IIC Journal of Innovation 5th Edition | Page 80

A Practical Guide to Using the Industrial Internet Connectivity Framework syntactic interoperability. We examine it nonetheless because it has wide awareness. sources, sinks and networks. The databus can control Quality of Service (QoS) like update rate, reliability and guaranteed notification of data liveliness. It can look at the data inside the updates and optimize how to send them, or decide not to send them at all. It also can discover and secure data flows dynamically. All of these things define interaction between software modules. The data-centric paradigm thus enables software integration. DDS Here are five questions to answer to decide if you need DDS: 1. Is it a big problem if your system goes down for a short time? 2. Are milliseconds important in your communications? 3. Do you have more than 10 software engineers? 4. Are you sending data to many places, as opposed to just one (like to the cloud or a database)? 5. Are you implementing a new IIoT architecture? So how does this satisfy the five questions? 1. Since it is directly controlling flow, a databus does not require servers. So, there’s no single point of failure. The downtime required to reboot a server and remake connections unexpectedly is never necessary. Without direct relationships with peers, redundancy is transparent. If the application is managing a thermostat, optimizing a plant, or assembling parts, a short downtime is not catastrophic. However, if the software is responsible for someone’s breathing or the stability of the power grid, even short interruptions cannot be tolerated. 2. Since the databus has full control over how data flows, it can send information directly between peers. Thus, it can deliver in times measured in milliseconds or microseconds. DDS can use multicast intelligently when available. It knows delivery deadline requirements and can measure if the system is meeting delivery times. So, it can warn applications if the network (or anything else) cannot handle the needed flow rates. If you answered three out of the five questions “yes,” you probably should use DDS. DDS is a series of standards managed by the OMG that define a databus. A databus is data-centric information flow control. It’s a similar concept to a database, which is data- centric information storage. The key difference: a database searches old information by relating properties of stored data. A databus finds future information by filtering properties of the incoming data. Both understand the data contents and let applications act directly on and through the data rather than with each other. Applications using a database or a databus do not have a direct relationship with peer applications. The databus uses knowledge of the structure, contents and demands on data to manage dataflow. It can, for instance, resolve redundancy to support multiple - 78 - September 2017