After years of COVID confinement, a pent-up desire for in-person music has been unleashed, and Summer music festivals worldwide have had impressive attendance numbers across all genres – from electronic, rock, pop, and hip-hop to electronic, country, jazz, and folk.
The biggest is about to take place this month: Hungary’s Donauinselfest, which is expected to draw 3 million people. Others with big numbers last year and this year include Montreal Jazz Fest with 2 million, Summerfest with 830,000, Pol'and'Rock with 750,000; Rock in Rio 700,000, and others worth mentioning like Austin City Limits, Lollapalooza, Coachella, Sziget, Mad Cool, Essence Music Fest, New Orleans Jazz and Heritage Fest, Electric Daisy Carnival, Tomorrowland, Untold Festival, Glastonbury, Primavera Sound, and South by Southwest.
Operators of course notice the huge brand-marketing opportunities presented by these massive, multi-day festivals, which is why they are sponsoring, co-branding, and providing the networks and value-add services for these and similar events.
Some examples include:
- AT&T’s Dream in Black during the New Orleans Essence Festival of 500,000+ people, and featuring the experiential Afrotropolis 3.0 activation – a “360-degree wonderland” that integrates Black culture, creativity, artistry and technology.
- T-Mobile’s upcoming iHeartRadio Music Festival and past “Posterpalooza” 3D Motion and AR Gallery created through a partnership with Google Pixel 6a and Pixel Buds Pro during Lollapalooza.
- Deutsche Telekom’s multi-country, Gen Z-focused “Summer of Joy, Youth, and Freedom” with international music program Electronic Beats and Grammy-nominated Jayda G.
- Telefónica/O2 and live entertainment giant EVENTIM partnership at Southside, Deichbrand and Highfield festivals.
- Verizon’s multi-year partnership with entertainment giant Live Nation for interactive, immersive AR experiences at music concerts across the United States.
- Vodafone UK’s huge multi-year festival partnership with Glastonbury.
As they integrate their brands with the experience of the audience, usually 18-to-35 year olds craving ubiquitous, reliable connectivity and app-driven, immersive experiences, they get a chance to expose people to new offerings and innovations. They also have a chance to build relationships with some of the world’s largest event organizers, which increasingly need networks to fuel expansive and immersive festival experiences, as well as robust internal comms for security, personnel, logistics, access control (turnstiles), and digital payments (for ticketing and food).
What’s Different About Today’s Music Festivals: Data, Data, and More Data
As these festivals grow in number and size, they exert enormous pressure on mobile networks. To keep up, operators rent, build, and haul equipment at great cost to themselves. The work that goes into erecting towers, installing antennae, transmission links, generators, petrol, and workers is tremendous, often costing operators literally millions of dollars for events that last just a few days, or sometimes, just a few hours.
To reduce the costs, operators are focusing more on real-time measures that empower them to more surgically plan and respond to real-time trends, as the event is happening, as well as soon after to better prepare for future events.
We can get an idea of the type of data demand by looking at recent examples. Last month, 3 UK’s annual Wireless Festival in London brought “treble the volume of [5G] data being used from last year,” said Chief Network Officer Iain Milligan in a recent Mobile World Live article. Where 45% of attendees last year tapped 3’s Network, this year it was 60% of the 50,000 or so attendees. To ensure a positive experience, 3 employed temporary antennas that delivered downlink rates of 53Mb/s and 23Mb/s up on 4G, and 337Mb/s down and 49Mb/s up on 5G.
Dynamic Traffic Management is Hard – Really Hard
In “static” mobile networks, the congestion normally occurs on the RF in the downlink direction. RAN schedulers quickly become saturated because they’re focused on maximizing instant spectrum utilization, and carrier aggregation makes it harder to detect the capacity of the node.
But in these huge events, the usage of the networks is very different. People shoot videos, take pictures, and go on live video calls with their friends, so upstream is in much more demand than normal. It’s not uncommon for the upstream to get congested first. And when upstream is congested, the ACK-packets for the downstream traffic are delayed or dropped, leading to an unintuitive low demand on the downstream RF.
