The Return of Edge Computing

We just went through a decade where the majority of industry experts told us that most of our computing needs were going to move to the cloud. But it seems that that trend is starting to reverse somewhat and there are many applications where we are seeing the return of edge computing. This trend will have big implications for broadband networks.

Traditionally everything we did involved edge computing – or the use of local computers and servers. But a number of big companies like Amazon, Microsoft and IBM convinced corporate America that there were huge benefits of cloud computing. And cloud computing spread to small businesses and homes and almost every one of us works in the cloud to some extent. These benefits are real and include such things as:

  • Reduced labor costs from not having to maintain an in-house IT staff.
  • Disaster recovery of data due to storing data at multiple sites
  • Reduced capital expenditures on computer hardware and software
  • Increased collaboration due to having a widely dispersed employee base on the same platform
  • The ability to work from anywhere there is a broadband connection.

But we’ve also seen some downsides to cloud computing:

  • No computer system is immune from outages and an outage in a cloud network can take an entire company out of service, not just a local branch.
  • A security breach into a cloud network exposes the whole company’s data.
  • Cloud networks are subject to denial of service attacks
  • Loss of local control over software and systems – a conversion to cloud often means losing valuable legacy systems, and functionality from these systems is often lost.
  • Not always as cheap as hoped for.

The recent move away from cloud computing comes from computing applications that need huge amounts of computing power done in real time. The most obvious examples of this is the smart car. Some of the smart cars under development run as many as 20 servers onboard the car, making them a driving datacenter. There is no hope of ever moving the brains from smart cars or drones to the cloud due to the huge amounts of data that must be passed quickly between the car’s sensors and its computers. Any external connection is bound to have too much latency to make true real-time decisions.

But smart cars are not the only edge devices that don’t make sense on a cloud network. Some other such applications include:

  • Drones have the same concerns as cars. It’s hard to imagine a broadband network that can be designed to always stay in contact with a flying drone or even a sidewalk delivery drone.
  • Industrial robots. Many new industrial robots need to make decisions in real-time during the manufacturing process. Robots are no longer just being used to assemble things, but are also being used to handle complex tasks like synthesizing chemicals, which requires real-time feedback.
  • Virtual reality. Today’s virtual reality devices need extremely low latencies in order to deliver a coherent image and it’s expected that future generations of VR will use significantly more bandwidth and be even more reliant on real-time communications.
  • Medical devices like MRIs also require low latencies in order to pass huge data files rapidly. As we built artificial intelligence into hospital monitors the speed requirement for real-time decision making will become even more critical.
  • Electric grids. It turns out that it doesn’t take much of a delay to knock down an electric grid, and so local feedback is needed to make split-second decisions when problems pop up on grids.

We are all familiar with a good analogy of the impact of performing electronic tasks from a distance. Anybody my age remembers when you could pick up a telephone, have instant dialtone, and then also got a quick ring response from the phone at the other end. But as we’ve moved telephone switches farther from customers it’s no longer unusual to wait seconds to get a dialtone, and to wait even more agonizing seconds to hear the ringing starting at the other end. Such delays are annoying for a telephone call but deadly for many computing applications.

Finally, one of the drivers to move to more edge computing is the desire to cut down on the amount of bandwidth that must be transmitted. Consider a factory where thousands of devices are monitoring specific operations during the manufacturing process. The idea of sending this mountains of data to a distant location for processing seems almost absurd when local servers can handle the data at faster speeds with lower latency. But cloud computing is certainly not going to go away and is still the best network for many applications. In this factory example it would still make sense to send alarms and other non-standard data to some remote monitoring location even if the data needed to keep a machine running is done locally.


Machine Generated Broadband

One of the more interesting predictions in the latest Cisco annual internet forecast is that there will be more machine-to-machine (M2M) connections on the Internet by 2021 than there are people using smartphones, desktops, laptops and tablets.

Today there are a little over 11 billion human-used machines connected to the Internet. That number is growing steadily and Cisco predicts that by 2021 there will be over 13 billion such devices using the Internet. That prediction also assumes that total users on the internet will grow from a worldwide 44% broadband penetration in 2016 to a 58% worldwide penetration of people that have connectivity to the Internet by 2021.

But the use of M2M devices is expected to grow a lot faster. There are fewer than 6 billion such devices in use today and Cisco is projecting that will grow to nearly 14 billion by 2021.

So what is machine-to-machine communication? Broadly speaking it is any technology that allows networked devices to exchange information and perform actions without assistance from humans. This encompasses a huge range of different devices including:

  • Cloud data center. When something is stored in the cloud, most cloud services create duplicate copies of data at multiple data centers to protect against a failure at any given data center. While this does not represent a huge number of devices when measured on the scale of billions, the volume of traffic between data centers is gigantic.
  • Telemetry. Telemetry has been around since before the Internet. Telemetry includes devices that monitor and transmit operational data from field locations of businesses, with the most common examples being devices that monitor the performance of electric networks and water systems. But the devices used for telemetry will grow rapidly as our existing utility grids are upgraded to become smart grids and when telemetry is used by farmers to monitor crops and animals, used to monitor wind and solar farms, and used to monitor wildlife and many other things in the environment.
  • Home Internet of Things. Much of the growth of devices will come from an explosion of devices used for the Internet of Things. In the consumer market that will include all of the smart devices we put into homes such as burglar alarms, cameras, smart door locks and smart appliances of many kinds.
  • Business IoT. There is expected to be an even greater proliferation of IoT devices for businesses. For example, modern factories that include robots are expected to have numerous devices that monitor and direct the performance of machines. Hospitals are expected to replace wires with wireless networked devices used to monitor patients. Retail stores are all investigating devices that track customers through the store to assist in shopping and to offer inducements to purchase.
  • Smart Cars and Trucks. By 2021 it’s expected that most new cars and trucks will routinely communicate with the Internet. This does not necessarily imply self-driving vehicles, but rather that all new vehicles will have M2M capabilities.
  • Smart Cities. A number of large cities are looking to improve living conditions using smart city technologies. This is going to require the deployment of huge numbers of sensors that will be used to improve things like traffic flow, monitoring for crimes and improvement everyday things like garbage collection and snow removal.
  • Wearables. Today there are huge numbers of fitness monitors, but it’s expected that it will become routine for people to wear health monitors of various types that keep track of vital statistics and monitor to catch problems at an early stage.
  • Gray Areas. There are also a lot of machine-to-machine communications that come from computers, laptops and smartphones. I see that my phone uses data even at those times when I’m not using it. Our devices now query the cloud to look for updates, to make back-ups of our data or to take care of other tasks that our apps do in the background without our knowledge or active participation.

Of course, having more machine-to-machine devices doesn’t mean that this traffic will grow to dominate web traffic. Cisco predicts that by 2021 that 83% of the traffic on the web will be video of some sort. While most of that video will be used for entertainment, it will also include huge piles of broadband usage for surveillance cameras and other video sources.

If you are interested in M2M developments I recommend M2M: Machine2Machine Magazine. This magazine contains hundreds of articles on the various fields of M2M communications.