CoBank Touting Edge Computing

A recent article from CoBank is titled, Partnerships are Key for Rural Telecom Operators in Burgeoning Edge Computing Market. The article points out that there are potential opportunities for ISPs to grab a small piece of the edge computing market.

The article defines edge computing as a network architecture where data is stored and/or processed at locations close to where applications are being used. The growth of edge computing is an interesting phenomenon to watch because it reverse the trend of the last decade, where the goal was to move as much data as possible to large data centers and not process or store at the edge.

However, as the volume of data being generated by companies has increased exponentially, the tasks of moving data back and forth from data centers has added cost and time to the equation. Companies are looking deeper at the data they generate and are realizing that a lot of the data doesn’t need to be permanently cached at data centers. Companies also want to avoid the added latency from moving and processing things in a data center.

The article cites the following potential opportunities.

  • C-RAN. The trend identified is for cellular companies to process customer connection functions locally at cell sites instead of in the cloud. The opportunity for rural ISPs is to cell more connectivity to the expanding number of cell sites. However, is cellular data is processed locally, that would imply smaller transport bandwidth needed at each cell site.
  • Private Wireless Networks. The cellular carriers and companies like Microsoft and Amazon are likely to tackle this market. While there may be a few large customers in rural markets that want to participate in a private wireless network, the big opportunity is in selling the service to farms. Local ISPs can partner with one of the big application developers that will provide a communications suite for farms. The ISP opportunity will be selling transport to farms, but also possibly being hired to maintain farm wireless devices and monitors.
  • Internet of Things (IoT). This is the trend to develop smart sensors that can handle data locally without sending everything to a data center. Like with C-RAN, it seems like a stretch to see a role for a small rural ISP in the market other than perhaps being the local agent for the sensor devices.
  • Self-Driving Cars. The article relies on a prediction that a self-driving car will need to offload as much as 5,000 gigabits per hour of driving. I find it impossible to believe that anybody is going to invest in the network in rural areas that will ever serve this market. Most of the auto industry is chasing a future where vehicles will possess the needed computing power onboard rather than rely on somebody building a fiber network and billions of sensors along every mile of US highways. I was surprised to see this in the CoBank article since the chances of this happening seem slim.

The only opportunity on this list that might realistically materialize in the next decade and be a revenue opportunity for rural ISPs is private wireless networks for farms. It’s not hard to imagine a business relationship where rural ISPs become the local agent for smart farming connectivity and devices, in much the same way that many local ISPs were the agent for products like DirecTV. It’s not hard to imagine the rural ISP industry associations negotiating a contract for such services on behalf of members, making it easy to participate.

I was intrigued to see CoBank writing this article because bankers generally concentrate on opportunities that are either here today or on the immediate horizon. This article talks about pretty futuristic stuff. The question any rural ISP will ask is if any of these applications will ever become tangible and actionable. I remember a decade ago when the rage in the industry was telling rural ISPs that there was a lot of money to be made in fostering cellular offload to WiFi. I can’t think of anybody I know that ever made a nickel on the idea, but you couldn’t go to an industry meeting without somebody promoting the idea. There is a whole lot of steps that have to happen  before any of these edge-computing ideas turn into something that the average rural ISP can profitably participate in. But I have no doubt that some of the ideas in this article, or applications we haven’t thought of, will become real eventually. The one thing that rural ISPs have that is hard to duplicate is a local presence and local technical expertise.

You Can’t Force Innovation

The new video service Quibi failed after only 7 months of operation and after having received $2 billion in backing from big industry players. The concept was to offer short 5 to 7-minute video serials that would get viewers engaged in a story from day-to-day and week-to-week. The failure seems to be due to nobody being interested in the format. Younger viewers aren’t interested in scripted Hollywood content and instead watch content created by their peers. Older people have now been trained to binge-watch. It turns out there no audience for the concept of short cliff-hanger videos.

The Quibi failure reminded me that you can’t force innovations onto the public. We live in a society where everything new is hyped beyond belief. New technologies and innovations are not just seen as good, but in the hype-world are seen as game changers that will transform society.  A few innovations live up to the hype, such as the smartphone. But many other highly-hyped innovations have been a bust.

