Evolution: Mainframe > Client Server > Mobile/Cloud > Edge

As its name implies, edge computing brings the power closer to the end user application, so instead of devices needing to constantly call home to centralized cloud infrastructure for instructions or analysis they are given the ability to accomplish these tasks on their own.

Together these devices create a massive distributed computing system.

Edge Computing Shift


Benefits of this setup include being able to make autonomous operational decisions, gracefully degrade during connectivity outages, and savings on bandwidth volume and costs.

This new evolution has come about due to the shear volume of data and latency required by modern applications like drones and autonomous cars (A self driving car for instance could create up to 4,000 GB of data a day). The trend is enabled by increasingly affordable and sophisticated edge hardware along with advancements in machine learning and on-board GPUs.

The cloud will become a strategically used resource where only the most important information is sent. The cloud can analyze, integrate and the send back only its most important learnings to the edge device in a reciprocal relationship.

In the IoT edge intelligence ecosystem overview below we cover:

  • Hardware vendors
  • Edge analytics and software providers
  • Example use cases


Edge Device Hardware


Sensors

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Edge Software & Analytics

AWS Greengrass
Software that lets you run local compute, messaging & data caching for connected devices in a secure way. With AWS Greengrass, connected devices can run AWS Lambda functions, keep device data in sync, and communicate with other devices securely – even when not connected to the Internet.

EdgeX

Cisco Fog Director
Fog Director delivers the capability to manage large-scale production deployments of IOx-enabled fog applications.

Cisco IOx
The Cisco IOx application environment combines IoT application execution within the network infrastructure; secure connectivity with Cisco IOS Software; and powerful services for rapid, reliable integration with Internet of Things (IoT) sensors and the cloud. By bringing application execution capability to the source of IoT data, customers overcome challenges with high volumes of data and the need for automated, near–real time system responsiveness.

IoT Edge Ecosystem

Industry Groups

Open Fog Consortium

Living Edge Lab - We are building a real-world testbed for Edge Computing with leading edge applications and user acceptance testing

ETSI Multi-access Edge Computing (MEC)
The Multi-access Edge Computing (MEC) initiative is an Industry Specification Group (ISG) within ETSI. The purpose of the ISG is to create a standardized, open environment which will allow the efficient and seamless integration of applications from vendors, service providers, and third-parties across multi-vendor Mobile-edge Computing platforms

.EdgeX Foundry
A Linux Foundation project to build a common open framework for Internet of Things (IoT) edge computing and an ecosystem of interoperable components that unifies the marketplace and accelerates enterprise and Industrial IoT.

Examples and Use Cases

Coca Cola Freestyle Machine

Waggle - Waggle is a research project at Argonne National Laboratory to design, develop, and deploy a novel wireless sensor platform to enable a new breed of sensor-driven environmental science and smart city research.

Additional resources

Background Articles

Videos / Presentations

Research Papers

Events

Notable acquisitions in the space

Difference between Edge and Fog computing?

Within the IoT industry there is a bit of confusion on the use of these two terms. Oftentimes they are used interchangeable and others see a bit of a difference in where exactly the computation is done differently in a Fog or Edge system.

The Fog Computing term was made famous by Cisco with Edge Computing having a longer life. Fog computing can be viewed as having the intelligence at the local area network level of network architecture, processing data in a IoT gateway level, whereas Edge would be seen having the intelligence all the way directly on the edge device itself without necessarily in between.

Fog Vs Edge Computing