Many IoT devices take advantage of cloud computing to process and store the data they produce. However, many developers are discovering the benefits of doing more computing and analytics on the devices themselves. This helps reduce latency, lower dependence on the cloud, and better manager the data deluge that is generated by IoT applications.
The common term for doing on-device processing and analytics is called “Edge Computing”, and is one of the hottest growth areas in IoT for 2018. The Edge is an ecosystem of internet-connected devices and gateways sitting on a virtual field, which is the counterpart to the Cloud. Edge computing provides new possibilities in IoT Applications, particularly for those relying on machine learning for tasks such as face recognition, language processing and object detection.
Both Edge and Fog computing are on the rise for managing the data associated with these tasks. However, don’t confuse Edge for Fog computing. Fog computing works with the Cloud, whereas Edge is defined by the exclusion of Cloud and Fog. Fog is hierarchical while Edge tends to be limited to a number of peripheral layers. Additionally, Fog also addresses networking, storage, control and data processing. Edge computing brings the analytics, computing, communications close to or into the device.
Why is this important? For a mix of reasons, mainly bandwidth, costs, speed, automation, maintenance, predictive analytics, remote connectivity, etc. These applications need a cheaper, and faster approach to connect and control their processes. This increases the pressure on the networks driving the IoT.
That’s where Edge computing really starts to make sense. If the data is generated at the Edge, then why not bring all of the intelligence and analysis as close to the Edge as possible? There are obvious benefits as the growing market for IoT devices skyrockets. The need for faster processing, increased strain on the Cloud, and increased pressure on networks will necessitate Edge computing.
Edge computing will also bring market opportunities for those working to secure and connect the edge of IoT. At the hardware level, trusted platform modules (TPM) will need to integrate cryptographic keys in chips that can be used by the software late for device authentication. The keys will then need to have encryption/decryption occurring on the TPM level, and not via sharing keys.
At the communication later, the data transmitted needs to be secure so being attacked “in the middle” can be avoided. Some common entry points to monitor would be local communications, where an endpoint device talks to one or more Edge gateways. Also, long range communications when gateways communicate with each other or a central cloud platform via an orchestration layer.
Cloud Security also needs to be maintained. Sensitive data should be moved from the Edge to the Cloud with encryption in place. A software layer for managing and configuring devices can simplify the movement of encrypted data to the master and vice versa. All digital certificates play a role in authentication of Cloud or third party applications communicating with the Cloud service.
This makes the communication layer very important. Using something like intelligent frequency hopping spread spectrum (FHSS) technology can take advantage of real-world Fog and Edge computing. FHSS is one option that can provide security and connectivity for such applications, putting the final piece of the Edge together. Sounds like an exciting new connected future.
To learn more about Edge Computing and FHSS, attend the 2018 IOT North America Conference and check out FreeWave Technologies FHSS/Edge Computing Session here: http://iotna.com/schedule/remote-intelligent-edge-fhss/