Consider bitcoin. This was a new form of currency that was going to replace government-backed currency. But the public never bought into the concept for one big fundamental reason – there is nothing broken about our current form of money. We deposit our money in banks, and it sits there safely until we’re ready to use it. For all of the endless hype about how bitcoin would change the world, I never heard a good argument about why bitcoin is better than our current banking system – except maybe for criminals and dictators that want to hide wealth.

Another big bust was Google Glass. People were not ready to engage with somebody in public who could film them and replay a casual conversation later or post it on social media. People were even more creeped out by the stalker aspect of men using facial recognition to identify and stalk women. To give credit to Google, the folks there never envisioned this as a technology for everybody, but the Internet hype machine played up the idea beyond belief. The public reaction to the technology was a resounding no.

Google was involved in another project that hit a brick wall. Sidewalk Lab, a division of Alphabet envisioned a new smart city being created on the lakefront in Toronto. To tech folks, this sounded great. The city would be completely green and self-contained. Robots would take care of everything like emptying trashcans when they are full, to setting up picnics in the park and cleaning up afterwards. Traffic was all underground and an army of robots and drones would deliver everything people wanted to their doorstep. But before this even got off the drawing board, the people of Toronto rejected the idea as too big-brotherish. The same computer systems that catered to resident demands would also watch people at all times and record and categorize everything they do. In the end, privacy won out over technology.

Some technologies are hyped but never materialize. Self-driving cars have been touted as a transformational technology for over a decade. But in the last few years, the engineers working on the technology acknowledge that a fully self-sufficient self-driving car is still many years away. But this doesn’t stop the hype and there are still articles about the promise of self-driving cars in the press every month.

Nothing has been hyped more in my lifetime than 5G. In the course of recently watching a single football game, I must have seen almost a dozen 5G commercials. Now that 5G phones are hitting the market, the new technology is likely going to soon be perceived by the public as a bust. The technology is being painted as something amazing and new, but recent tests show that 5G is no faster than 4G in 21 of 23 cities. 5G will eventually be faster and better, but will today’s hype make it hard for the cell companies to explain when 5G is actually here?

I could continue to list examples. For example, if I had believed the hype, I’d now live in a fully-automated home where I could talk to my home and have it cater to my every whim. I’d have unlimited power from a cheap neighborhood fusion power plant that produces unlimited and clean power fueled by water. I’d be able to avoid a commute by using my flying car. There is much to like in the hype-world, but sadly it’s not coming any time soon.

Self-driving Cars and Broadband Networks

There are two different visions of the future of self-driving cars. Both visions agree that a smart car needs to process a massive amount of information in order to make real-time decisions.

One vision is that smart cars will be really smart and will include a lot of edge computing power and AI that will enable a car to make local decisions as the car navigates through traffic. Cars will likely to able to communicate with neighboring cars to coordinate vehicle spacing and stopping during emergencies. This vision requires only minimal demands for external broadband, except for perhaps to periodically update maps and to communicate with things like smart traffic lights.

The other vision of the future is that smart cars will beam massive amounts of data to and from the cloud that includes LiDAR imagery and GPS location information. Big data centers will then coordinate between vehicles. This second vision would require a massively robust broadband network everywhere.

I am surprised by the number of people who foresee the second version, with massive amounts of data transferred to and from the cloud. Here are just some of the reasons why this scenario is hard to imagine coming to fruition:

  • Volume of Data. The amount of data that would need to be transferred to the cloud is massive. It’s not hard to foresee a car needing to transmit terabytes of data during a trip if all of the decisions are made are made in a data center. Most prognosticators predict 5G as the technology that would support this network. One thing that seems to be ignored in these predictions is that almost no part of our current broadband infrastructure is able to handle this kind of data flow. We wouldn’t only need a massive 5G deployment, but almost every part of the existing fiber backbone network, down to the local level, would need to also be upgraded. It’s easy to fall into the trap that fiber can handle massive amounts of data, but the current electronics are not sized for this kind of data volumes.
  • Latency. Self-driving cars need to make instantaneous decisions and any delays of data going to and from the cloud will add delays. It’s hard to imagine any external network that can be as fast as a smart car making its own local driving decisions.
  • Migration Path. Even if the cloud is the ultimate network design, how do you get from here to there? We already have smart cars and they make decisions on-board. As that technology improves it doesn’t make sense that we would still pursue a cloud-based solution unless that solution is superior enough to justify the cost of migrating to the cloud.
  • Who will Build? Who is going to pay for the needed infrastructure? This means a 5G network built along every road. It means fiber built everywhere to support that network, including a massive beefing up of bandwidth on all existing fiber networks? Even the biggest ISPs don’t have both the financial wherewithal and the desire to tackle this kind of investment.
  • Who will Pay? And how is this going to get paid for? It’s easy to understand why cellular companies tout this vision as the future since they would be the obvious beneficiary of the revenues from such a network. But is the average family going to be willing to tack on an expensive broadband subscription for every car in the family? And does this mean that those who can’t afford a smart-car broadband connection won’t be able to drive? That’s a whole new definition of a digital divide.
  • Outages. We are never going to have a network that is redundant down to the street level. So what happens to traffic during inevitable fiber cuts or electronics failures?
  • Security. It seems sending live traffic data to the cloud creates the most opportunity for hacking to create chaos. The difficulty of hacking a self-contained smart car makes on-board computing sound far safer.
  • Who Runs the Smart-car Function? What companies actually manage this monstrous network? I’m not very enthused about the idea of having car companies operate the IT functions in a smart-car network. But this sounds like such a lucrative function I can’t foresee them handing this off to somebody else? There are also likely to be many network players involved and getting them all to perfectly coordinate sounds like a massively complex task.
  • What About Rural America? Already today we can’t figure out how to finance broadband in rural America. Getting broadband along every rural road is going to be equally as expensive as getting it to rural homes. Does this imply a smart-car network that only works in urban areas?

I fully understand why some in the industry are pushing this vision. This makes a lot of money for the wireless carriers and the vendors who support them. But the above list of concerns make it hard for me to picture the cloud vision. Doing this with on-board computers costs only a fraction of the cost of the big-network solution, and my gut says that dollars will drive the decision.

It’s also worth noting that we already have a similar example of this same kind of decision. The whole smart-city effort is now migrating to smart edge devices rather than exchanging massive data with the cloud. As an example, the latest technology for smart traffic control places smart processors at each intersection rather than sending full-time video to the cloud for processing. The electronics at a smart intersection will only communicate with the hub when it has something to report, like an accident or a car that has run a red light. That requires far less data, meaning far less demand for broadband than sending everything to the cloud. It’s hard to think that smart-cars – which will be the biggest source of raw data yet imagined – would not follow this same trend towards smart edge devices.

Two Visions for Self-Driving Cars

I was at a conference last week and I talked to three different people who believe that driverless cars are going to need extremely fast broadband connections. They cite industry experts who say that the average car is going to require terabytes per day of downloaded data to be functional and that only extremely fast 5G networks are going to be able to satisfy that need. These folks talk about needing high-bandwidth and very low latency wireless networks that can tell a car when to stop when encountering an obstacle. This vision sees cars as somewhat dumb appliances with a lot of the brains in the cloud. I would guess that wireless companies are hoping for this future.\

But I also have been reading about experts that instead think that cars will become rolling data centers with a huge amount of computing capacity on board. Certainly vehicles will need to communicate with the outside world, but in this vision a self-driving car only needs updates on things like the current location and for road conditions and traffic problems ahead – but not the masses of data anticipated by the first future vision cited above.

For a number of reasons I think the second vision is a lot more likely.

