Back in 2009 just before the Internet of Things became Connected Living, it was called M2M Machine to Machine and we were discussing it within Industry meetings. We discussed all the issues below and what might become of this new technology. Now these issues are in the public eye, what will Operators do now that they look like a reality.
IoT traffic volumes can put mobile networks at risk
A digital transformation is now underway, which is impacting the way we live our lives. As the “Internet of Things” becomes more prevalent, communications capabilities will be extended to billions of objects making signaling traffic a potential bottleneck.
IDC forecasts that the worldwide market for IoT solutions will grow from $1.9 trillion in 2013 to $7.1 trillion in 2020. The number of cars connected to the Internet worldwide alone will grow more than sixfold to 152 million in 2020 from 23 million in 2013 according to IHS Automotive. Highly automated and autonomous driving vehicles from Audi, BMW and Mercedes-Benz were demonstrated at the Consumer Electronics Show in Las Vegas this year. Tesla’s cars are already able to receive data from headquarters, act on instructions and upgrade entertainment, engine and safety capabilities in real time.
Congestion from inefficient messaging
IoT requires that each device send small amounts of data periodically. When each of these signaling messages are added up and multiplied by the number of devices, the impact on network congestion is even more than the increase in data traffic.
Network applications need to communicate with their devices to determine network status, including key information on which parts of the network are congested, the location of the device, wake-up times and who has authorized access. The level of messages can result in an inefficient use of resources in both the network and the device, for example:
• Push notifications can be sent to a large number of devices within a small time window, creating huge spikes in signaling load.
• Devices can send frequent “keep alive” messages just to ensure the network address translation port remains open.
• Devices can ping the network every few minutes when unable to connect to the application server.
When each of these inefficiencies is multiplied by millions of devices, the extra load on the network can have a negative impact on the subscriber quality of experience.
There are several different approaches for addressing increased traffic loads as a result of IoT. One solution is to develop a separate, different kind of network that can send tiny messages across a low-power, wide-area network. For example, San Francisco is set to get a new cellular network later this year designed exclusively for devices provided by French company SigFox. However, creating a separate network is extremely expensive, and outside of major cities is not always a viable option.
A less complicated and probably less costly approach would be to schedule on the same network when transmissions occur to avoid traffic spikes. For example, some applications, such as smart meters and vending machines, have very flexible communication requirements and their transmissions can be scheduled for off hours, while other applications, such as security systems and health care, can always have network access. The following schedule, for example, could help control signaling congestion:
• Water meters – 1 to 2 a.m. in increments of minutes.
• Gas meters – 3 to 4 a.m.
• Waste receptacles – 4 to 5 a.m.
• Home security devices – whenever necessary.
However, this approach would require the operator to communicate with all of the sources of IoT data and then have them all agree to a schedule, which is highly impractical.
The best option is to support more intelligent signaling to reduce congestion. With this approach, inefficiencies with signaling can be eliminated by streamlining and orchestrating the data traffic to reduce the number of signaling messages. The sending of unnecessary data control messages can be managed or delayed until there is a more opportune time for transmission.
Here are some examples of how signaling can be tweaked to improve network performance:
• Data control messages can be delayed, queued and then transmitted in batches.
• Repeated data can be identified and piggybacked to prevent the need to create and tear down multiple messaging sessions.
• Signaling messages can be balanced over time to prevent bursts.
These optimization techniques can reduce data signaling events by up to 15%, reduce RF load and save battery life. By influencing traffic flows at the network core the increased efficiency is automatic and all signaling traffic is optimized.
Optimizing signaling transmissions could help ensure IoT won’t cause mass disruption to the network, lead to a diminished quality of experience for network subscribers and a potential loss in revenue and reputation for operators. With legislation like the current European Union directive requiring all cars to be connected, IoT will most likely become a reality that operators will need to manage, and orchestrating at the core could be the most practical solution.
Source: RCR Wireless