In the age of IoT, think “Data Centric”
There are two primary approaches to sharing data in the IoT: message-centric and data-centric. The message-centric approach (made popular by MQTT) has become the go to approach when architecting, designing and implementing IoT systems. We believe that there are systems for which a data-centric approach is much more suitable and should be considered.
Unlike a message-centric approach, in a data-centric approach each physical entity is represented as a data object that has:
- An identity
- A structure
- A state
- A lifecycle, and
- Metadata that characterises it and captures the above as well as provides content-awareness for database like filtering and querying.
Furthermore, there are some data-centric solutions that allow for attaching data qualities to the data. Examples of data qualities are:
- Urgency; and
We will look at the primary differences between a message-centric and data-centric approach to sharing data in an IoT system. As part of this the systems or scenarios were a data-centric approach should be considered are explained to show the benefits to using data-centricity. Finally, we conclude by looking at some open standards for a data-centric approach to data sharing. For example, the Data Distribution Service (DDS) from the Object Management Group (OMG) is one such standard.