For this final blog in our series on the unique requirements of real-time systems for the cloud, let’s step back a bit and look at the whole picture. In any industrial or embedded cloud application, there are essentially three parts:
- The data sources, such machines, industrial processes, or perhaps remote terminal units (RTUs) or sensors used for data acquisition.
- The cloud system.
- The data consumers, which might be web pages, databases for generating reports, spreadsheets for running analytics, or even other machines or processes.
Each data source can send data individually to the cloud system, but often a number of sources will be connected on a LAN. Most LANs of this kind are protected in some way from the open Internet, either by a secure firewall or in many cases simply by not having any physical connection to it. Ideally, to distribute this well-protected data via the cloud, you want to be able to pull the data you need from the system and recreate it remotely, without opening any firewalls and without interfering at all with other data communication taking place on the LAN.
A real-time LAN-to-LAN cloud system is able to maintain a complete copy of the data set from the source LAN and send it across to the user LAN, continuously updating it in real time. On the user LAN, the effect is that the entire source data set becomes immediately available, just like another node on the network.
Of course, data consumers can also make their own direct connections to a real-time cloud server, but there are many benefits from creating synchronized LAN-to-LAN connections. For example, if a corporate office requires access to a remote plant, it would much prefer to maintain its own LAN-based system that replicates the data in the remote plant. This would allow multiple researchers, engineers and managers to access the plant data without making their own connections to the cloud or the plant.
By keeping a single system synchronized with the cloud server, all data is transmitted from the cloud only once, and then distributed inside the local LAN to any number of users. This produces both cost savings and improved responsiveness for those on the LAN. It also allows for implementing redundancy. Of course, this synchronization should occur without the need to open a port in the corporate firewall. Effectively, the cloud server must act as a bridge between two client connections, both occurring from within fully secured firewalls.
So, this is what is so special about a real-time infrstucture for cloud computing. It requires quick data rates and low latency, and it reverses the client/server relationship at the data sources to keep firewalls closed. It relies on a data-centric infrastructure, allows for redundancy, and finally, it can bridge the process LAN to the corporate LAN to support fully synchronized data sets in real time. With the value of this kind of infrastructure understood, we can now talk about real-time cloud computing in a meaningful way.