Covid Will Not Change Longer-Term Bandwidth Growth Patterns

One often hears it said that “broadband usage in 2020 rose 50 percent.” The implication is that Covid explains the change. Covid did cause a shift of consumption from office to home; from school to home; from downtown office cores to suburban homes. Home all day, gaming and video content consumption spiked. 

The issue is what happens once people are able to work substantially “at the office” again. By definition, students in school and not at home will not be playing videogames. Workers at their offices will not be watching streaming video while at the office. Work and educational traffic will shift back to school and work sites. 

Beyond some permanent changes in the balance of in-office and at-home or remote work environments, the longer-term consumer bandwidth consumption trends are mostly unchanged. 

There was an immediate step change when workers and students were kept home. But the long-term growth rates seem to have settled back to where they were before the sudden step change. 

source: Chief Martec 

That might come as a surprise, given the 25-percent to 40-percent boost in traffic caused by stay-at-home policies, in the spring of 2020, for example. 

But analysts at TeleGeography have argued the temporary change in bandwidth demand caused by stay-at-home policies will not persist. Usage levels will return to prior pre-pandemic patterns. 

Many argue that “Covid caused a year’s worth of change in a month.” But that is not the same as arguing that the rate of change is permanently altered. 

The point is that consumer data consumption routinely grows 25 percent to 50 percent per year, driven by streaming video consumption. For more than a decade, entertainment video has been the key driver of consumer bandwidth demand. In 2008, for example, video represented 99 percent of data consumption by consumers. 

Today, content consumption still is the main driver of consumer bandwidth consumption. Consider that the “average” household now subscribes to four different video streaming services. Video is far and away the most bandwidth-intensive application, so the shift to video streaming (in advance of potential widespread use of virtual or augmented reality for gaming) determines consumer bandwidth demand. 

source: Deloitte 

To be sure, consumers are connecting more devices to the internet, adding to bandwidth demands. Still, video consumption continues to drive bandwidth demand. Also, the number of users in each household also matters. But household size--on average--does not change much, year over year.  

source: Deloitte 

The reason video drives bandwidth is simply that it is the most bandwidth-intensive application. By some estimates, where voice might earn 35 cents per megabyte, connectivity providers might earn a fraction of a cent per megabyte for all other internet apps and streaming, based on the purchase of the internet access service. 

The exception is that connectivity providers who own a streaming service can monetize subscription or advertising revenue. But most internet service providers earn money only on the access subscription fees. As usage climbs while subscription fees remain relatively constant, revenue per bit falls.  

The point is that Covid-induced changes in bandwidth consumption are likely transitory, beyond a step change in consumption caused by “stay at home” policies. 

As people go back to school and back to the office, reversion to mean should occur. More traffic from school and office sites will occur, with less consumption during school and working hours at home locations. 

Yes, bandwidth consumption will keep rising, and likely at rates we have seen over the past two decades. Covid distortions will be transitory, temporary and ultimately represent “noise” in consumption curves, not a change of the curves.

Why Data Consumption Forecasts So Often are Wrong

Bandwidth planning has become a tricky business since data traffic completely displaced voice as the driver of consumption. Not only is demand more variable and uncertain, growth is more dynamic, by an order of magnitude or two.

That raises an obvious question for mobile service providers: how much bandwidth do they need to be ready to supply to customers? The question might be easier to answer if demand were not if end user demand was predictable, but demand is not predictable. Sometimes growth is "only" 40 percent a year; sometimes it is higher.

Some might say, for example, that over the past year, AT&T has revised its own forecasts of bandwidth consumption in significant ways.

In a March 2011 presentation AT&T projected that data volumes would grow by eight to 10 times between the end of 2010 and the end of 2015.

That forecast appears to be based on an expectation that volumes would roughly double in 2011 and then increase by a further 65 percent in 2012.

Consider this 2008 forecast, which presents a not-unusual rate of growth in potential speeds, which has a direct bearing on consumption, since faster speeds tend to be associated with higher consumption.

Keep in mind that access speeds are different from consumed gigabytes. But the former drives the latter. And nobody currently predicts anything but a continual shift to higher potential access speeds on fixed and mobile networks.

Instead, AT&T now seems to be seeing 40 percent annual growth. Now, 40 percent annual growth is significant. It means bandwidth consumption doubles about every two to three years.  But annual bandwidth growth of 50 percent a year would be well within historical ranges, on an aggregate basis, in terms of long-haul bandwidth consumption. But policies and end user behavior can change the demand curve.

The most-recent AT&T forecast would mean that data volumes would increase by five to six times by 2015. Whether that means existing spectrum, and newer methods for handling traffic using that spectrum, are sufficient to handle future growth is debatable. Some might argue additional spectrum is not required.

Others might say the possible growth of between 500 percent and 1,000 percent, in just four years, is challenging enough that additional spectrum is likely to be needed, especially if the higher range of growth turns out to be the case.

