The term “edge computing” has become a buzzword. Professionals are extolling the virtues of the Edge, but what does it really mean; as an element of the technological lexicon, and as a commodity or services for your enterprise?

What is edge computing?

In edge computing, data is transmitted, analyzed and stored much more locally than in traditional cloud computing. For example, an autonomous vehicle located in San Francisco would see data processing occur in the same geographic region; as opposed to in Europe, South America or India.

This workload configuration has numerous advantages, from greater compute expediency and reduced latency to lower bandwidth requirements for transporting the data; key issues that have arisen through the expanded adoption of the cloud.

Use-cases for edge computing

Edge computing has limitless potential, but projects that excite business leaders and engineers alike include:

  • Enabling industrial machines to more accurately assess and account for the causes of any seeming malfunctions. Local processing of data will mean that machines can detect whether they’re overheating due to solar exposure, or due to other causes. These type of self-conducted analyses can improve operational efficiency.
  • Providing healthcare organizations with the capacity to process data in real-time. This could potentially improve patient experiences and even affect health outcomes.
  • Improving the speed and efficacy of real-time decision making within autonomous vehicles. By processing data locally, autonomous vehicles will be able to more adroitly adapt to rapidly changing traffic patterns and obstacles.

Edge vs. Fog

The Edge and Fog are similar, as they both push data processing and analysis to locations that are close to the data’s origin. Edge computing typically occurs either on the device’s sensors, or in a gateway that is on the device. Fog computing involves processing information on LAN hardware, making processing and analysis more distant from the device itself.

Benefits of edge computing

  • Reduced processing latency.
  • Fewer demands on cloud bandwidth.
  • Decreased server resource requirements.
  • Possible cost savings.
  • More limited hardware and software management demands. 

Challenges associated with edge computing

  1. Processing power. Edge computing uses smaller processors and storage platforms than are available within the cloud. This means that users will experience greater limitations when it comes to throughput. Sending too much data into an edge infrastructure can overwhelm the system.
  2. Security. As with IoT, the design of edge computing took place first, and security concerns surfaced later.

How secure are edge computing devices?

The evolution of security mechanisms for edge computing has not kept pace with the evolution of the Edge itself. When deploying edge-based infrastructure, be sure to apply two factor authentication, and to manage passwords effectively.

Additionally, edge computing isn’t just a cyber security risk. It also presents physical security risks. When data processing takes place in a local space or on a local device, a bad actor could disrupt or destroy the local infrastructure. For deeper insights into how to secure your edge devices, be sure to see this whitepaper.

Lastly, please join us at the premiere cyber security event of the year – CPX 360 2022. Register here.