Internet of Things Development Trend 4 (2019)

Continued from the previous article:

• "The Development Trend of Internet of Things (2019)"
• "Development Trends of the Internet of Things 2 (2019)"
• "Development Trends of the Internet of Things 3 (2019)"

In the article IoT Development Trends 3 (2019), we introduced two modes of edge computing: fixed logic processing mode and artificial intelligence learning mode. Today we will continue to discuss the processing mechanism of edge computing.

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Device edge measurement and cloud center control selection mechanism

A device can be controlled by the edge or by the cloud computing center. The following problems need to be solved when controlling the device:

• Is this device controlled by the edge (or cloud center) alone? Or can it be controlled by both the edge and the cloud?
• If single control is selected, which types of equipment are suitable for edge computing control, and which types of equipment are suitable for operation center control?
• If this device can be controlled by both the edge and cloud centers at the same time, when the control of the edge and cloud computing is inconsistent, which control should the device respond to first?

These problems are not prominent when edge computing is still immature. When edge computing becomes popular, these problems will trouble system designers.

Let’s try to use human processing mechanisms to provide some reference for the development of edge computing.

Selection of low-end neural control and high-end neural control of organs

I chose to explain the control methods of the heart, lungs and hands respectively.

Can people control the beating of their hearts with their brains? The beating of the heart is not controlled by the brain.

The lungs can be controlled by the brain. For example, people can consciously control their breathing rate, and can adjust deep and shallow breathing. They can also consciously hold their breath. But when you hold your breath for a long time and reach the limit of holding your breath, even if the brain still controls the lungs to hold their breath, the lungs no longer accept the control of the brain, but choose to be controlled by the low-end nerves.

The hand is controlled by the brain most of the time. However, under some extreme conditions, the hand is controlled by the low-end nerves: the hand suddenly encounters painful stimulation [such as the finger encountering fire].

It can be seen that there is a mechanism for people to accept low-end neural control and high-end neural control: in order to ensure safety, low-end neural control is mostly used, while in order to ensure flexibility, high-end neural control is often chosen.

The safety-related processing mechanisms are solidified into the low-end nerves, and when encountering safety-related choices, low-end nerve control is given priority.

For organs that require high flexibility, high-end nerve control is more commonly used.

Device control selection mechanism

According to the mechanism of high-end neural and low-end neural control, the edge computing and cloud computing control mechanism of future IoT devices can be designed as follows:

• Security-related processing logic is solidified at the edge and is the highest priority control.
• According to the importance of the equipment, choose edge measurement and cloud computing control. For example, for equipment with the highest security level, choose edge computing control.
• According to the flexibility of device functions, choose edge measurement and cloud computing control. If flexible devices are required, choose cloud computing control.
• Define a safety threshold boundary. Once safety reaches this threshold boundary, the device is automatically processed by the inherent logic of edge computing.

summary

After edge computing is perfected, we will face the dilemma of choosing between cloud computing control and edge computing control. Drawing on human processing experience, we can consider it from two dimensions: security and flexibility. Edge processing with high security and low flexibility; cloud computing processing with low security and high flexibility; cloud computing control with high security and high flexibility, with high edge monitoring level; edge control with low security and low flexibility, with moderate increase in cloud computing control capabilities.