For that reason, event congestion is very different from your normal day-to-day mobile network congestion. As such, the traffic management and level of QoE you deliver is very different for events.
What makes events even more tricky is the fact they occur infrequently. Infrequent means that RAN planning teams do not really know what to expect.
- How many people?
- Where will they be, exactly?
- What times will be the busiest?
- What will they do and how much upstream and downstream bandwidth will they consume?
These unknowns, plus the economic inability to spend a fortune on each event, make it challenging to deliver a poster child QoE experience. Events are hard.
Traffic management for music events is absolutely critical, but incredibly hard. If you don’t know the subscriber counts or what the subscribers will be doing, how do you allocate the “right” amount of bandwidth per app, or per subscriber per app? Will you have enough bandwidth for 640p video per user, or 460p?
You want to push cloud syncing of videos and images to the off-peak hours in the day, because they’re not real-time sensitive. You need your precious upstream for those hungry for real-time performance.
But what do you set the shapers to during a music event? 100 kbps? 1Mbps? 10 kbps? All the answers depend on the unknowns above. You can make some educated guesses, and you’ll likely improve the situation compared to doing nothing. But it doesn’t feel right, does it?
The Solution: Intent Based Congestion Management for Automated Optimization
Traditional congestion management is not going to work in dynamic app-driven events.
When there’s congestion in the RAN, it’s important to manage the heaviest usage in real time, before it negatively impacts a large number of users. That means optimizing spectrum utilization so you can increase the average throughput per user and reduce the number of congested cells.
At Sandvine, we enable this automation through Intent-based Congestion Management, which boasts real-time congestion detection, identifying “intent” by assigning “scores” for target QoEs across a spectrum of users and content.
By tracking RTT of every subscriber, any increases in users’ suffering are detected through Advanced Subscriber and Application Intelligence, measuring traffic volume and classifying usage across a spectrum of usage and subscribers (Normal, Suffering, and Heavy).
This solves the “what should I set the shapers to?” problem, working independently of the number of subscribers, and independently of their activities. By setting the intent for QoE and the priorities between the different application classes, the IBCM algorithm can take care of the rest.
It is recommended, however, that the IBCM be disabled for some amount of the RF, or some amount of the time, so that it’s possible to have a clear “before-and-after” comparison of what IBCM achieved. The results are typically a “night-and-day” difference, but unless there’s a control group or clear data with which to compare, it’s difficult to know what was achieved, and how to make it even better with the next event.
The IBCM solution also offers Operational Insights for Capacity Calculation and Enforcement, which calculates and enforces the Operational Capacity for congestion domains with dynamic capacities, such as Mobile cells, as shown below.
This all works toward the automated delivery of optimal App QoE through automatic enforcement of policies and dynamic allocation of bandwidth during congestion to predefined traffic classes. This is Intent Based Congestion Management, designed for the the automatic adjustment of per-category shape rates based on App QoE feedback at 2-4 minute intervals.
IBCM automatically adjusts operational capacity based on RTT feedback (received at 15-30 second intervals), squeezing low-priority categories until the next App QoE evaluation.
This feedback fosters more equitable use of resources, preventing non-critical applications, or applications that use buffers, from compromising QoE for the greater majority of users. By doing so, it ensure operators get the most efficient use of resources while delivering the best QoE to the most users.
IBCM’s intuitive dashboards visualize congestion trends over time in open (policies OFF) and closed-loop (policies ON) scenarios. This reveals the how many locations met/didn’t meet the minimum and target intent, as well as which locations were the best or worst in terms of congestion management. Geo-maps of the locations and their intent-met status offer 24-hour views of intent management, per location, by each application category.
To learn more about App QoE-focused congestion management for mobile networks, download our Intent Based Congestion Management Use Case brief and set up a demo here.
Book a meeting with us at Digital Transformation World TM Forum 2023.