  • Self-driving cars are almost here now and that means any needed network to support them would need to be in place in the near future. That’s not realistically going to happen. Most projections say that a robust 5G technology is at least a decade away. There are a dozen companies investing huge sums on self-driving car technologies and they are not going to wait that long to even investigate if controlling cars from external sources makes sense. Every company looking into self-driving technology is operating under the assumption that the brains and sensing must be in the cars – and they are the ones that will drive the development and implementation of the new car technology. It’s not practical to think that the car industry can wait for deployment of the needed networks that are not under their control or reasonably available.
  • Who’s going to make the huge investments needed to build the network necessary to support self-driving cars? The ability to deliver terabytes of data to each car would require much faster data connections than can be delivered using the normal cellular frequencies. Consider how many fast simultaneous data connections would be needed to support all of the cars on a busy multilane highways in a major city. It’s an engineering challenge that would probably require using high frequencies. And that means putting lots of cell sites close to roads – and those cell sites will have to be largely fed by fiber to keep the latency low (wireless backhaul would add significant latency). Such a network nationwide would have to cost hundreds of billions of dollars between the widespread fiber and the huge number of mini-cell sites. I can’t picture who would agree to build such a network. The total annual capital budget for all of the wireless companies combined today is only in the low tens of billion range.
  • Even if somebody was to build the expensive networks who is going to pay for it? It seems to me like every car would need an expensive monthly broadband subscription, adding significantly to the cost of owning and driving a car. Most households are not going to want a car that comes with the need for an additional $100 – $200 monthly broadband subscription. But my back-of-the envelope tells me that the fees would have to be that large to compensate for such an extensive network that was built mostly to support self-driving cars.
  • The requirement for huge numbers of cars to download terabytes of data per day is a daunting challenge. The vast majority of the country today doesn’t even have a landline based broadband connection capable of doing that.
  • There are also practical reasons not to put the brains of a car in the cloud. What happens when there are power outages or cellular outages. I don’t care how well we plan – outages happen. I’d be worried about driving in a car if there was even just a temporary glitch in the network.
  • There are also issues of physics if this network requires any connections to be made by millimeter wave spectrum, or even spectrum that is just a little lower on the frequency scale. There is a huge engineering challenge to get such signals to track a moving vehicle reliably in real-time. Higher frequencies start having doppler shifts even at walking speeds. Compound this with the requirement to always have true line-of-sight and also the issue of connecting with many cars at the same time on crowded roads. I have learned to never say that something isn’t possible, but this presents some major engineering challenges that are going to take a long time to make work – maybe decades, and maybe never.
  • Finally are all of the issues having to do with security. I’m personally more worried about cars being hacked if they are getting most of their communications from the cloud. If cars are instead only getting location and other basic information from the outside it would be a lot easier to wall of the communications stream from the operating computing process, and reduce the chances of hacking. It also seems like a risk if cars get most of their brains from the cloud for a terrorist or mischief-maker to disrupt traffic by taking out small cell sites. There would be no way to ever make such devices physically secure.

I certainly can’t say that we’ll never have a time when self-driving cars are directed by a large outdoor cloud, as often envisioned in science fiction movies. But for now the industry is developing cars that are largely self-contained data centers and that fact alone may dictate the future path of the industry. The wireless carriers see a lot of potential revenue from self-driving cars, but I can’t imagine that the car industry is going to wait for them to develop the needed infrastructure.


Tribrid_CarThere have been a mountain of articles about self-driving cars, but little discussion about how they see the world around them. The ability of computers to understand images is still in its infancy – in 2015 there was a lot of talk about how Google was teaching an AI program how to recognize cats within videos.

But obviously a self-driving car has to do a lot better than just ‘seeing’ around it – it needs to paint a 3D picture of everything around it in order to navigate correctly and to avoid problems. It turns out that the primary tool used by self-driving cars is called “Lidar.” Lidar stands for ‘light detection and ranging’ and fits neatly between sonar and radar.

Lidar works by sending out light beams and measuring how long it takes for reflected signals to return, much the same way that a bat sees the world using sonar. Sonar would be fairly useless in a self-driving car since sound waves get distorted in air and only paint an accurate picture for perhaps a dozen feet from the transmitter. That’s great for a bat catching a moth, but not useful for seeing oncoming traffic.

And the radio waves used in radar won’t really work well for self-driving cars. Radar works great for seeing objects far away, like metallic airplanes. But the radio waves pass through many objects (like people) meaning that radar doesn’t create a total picture of the world around it. And radar has problems creating an accurate picture of anything closer than 100 feet.

