IDG Contributor Network: Stay smart as you approach the edge

Fundamental to harnessing the full potential of the Internet of Things (IoT) is the need for decisions to be made in real time, and it’s in addressing this that discussions have turned to the subject of edge computing over recent years.

Before the data generated by myriad of connected IoT devices is sent to the centralized cloud, edge computing sees it stored and processed locally, in distributed micro-clouds at the edge of the network, closer to where the devices are placed, and the data produced. Doing so cuts down on the need for data traffic to be back-hauled to and from a remote data center, thus making it ideal for supporting the real time data delivery required by the IoT.

This is further optimized by the deployment of machine learning, effectively making edge compute devices “smarter”, empowering each one to train itself using the particular dataset it processes to conduct more effective analysis to glean actionable intelligence at the edge.

Edge computing also lends itself to improving the efficiency and efficacy of data-driven cloud-based enterprise applications and addresses several issues faced by businesses today. With data first processed by multiple interconnected micro-data centers close to the edge, before being sent to the cloud for additional processing on a global level, IT teams are afforded more application scalability and enjoying perhaps the greatest benefit of edge computing – significantly reduced latency.