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Episode 5: Living On The Edge

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Episode 5: Living On The Edge
Series: Making Sense of Sensor Data

 

[00:00:10] It’s not always obvious to people why edge computing would be important to our system.

[00:00:14] In a traditional cloud platform you’re kind of sending all of the data up. The amount of it is very large. So one of the ways that we can address that is being able to use the compute power of the devices themselves, decide how much data has to be sent up to the cloud versus what we can keep on a device.

[00:00:33] How do you process this information in a timely enough fashion? There’s all kinds of inbound data that comes from different sources. Some may come from sensors, some of it may come from third party data sources. I have to aggregate that information fast enough in order to make a decision that’s relevant in the timeframe that I have available. I think we’ve all had this experience where we’re driving along and you use Google or Waze or some other car direction finding service and it tells you to turn after you’ve already crossed the street where you’re supposed to have turned. So if it doesn’t know exactly where I am and doesn’t know where I’m turning, then that information is no longer actually valuable. So sensor data has the same fundamental problem. By the time the data gets through the network it’s validated and then returned back to the original requester. Nothing can be done. So Sixgill wants to move those decisions closer and closer to the point of decision.

[00:01:24] Edge computing has three primary advantages. Number one when we get the ability to improve our scalability and maintain our scalability under escalating data load by allocating some of the compute resources to computational resources that are on the edge device. The second thing we get as performance increases we can reduce the network traffic. The travel of data back and forth so that we can maintain realtime response and constantly attack latency. We can get a result to a person or device while still relevant to get the results to them. The third thing we get with edge computing is better security resources. One of the primary problems with sensor data is that it’s intrinsically insecure. We’ve seen hacker attacks for instance that have used as entry point relatively innocent since the devices are connected to the Web. The aggregation points that the gateways have compute resources that allow us to an agent on there. We take advantage of edge computing in order to progressively harden the system.

[00:02:24] In some cases it’s important to integrate as SDKs directly on devices. But many more in the future will take on the capability of services integrated directly into cloud Gateway environment. The service that we’re providing not only aggregates data, but we do that cleansing and normalization of it for them. We feed a lot of their decision making capabilities. We feed their analytics platforms and so having this rich granular data set that’s sitting right near their cloud environment is becoming more important to their daily business use.

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