Industry experts believe that together, edge computing and distributed cloud improve the user experience of a network. While these technologies are related, they are distinct and unique.
Edge computing refers to computing happening at the edge of a network. Various access points define the network edge, hence the name for its architectural standard, Multi-access Edge Computing (MEC). Edge access points include cell phone towers, routers, WiFi, and local data centers.
A distributed cloud refers to having computation, storage, and networking in a micro-cloud located outside the centralized cloud. Examples of a distributed cloud include both fog computing and edge computing. Establishing a distributed cloud situates computing closer to the end user, providing decreased latency and opportunities for increased security. Potential security solutions include a blockchain-based security architecture or random auditing of data to check for integrity. A distributed cloud also processes data in real-time.
The Future Need for Edge and Distributed Cloud
Edge computing is already a reality. It’s anticipated that a significant increase in connected technology will surge the demand for edge computing to alleviate network traffic. One major contributor to its growth is the Internet of Things (IoT). Santhosh Rao, Gartner’s senior analyst, commented that “currently, around 10 percent of enterprise-generated data is created and processed outside a traditional centralized data center or cloud. By 2025, Gartner predicts this figure will reach 75 percent.”
The Advantages of Edge Computing as a Distributed Cloud
Edge computing offloads data to the cloud during peaks in computing traffic, thus ensuring a quick, reliable, real-time connection.
For example, IoT devices often require constant internet connections, sometimes along with low latency needs. Edge helps manage the massive amounts of data produced by IoT devices by storing and processing the data locally until a connection can be reestablished, or by quickly sending data to the central cloud when the network is overwhelmed.
Edge computing allows smart manufacturing machines to operate without relying on a large central data center or cloud. Using the edge for analysis of data gathered on location minimizes the amount of data infrastructure needed and means less frequent disruptions.
With edge computing, machines in a smart factory will be automated. Edge computing can enable the many devices in the factory to work together. Sensor data can allow for changes to speed of operations to adapt to conditions of the machinery. Outside of IoT uses, predictive analytics can help factory managers plan for machine part replacement, minimizing downtime.
Since distributed clouds are local to the user, data only has to travel a short distance to the compute, storage, or network resources. This means less data is going greater distances to large data centers or centralized clouds, and there is an overall decrease in network traffic congestion.
A distributed cloud can reduce the strain of wearable devices on the core network, because data from those devices doesn’t have to go as far to get to the necessary server for data storage and processing, minimizing the use of network infrastructure.
Updated April 2019