced by outdated data, potentially leading to incorrect decisions. MQTT architecture allows for unlimited clients over a publish/subscribe protocol, which means that the data published from a manufacturing asset can be consumed by multiple applications all at the same time. Such timely information sharing is critical to feed data into real-time analytics and decision support systems, which are the pillars of predictive maintenance of production machinery, quality control, and process optimization.
- Tele-maintenance and remote control of machinery – MQTT’s data aggregation capabilities enable gathering data from diverse sources and funneling it to central systems for enrichment and analysis. As a bi-directional protocol, data can also take the reverse path. This allows to remotely control machinery by transmitting control commands from a central control center to machines in the field. Plant operators can use MQTT to publish control commands to specific machine topics, triggering actions or adjustments. These commands may include starting or stopping equipment, adjusting operating parameters, or implementing safety protocols. MQTT brokers’ ability to retain historical data also facilitates trend analysis, compliance reporting, and forensic examination, aligning with the needs of industries requiring long-term data insights.
- Secure factory data transfer – The primary concern for most manufacturers considering the adoption of edge or cloud-based IoT stack is about security and privacy risks. MQTT supports robust security mechanisms, including TLS/SSL encryption and authentication, to protect data in transit and prevent unauthorized access. These security features are vital for safeguarding sensitive information in enterprise IIoT deployments.
Get started with advanced infrastructure management with Clea
The MQTT protocol is gaining in popularity for factory-to-cloud communications due to its lightweight nature and extensive features related to scalability, reliability, and security. IIoT and MQTT-enabled factory management helps in reducing unplanned downtime and advancing the company’s manufacturing capabilities and efficiencies.
SECO’s Clea software suite provides a solid solution for modernizing manufacturing infrastructure with a comprehensive set of tools including the MQTT protocol. Clea’s modular software stack acts as the digital counterpart of edge devices spread across the industrial facility, offering standard, ready-to-use platforms and infrastructures to handle tasks from field data analysis and optimization to fleet and device management. Clea employs MQTT as a core component for device-to-device and device-to-cloud communication. This ensures that field data is appropriately ingested into cloud databases, analytics platforms, or other cloud-based applications for real-time processing and decision-making.
Astarte, the data orchestration module included in the Clea software stack, uses MQTT protocol to communicate with field device and connect them with the cloud. This implementation relies on a broker providing an MQTT protocol built upon the MQTT v3.1.1 specification, BSON (Binary JSON, version 1.1) serialized payloads and on optional zlib deflate. The broker is responsible for receiving, processing, and routing MQTT messages between IoT devices and the cloud service. Leveraging MQTT technology, Astarte can connect to an endless number of devices for transmitting and receiving data directly from the network edge and moving it to the cloud for further analysis. Beyond MQTT capabilities, Astarte is the tool to unleash the potential of IoT data through extensive data orchestration, automated actions, streamlined data processing via pipelines, and seamless integration with third-party systems via comprehensive APIs.
In addition to Astarte, Clea modular, open-source and production-ready software stack includes Edgehog Device Manager and Portal front end framework. Seamlessly working together, these ready-to-use platforms handle tasks from field data analysis and optimization to fleet and device management and multi-tenancy visualization, but they are also available as standalone solutions, according to the customer’s needs and use case.
Bringing intelligence closer to the data source, Clea empowers companies to achieve advanced management of facilities and industrial machinery. New value extracted from production data results in maximized process efficiency and reduced time-to-market. Contact our team of experts today to discover how to get the most out of your IoT infrastructure with the help of your data and Clea.