The Smart City Networks Of The Future
By Christian Mildner
What will the smart city networks of the future look like?
Increasing internet connectivity capabilities are transforming modern cities, creating unprecedented opportunities. It is easier than ever to monitor infrastructure and industrial assets through sensors, and thanks to the connectivity that links them to remote applications, a wealth of third-party data and service integrations can be leveraged.
Many types of wireless connectivity protocols and networks exist. They differ by how much bandwidth is used, how long battery-powered devices last, and more broadly the performance, scalability, reliability and interoperability of networks and connected devices. All of this ultimately determines the total cost of ownership, which can vary widely between different options.
Technology is developing rapidly too, and requirements for smart city networks constantly evolve. Therefore, it is important to consider the future capabilities of networks and connected devices, as well as evolving city needs, to plan ahead and to future-proof investments.
IoT networks follow 2 major topologies, the so-called “star” or “mesh” topology.
In a star network, all end devices orbit central networking infrastructures, such as access points or base stations. The end devices do not ever communicate directly with each other, speaking instead directly to the network infrastructure or cell tower. Typical star network protocols are Wifi and LTE. For industrial and smart city applications, LoRaWAN and cellular NB-IoT/Cat-M1 are popular protocols.
Star networks tend to be cost-effective and quick to deploy and they provide effective and efficient 2-way communication between the end devices and a central platform/application. This is sufficient for many of today’s applications, which tend to connect smaller numbers of relatively simple devices, which collect and send small amounts of data.
In a mesh network, each device can speak to its neighbours, which allows its messages to travel long distances by hopping between each node in the network. When deployed with sufficient density, mesh networks will provide multiple paths from the end-device to an access point, or gateway, which will connect to a backhaul network to send the data to a central management system. Typical mesh network protocols are ZigBee and Thread, and for industrial and smart city applications in particular, WiSUN is a popular protocol due to its scalability, reliability and security.
Enterprise-grade mesh networks have the capability to scale rapidly because each additional device strengthens the mesh and makes the network more powerful and resilient. Mesh networks can also self-heal and self-optimize in response to changes in the environment and network topography.
As such, both network types have their unique characteristics and are suited for different use cases, but it is only with a keen eye on future trends that the right choices can be made today.
The rise of Edge Computing
One such trend to watch is edge computing, a concept that broadly refers to pushing the “smarts” to the edge of a network, distributing intelligence across connected devices and networking equipment, which are often referred to as “network nodes”. With network nodes becoming smarter and more powerful, e.g. through embedded processing power and data storage, more computing and data processing can be done on the networked devices to determine when and if data needs to be uploaded to a more central location.
Edge computing puts the smarts to process data closest to the devices that collect and transmit it. This vastly reduces the amount of data that needs to be stored and sent to a central data centre, saving not only network bandwidth, which becomes increasingly scarce and costly, but also computing resources allocated unnecessarily in the main data centres. The further out on the network edge data can be turned into useful information, the easier and faster that information can be applied to the environment where it matters most.
Circling back to the network types, star and mesh, in mesh networks the devices can exchange data directly with each other. In the context of edge computing, this capability provides significant benefits to not only process data at the edge, but also to aggregate and interpret information at the device level and to trigger direct responses when devices send instructions and commands to one-another, enabling more efficient real-time applications.
Over time, the processing of data at the edge will be further enhanced by artificial intelligence applications running on networked devices. They will significantly increase the capability of networks to interpret data at the device level and to define and trigger actions, improving “direct response” capabilities.
Importantly, edge computing does not only reduce the need for central processing power, but in turn also reduces the reliance on cellular backhauls to connect networks to data centres, making them more resilient, especially during times of emergency such as extreme weather events.
The smart city networks of the future
There is no “one size fits all” when it comes to smart city networks. Most use cases and applications have their own unique set of network-related requirements and commercial considerations, such as cost and speed of deployment.
Several different networks will likely co-exist in cities and be used for different use cases as needed, with some networks dominating others over time as needs and technologies evolve.
The same devices will be connected on different networks depending on the specific use cases they serve, and the more intelligent devices of the future will be able to switch between networks based on their connectivity needs in real-time, for example when they shift from catering for one use case to another. This concept of software-defined networking is supported by several new standards that are being developed and alliances that ensure inter-operability between smart city and IoT networks, connected devices and data platforms, e.g. TALQ and uCifi.
With the rise of artificial intelligence, connected devices becoming ever smarter and more powerful, and with many new use cases and applications requiring real-time data processing, the demand for edge-computing capabilities in smart city networks will substantially increase. These capabilities are greatly enhanced when devices can communicate directly with one another and the networks of the future will increasingly facilitate device-to-device connectivity.
At some point in the future, cities might even deploy smart networks with enough edge computing capabilities and artificial intelligence baked into the networked devices to run themselves – with no or only very little need for central processing power and a central management system.
However, as is the case with many new trends and technologies, solving one problem can create others. From a security standpoint, data storage and processing at the network edge can be troublesome, especially when it is being handled by different devices that might not be as secure as a centralised or cloud-based system. Therefore, with the rise of edge computing, the security, reliability and resilience of networks are becoming ever more critical.
Finally, future smart city networks will need to be based on open standards and protocols. This is important to support and foster partner ecosystems that develop compatible and interoperable solutions with seamless connectivity, including devices with embedded edge computing capabilities and distributed intelligence and AI applications. For a city, a vibrant and mature ecosystem around the technology it deploys prevents vendor lock in, ensures long-term support for the technology and provides ongoing access to innovative solutions and services.
Written by Christian Mildner
Solutions Architect SCS