Column - From the Clouds to the Fog

This is one of a series of articles from the last decade, updated by request to adopt to changing times. The original was published as Clouds and Rain in the August 2008 issue of Automated Buildings.

Cloud Computing is a name for putting computing services, whether traditional, such as CRM applications, or modern, such as SaaS, on computers up in the wider network. In 2008, I was reading Dennis Brandl, a thought leader among practitioners of factory control systems. The challenges of factory systems are both greater and less than building systems. They are greater because, well the systems are larger and more complex. The challenges are simpler because no factory needs to be convinced that better control of factory automation offers benefits. One constant, though, is that most such systems have developed in a silo outside of traditional IT, and so are slow to adapt the protocols and service architecture of today’s Web 2.0 world.

In the July issue of Control Engineering, Dennis Brandl described his classification of clouds. This is more critical today, as large vendor marketing has re-branded the term “cloud” to mean only “hosted in large data centers by the likes of Amazon or IBM or Microsoft.” Just as they did before with the Enterprise Service Bus, they have turned a useful architectural concept into something smaller and branded.

Brandl divided cloud computing into cumulus, stratus, and cirrus clouds, respectively the lowest, the mid atmosphere, and highest clouds. He then discussed which computing processes belong in which clouds, with the highest clouds being the least connected to direct control processes. This is useful because it lets us distinguish between clouds. In 2008, Brandl advocated nearly everything in the cloud, with only the core control processes on the ground. For buildings and energy, this puts protocols such as BACnet, LON, ModBus, and DNP3 on the ground. Anything in the clouds should interact using internet protocols.

New options in computing and small-scale intelligence introduce patchy fog and mist (or just fog) into the technical conversation.

Traditional control systems used no clouds – only towers in the sky. Whether or not it makes sense, building systems from one building or many have traditionally gone up to a central point; they have been a silo reaching up into the clouds.

Back then, I advocated for enterprise energy monitoring and building control in the low-lying cumulus clouds.
Today, I would look to managing energy and service delivery in local autonomous systems. These autonomous systems are the fog. Fog offers thinly disbursed nodes of intelligent actors. The challenge in Fog architectures is coordinating response across the fog.

We see this problem in guard drones. With a little searching, you can find reports and videos of autonomous patrol boats in the Chesapeake. In early experiments, these boats would swarm, that is all boats would converge on a detected threat, leaving the other side of a port unguarded. In demonstrations, last winter, only a portion of a fleet would converge on a threat, while the remainder spread themselves out, and searched for similar threats across the perimeter. The coordination has gotten better and more sophisticated. Fog on the water.

Cryptochain technologies bring the databases into the fog. Cryptochains create distributed consensus databases. Each transaction is written down by those systems closest to the event, and because there are several copies, any changes can be detected. This removes the need for high-speed and expensive database connections at all times. The oldest cryptochain technology is blockchain, and many refer to this whole type of technology as blockchain. One of the newest technologies is Tangle, based on directed acyclic graphs (DAG).

Autonomous cars are pushing the Patchy Fog model of computing. Today, they rely on traditional “big data center” computing. The Cirrus Clouds, though, are too far away, and the transmission time to and from far away cloud center make the response time too great. Neighborhood phone centers (POPs), no longer needed as people cut off their land lines, are being re-purposed as local cloud computing centers to support safe driving. Simple pattern recognition and response (“Look, a dog!”) are handled locally, more advanced or tactical services are provided in the patchy fog, and the high-level guidance (traffic ahead) is managed to the Cirrus Clouds.

[an error occurred while processing this directive]The question to many is whether the local mist can provide higher level Artificial Intelligence (AI). It is one thing for the auto companies to create custom systems and software to build into cars. What about the rest of us? This post from Microsoft seems to answer the question with a resounding yes; AI on Raspberry Pi is accessible to any smart building system.

Transactive resource management becomes a means to coordinate systems in the fog. Transactive Energy and Transactive Water enable disparate systems to coordinate their behaviors even without direct controls. Without common controls, these systems can evolve far faster than we have seen traditionally in building systems. Transactive resource management can work without central controls and databases by using lightweight cryptochain systems to track interactions locally and securely.

Keep some clouds close to you, ones in which fast response and control are the most important. Let some clouds drift up into the atmosphere, where forces out of your control may determine their performance and availability, but where superior resources or specialized knowledge can be purchased. And put services where enterprise identity and line of business interaction are the most important in the stratus layer.

Changing business interactions and requirements can change which cloud best matches the business process. The protocol for communication to any cloud layer should be the same; internet ready, secured, and standards-based, ready for e-commerce.

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