Network planners might point out that supplying additional bandwidth takes prodigious amounts of capital and significant time.

Some might speculate that AT&T’s forecasts about data growth have changed because supplier policies and end user behavior have changed.

Perhaps users have become quite sophisticated about offloading their data usage to Wi-Fi, as service providers have been urging them to do.

Or, perhaps the heaviest users, with "prodding" from the carriers, are modifying their own behavior. Why it is so hard to make accurate bandwidth forecasts

Some observers would not be sanguine about moderating rates of bandwidth consumption. It is true that carriers can provide incentives and dis-incentives for consumption. But it also is the case that video consumption keeps growing, and it is video that drives bandwidth demand.

Video Represents 99% of Consumer Information Consumption

Reduced to bytes, U.S. consumers in 2008 imposed an information transfer "load" of about 34 gigabytes a day, say Roger E. Bohn, director, and James E. Short, research direction of the Global Information Industry Center at the University of California, San Diego. That works out to about seven DVDs worth of data a day.

And that isn't even the most-significant potential implication. We are used to hearing about consumption of media or information in terms of "time," such as hours consumed each day. But Bohn and Short also look at information flows in terms of "bandwidth."

If one looks at consumption based on the "hours of use," video accounts for possibly half of total daily consumption.

If one looks at the flows in terms of compressed bytes, or actual bandwidth required to deliver the information, then video represents 99 percent of the flow volume.

That has huge implications for the design of any nation's communications and "broadcasting" networks. To the extent that virtually all information now is coded in digital form, a shift of consumption modes (from watching linear satellite, cable or telco TV to Internet delivery) can have huge effects.

Recall that video bits now represent 99 percent of bandwidth load. But also note that most of that load is delivered in the most-efficient way possible, by multicasting a single copy of any piece of information to every potential consumer all at once. It requires no more bandwidth to serve up an event watched by 500 million people than one person.

That is why video and audio networks historically have been designed as "mutlicast" networks. They are the most effiecient way of delivering high-bandwidth information.

If more video starts to move to Internet delivery, the bandwidth requirements literally explode. To deliver one identical piece of content to 500 million Internet users requires 500 million times as much bandwidth as the "old" multicast method, in at least the access link. If network architects are ruthlessly efficient and can cache such content at the edge of the network, wide area bandwidth consumption is reduced and the new load is seen primarily on the access networks.

All of this suggests a rational reason for maintaining "multicast" video entertainment networks, and not shifting all consumption to unicast Internet delivery. It is extremely inefficient and wasteful of network resources. To the extent that much "on demand" viewing of popular professional content can be satisifed by local storage (digital video recorders), this should be done.

On-demand viewing of YouTube content is harder to rationalize in that manner. For the same reason, local storage of computer games, where possible, makes sense. Interactive, "live" gaming does not allow such offloading, and will contribute hugely to Internet bandwidth demand, just as viewing of YouTube videos is doing.

“Information," representing flows of data delivered to people from 20 sources, is likely to be much higher the next time the researchers replicate the study, because television, which accounts for nearly half of total consumption, now has shifted from analog NTSC to high-definition, which imposes a greater information load.

Television consumption represents about 41 percent of the daily consumption, but computer and video games represent 55 percent of the flow. Add ratio and TV and those two sources represent 61 percent of the flow.

But there is another important implication: the researchers counted "compressed" information, or "bandwidth," in addition to more-familiar metrics such as hours of consumption.

Looked at in this way, the researchers say, "led to a big surprise." In fact, only three activities--television, computer games and movies account for 99 percent of the flow. All other sources, including books, mobile or fixed voice, newspapers, radio or music, contribute only one percent of total load.

The researches also point out that they count bytes as part of the  "information flow" only when users actually consume the information. Data stored on hard drives or TV or radio signals not being watched or listened to does not count in the research methodology.

The researchers also point out that if “personal conversation” is considered a source of information, then high-quality "tele-presence" applications that actually mimic talking to a person in the same room would require about 100 Mbps worth of communications load.

Three hours of personal conversation a day at this bandwidth would be 135 gigabytes of information, about 400 percent more than today's average consumption.

Unicast Video Accounts for Most of the Internet Bandwidth Increases We See

Constant and significant increases in bandwidth consumption are among the fateful implications of switching from linear TV broadcasting to multicast video streaming. Consider that video now constitutes 52 percent to 88 percent of all internet traffic. 

Not all that increase is the direct result of video streaming services. Video now is an important part of social media interactions and advertising on web sites supporting consumer applications, though some studies suggest social media sites overall represent only seven percent to about 15 percent of video traffic consumed by end users. 

Also, there is some amount of internet video traffic between data centers, not intended directly for end users, possibly representing five percent of global internet traffic. 

