Things Computing: Wait, What About the Cloud?

Two starkly different elements of our ecosystem behave in a similar manner. On the one hand there’s water, the source of all life and a necessary natural resource, and on the other there’s technology, essentially man-made and denoting human progress and innovation. It is the cyclical nature of these disparate elements that make them alike as functional constructs.

One could ascertain the veracity of this by comparing the water cycle with computing technology. Water moves through the states of matter via evaporation, condensation, and precipitation, only to arrive at the first stage of the cycle yet again. The computing market has likewise evolved from mainframes to Cloud servers only to arrive at edge computing.

Decoding “Things” Computing

While Cloud computing hinges on extracting operational insights from sensors, supervisory control and data acquisition (SCADA) systems, and IoT-enabled devices, ‘edge’ refers to computing infrastructure that functions close to the data source. I prefer referring to these data sources as “things” as edge computing is where there’s a cyber-physical connect through which software programs meet and interact with machines.

Forecasting the Technological Weather

By 2019, things computing is expected to store, process, analyze and act upon at least 40% of IoT-generated data. The functional scope of “things” in terms of the data they are capable of producing is unprecedented. We’re speaking about zettabytes of data from intelligent machines retrofitted with embedded software programs that can perform small-scale analysis.

But why analyze data on the edge rather than on the Cloud? The answer’s simple: it is more expensive and time-consuming to send massive volumes of data to the Cloud than to pack in all the functions into smaller devices at the edge.

Decision-Making at the Edge

Simply put, edge computing reduces response time and in some situations, this could make the difference between life and death. Self-driving cars, for instance generate data on the go through sensors and embedded communication systems. However, if one relies on GPS systems and video cameras to keep track of distance, pedestrians, and other vehicles on the road, and waits for data to be sent to the Cloud and then processed, an accident might well be the end result. It is in these situations that things computing brings its value to the table, enabling advanced products such as autonomous cars to be true to their names.

While there’s limited infrastructure to support edge computing, the development of hyper-local 5G mobile network capabilities is likely to change the situation. Latency and connectivity challenges of machines will then become a thing of the past.

Synergizing Edge with the Cloud

Experts suggest that edge computing will be a game changer in 2018. But, Cloud and things computing aren’t quite diametrically opposite approaches. One can locate areas of synergy between the two. For a start, companies can create a service-oriented architecture that can operate in disconnected areas of the Cloud. When Cloud and edge computing work in tandem, the computing topology itself represents a framework where information collection, processing, and delivery is bereft of impediments.

An optimized collocation of things computing with the Cloud will not just help enterprises overcome latency, bandwidth, and connectivity challenges, but also establish a scalable architecture. For organizations then, the real challenge is to build a co-habitable ecosystem for the edge and Cloud to ensure smooth interoperability for a new generation of technology. And for us, all we need to do is wait and see this paradigm shift take effect.