The Industrial IoT introduces new requirements for the velocity, variety, and volume of information exchange. Connectivity must be real-time and secure, and it must work over mobile, disconnected, and intermittent links. It must efficiently scale to handle any number of things, each of which may have its own unique requirements for information exchange, such as streaming updates, state replication, alarms, configuration settings, initialization, and commanded intents. These requirements are above and beyond the requirements commonly handled by conventional connectivity solutions designed for static networks.

Designers and standards organizations are fueling the advancement of appropriate connectivity standards like the Data Distribution Service (DDS) that meet these requirements and facilitate a more open, interoperable connectivity architecture for intelligent devices. The benefits include shorter development times, flexible design options, and scalable designs that can evolve with the IoT.

Reduced Integration Times

One of the primary roles of the connectivity architecture is to ensure interoperability of the IoT and thereby reduce integration time for complex devices and subsystems. Ultimately, the goal is to evolve the connectivity architecture to achieve full plug-and-play compatibility.

Currently, industry standards for real-time connectivity are focused on mid-level interoperability, or syntactic-level compatibility, where all endpoints and systems use a common data format and syntax.

Flexible Connectivity Gateways

A connectivity standard that delivers syntactic-level interoperability facilitates the introduction of connectivity gateways to address the diversity of devices in modern systems. These gateways serve multiple purposes, including the support of external systems and devices that rely on other connectivity technologies. Gateways can also be used to create hierarchical architectures and to group various endpoints and devices into subsystems.

Decoupled Apps and Data

Unlike human-driven environments, industrial systems operate autonomously and therefore call for a data- driven architecture. This shift can be compared to the historical development of databases. By decoupling data from applications, databases gave application developers much greater flexibility for evolving modular, independent applications, and they fostered innovation and standards in the application programming interface (API).

Within the Industrial IoT, data-centric communications can similarly promote interoperability, scalability, and ease of integration. The concept of a data bus allows the possibility of decoupling data from application logic so application components interact with data and not directly with each other. The data bus can independently optimize the delivery of data in motion, and can also be more effectively managed and scaled separately from the application components.

Fundamental Building Blocks

In conventional enterprise IT environments, the data architecture deals with events, transactions, queries, and jobs. The Industrial IoT, which is made up of a broad range of devices, differs greatly from this human-driven environment. The fundamental building blocks of the Industrial IoT include streams of data, commands, status (or state) information, and configuration changes.

Note that the key activity triggers within conventional environments involve human requests or responses (decisions). In the Industrial IoT, activity is triggered by data or state changes that exist and happen autonomously.