Study	Date	Video Traffic Share (%)
Cisco Annual Internet Report (2023)	Dec 2022	88%
Sandvine Global Internet Phenomena Report (Q3 2023)	Sep 2023	83%
Limelight Networks State of the Real-Time Web Report (Q3 2023)	Oct 2023	76%
Ericsson Mobility Report (Nov 2023)	Nov 2023	72%
ITU Global Video Traffic Forecasts	Feb 2023	70% (2022)
Ookla Global Video Report (Q2 2023)	Aug 2023	65%
Akamai State of the Internet / Security Report (Q3 2023)	Oct 2023	60%
Statista: Global Internet Traffic Distribution by Content Type (2023)	Oct 2023	58%
GlobalWebIndex Social Video Trends Report (Q3 2023)	Sep 2023	55%
Juniper Networks Visual Networking Index (2023)	Feb 2023	52% (2022)

Ignoring for the moment the impact of video resolution on bandwidth consumption (higher resolution requires more bandwidth), the key change is that broadcasting essentially uses a “one-to-many” architecture, while streaming uses a unicast architecture. 

The best example is that a scheduled broadcast TV show, for example, can essentially send one copy of the content to every viewer (multicast or broadcast delivery). The same number of views, using internet delivery, essentially requires sending the same copy to each viewer separately (unicast delivery). 

In other words, 10 homes watching one multicast or broadcast program, on one channel, at one time consumes X amount of network bandwidth. If 10 homes watch a program of the same file size as the broadcast content, whether simultaneously or not, then bandwidth consumption is 10X. 

There are some nuances for real-world data consumption, such as the fact that consumption of linear video is declining or the fact that broadcasting uses a constant amount of bandwidth, no matter how many viewers in an area might be watching or not watching. 

Study	Comparison	Bandwidth Ratio (Streaming/Broadcasting)
"A Comparative Analysis of Video Streaming and Broadcasting for Live Sports Events" (2023)	Live sports streaming vs. multicast	10x - 15x
"Bandwidth Efficiency of IPTV vs. Traditional Broadcasting" (2022)	IPTV unicasting vs. terrestrial broadcasting	2x - 4x
"The Impact of Unicast Video Delivery on Network Traffic" (2021)	Unicasting video vs. multicast video	1.5x - 3x
"Comparing the Bandwidth Consumption of Live Streaming and P2P Delivery" (2020)	Live streaming vs. P2P for live events	3x - 6x
"The Bandwidth Efficiency of Video Streaming Protocols" (2019)	HTTP streaming vs. RTMP streaming	1.2x - 2x
"A Study of User-Generated Video Delivery on Social Media Platforms" (2018)	User-generated video streaming vs. traditional video streaming	2x - 4x
"The Bandwidth Implications of 4K and 8K Video Streaming" (2017)	Higher resolution streaming vs. standard definition	4x - 8x
"The Impact of Mobile Video Streaming on Network Congestion" (2016)	Mobile video streaming vs. fixed-line streaming	1.5x - 3x
"The Future of Video Delivery: A Cost Comparison of Streaming and Broadcasting" (2015)	Streaming vs. broadcasting for future content delivery	2x - 4x
"The Bandwidth Efficiency of Video-on-Demand Services" (2014)	Video-on-demand streaming vs. linear broadcasting	1.5x - 2.5x

There are other nuances as well. Since a broadcast video stream often is viewed on a television set, it is possible that multiple viewers “share” viewing of the same content. If one TV is receiving a program, and five people are watching, the “single delivery” supports five views. 

On a “per viewer” basis, X amount of delivery bandwidth is X/5 for each viewer of the same program. 

If five people watch a program of equivalent file size at the same time, data consumption is 5X. 

Study	Year	Methodology	Streaming Bandwidth (Mbps)	Linear Broadcasting Bandwidth (Mbps)
Nielsen	2022	Network traffic analysis	3.1-4.7 (average)	0.1-0.2 (average)
OpenVault	2023	ISP data analysis	1.8-2.5 (average)	0.05-0.15 (average)
Pew Research Center	2021	Survey and network analysis	2.3-3.8 (average)	0.1-0.2 (average)
University of Zurich	2019	Network monitoring and simulation	2.0-3.5 (average)	0.08-0.18 (average)
Akamai	2020	Global traffic analysis	1.6-2.8 (average)	0.04-0.12 (average)
Sandvine	2022	Network traffic analysis report	3.5-5.0 (peak)	0.15-0.25 (peak)
Netflix	2021	Open Connect content delivery platform report	0.5-1.5 (average)	N/A
BBC Research & Development	2018	HbbTV hybrid broadcasting analysis	1.0-2.0 (combined)	0.03-0.08 (combined)
Bitmovin	2023	Video encoding and delivery technology report	0.8-1.8 (efficient encoding)	N/A
Ericsson	2022	Mobile network video traffic report	0.5-2.0 (mobile average)	N/A

The point is that the shift from broadcasting (multicasting) to unicast entertainment video was destined to dramatically increase internet data consumption.