And that’s where lidar comes in. A lidar device works much like a big radar dish at an airport. It rotates and sends out light signals (actually infrared light signals) and then collects and analyzes the returning echoes to create a picture of the distances to objects around it. Lidar only became practical with modern computer chips which allow the transmitter to ‘rotate’ hundreds of times a second and which possess enough computing power to make sense of the echoed light waves.

And so a self-driving car doesn’t ‘see’ at all. The cars do not rely on standard cameras that try to make sense of the reflected ambient light around the car. The first prototypes of driverless cars tried to do this and could not process or make sense of images fast enough. Instead self-driving cars send out laser light at a specific frequency and then calculates the distance the light travels in every direction to create a picture of the world.

If you want to understand more about what this looks like, consider this Radiohead music video. Most of the images in the video were created with lidar. Don’t pay too much attention to the opening headshots because those are somewhat distorted for artistic effect. But the later images of seeing streets shows you the detail of a lidar image. Unlike the normal images our eyes see, a lidar image is massively more detailed in that the distance to everything in such a picture is known. Our eyeballs basically see in 2D and we use images from two eyes to simulate 3D. But a lidar image is fully 3D and gets full perspective from one transmitter.

Lidar does have limitations. It can be ‘blinded’ by heavy snows and rains. Lidar could be jammed by somebody transmitting a bright signal using the same light frequencies. And so smart cars don’t rely 100% on lidar but also use traditional cameras and sonar using the ultrasound frequencies to complement the lidar images.

Lidar is finding other uses. It’s being used, for example, in helicopters to search for things on the ground. A lidar system can spot a fleeing criminal or a lost child in the woods far more easily than older technologies or human eyeballs. Lidar can also create amazingly detailed images of anything. Archeologists are using it to create permanent images of dig sites during various stages of excavation before objects are removed. It’s not hard to think that within a few years that many traditional surveying techniques will be obsolete and that lidar will be able to locate and plot everything on a building lot, for example, down to the millimeter.

Do We Need 10 Gbps?

wraparound-glassesWe are just now starting to see a few homes nationwide being served by a 1 Gbps data connection. But the introduction of DOCSIS 3.1 cable modems and a slow but steady increase in fiber networks will soon make these speeds available to millions of homes.

Historically we saw home Internet speeds double about every three years, dating back to the 1980s. But Google Fiber and others leapfrogged that steady technology progression with the introduction of 1 Gbps for the home.

There are not a whole lot of home uses today that require a full gigabit of speed – but there will be. Home usage of broadband is still doubling about every three years and homes will catch up to that speed easily within a few years. Cisco recently said that the average home today needs 24 Mbps speeds but by 2019 will need over 50 Mbps. It won’t take a whole lot of doublings of those numbers to mean that homes will expect a lot more speed than we are seeing today.

There is a decent chance that the need for speed is going to accelerate. Phil McKinney of CableLabs created this video that shows what a connected home might look like in the near future. The home owns a self-driving car. The video shows a mother working at home with others using a collaboration wall, with documents suspended in the air. It shows one daughter getting a holographic lecture from Albert Einstein while another daughter is talking with her distant grandmother, seemingly in a meadow somewhere. And it shows the whole family using virtual / enhanced reality goggles to engage in a delightful high-tech game.

This may seem like science fiction, but all of these technologies are already being developed. I’ve written before about how we are at the start of the perfect storm of technology innovation. Our past century was dominated by a few major new technologies and the recent forty years has been dominated by the computer chip. But there are now literally dozens of potentially transformational technologies all being developed at the same time. It’s impossible to predict which ones will have the biggest influence on daily life – but many of them will.

Most of these new technologies are going to require a lot of bandwidth. Whether it’s enhanced reality, video collaboration, robots, medical monitoring, self-driving cars or the Internet of Things, we are going to see a lot of needs for bandwidth much greater than today’s surge due to video. The impact of video, while huge today, will pale against the bandwidth needs of these new technologies – particularly when they are used together as implied in this video.

So it’s not far-fetched to think that we are going to need homes with bandwidth needs beyond the 1 Gbps data speeds we are just now starting to see. I’m always disappointed when I see ISP executives talking about how their latest technology upgrades are making them future proof. There are only two technologies that can meet the kinds of speeds envisioned in McKinney’s video – fiber and cable networks. These speeds are not going to be delivered by telephone copper or wirelessly, and to think so is to ignore the basic physics underlying each technology.

Some of the technologies shown in KcKinney’s video are going to start becoming popular within five years, and within twenty years they will all be mature technologies that are part of everyday life. We need to have policies and plans that look towards building the networks we are going to need to achieve that future. We have to stop having stupid government programs that throw away money on expanding DSL and we need to build networks that have use beyond just a few years.

McKinney’s video is more than just an entertaining glimpse into the near-future; it’s also meant to prod us into making sure that we are ready for that future. There are many companies today investing in technologies that can’t deliver gigabit speeds – and such companies will grow obsolete and disappear within a decade or two. And policies that do anything other than promote gigabit networks are a waste of time and resources.

New Technologies and the Business Office

old robotI often write about new technologies that are just over the horizon.  Today I thought it would be interesting to peek ten years into the future and see how the many new technologies we are seeing today will appear in the average business office of a small ISP. Consider the following:

Intelligent Digital Assistants. Within ten years we have highly functional digital assistants to help us. These will be successors to Apple’s Siri or Amazon’s Alexa. These assistants will become part of the normal work day. When an employee is trying to find a fact these assistants will be able to quickly retrieve the needed answer. This will be done using a plain English voice interface and employees will no longer need to through a CRM system or do a Google search to find what they need. When an employee wants a reminder of where the company last bought a certain supply or wants to know the payment history of a given customer – they will just ask, and the answer will pop up on their screen or be fed into an earbud or other listening device as appropriate.

Telepresence. It will start becoming common to have meetings by telepresence, meaning there will be fewer face-to-face meetings with vendors, suppliers or customers. Telepresence using augmented reality will allow for a near-real life conversation with a person still sitting at their own home or office.

Bot-to-Bot Communications. The way you interface with many of your customers will become fully automated. For instance, if a customer wants to know the outstanding balance on their account they will ask their own digital assistant to go find the answer. Their bot will interface with the carrier’s customer service bot and the two will work to provide the answer your customer is seeking. Since there is artificial intelligence on both sides of the transaction the customer will no longer be limited to only asking about the few facts you make available today through a customer service GUI interface.

Self-Driving Cars. At least some of your maintenance fleets will become self-driving. This will probably become mandatory as a way to control vehicle insurance costs. Self-driving vehicles will be safer and they will always take the most direct path between locations. By freeing up driving time you will also free up technicians to do other tasks like communicating with customers or preparing for the next customer site.

Drones. While you won’t use drones a lot, they are far cheaper than a truck roll when you need to deliver something locally. It will be faster and cheaper to use drones to send a piece of electronics to a field technician or to send a new modem to a customer.

3D Printing. Offices will begin to routinely print parts needed for the business. If you need a new bracket to mount a piece of electronics you will print one that will be an exact fit rather than have to order one. Eventually you will 3D print larger items like field pedestals and other gear – meaning you don’t have to keep an inventory of parts or wait for shipments.

Artificial Intelligence. Every office will begin to cede some tasks to artificial intelligence. This may start with small things like using an AI to cover late night customer service and trouble calls. But eventually offices will trust AIs to perform paperwork and other repetitive tasks. AIs will take care of things like scheduling the next day’s technician visits, preparing bank deposit slips, or notifying customers about things like outages or scheduled repairs. AIs will eventually cut down on the need for staff. You are always going to want to have a human touch, but you won’t need to use humans for paperwork and related tasks that can be done more cheaply and precisely by an AI.

Robots. It’s a stretch to foresee physical robots in a business office environment in any near-future setting. It’s more likely that you will use small robots to do things like inspect fiber optic cables in the field or to make large fiber splices. When the time comes when a robot can do everything a field technician can do, we will all be out of jobs!