The Internet of Things, or IoT, is the new frontier in app development. Although some IoT devices and apps, like smart thermostats and connected cars, are already in production, they represent only the tip of the iceberg. More diverse types of IoT hardware, and more complex software to power them will emerge as the IoT continues its projected 285 percent growth rate over the next several years.
A bigger, more diverse IoT presents new challenges to developers in several respects. One of the biggest is in the realm of data syncing. How can programmers ensure that IoT devices and apps share data effectively in real time? What will it take to keep data syncing efficient, reliable and private on IoT devices with minimal resources?
This article explores these questions in order to help developers understand the special data syncing challenges to which the IoT gives rise, and how programmers can respond to them.
What makes the IoT special
To understand the special challenges that arise when syncing data across the IoT, you first need to understand what makes the IoT fundamentally different. On this topic, consider the following points:
- IoT devices may have intermittent connectivity: Some IoT devices, such as sensors connected via long-distance wireless networks that are subject to interference, are not going to be connected to the network constantly. That makes uniform data syncing across all devices difficult.
- IoT devices may have minimal resources: The compute and storage power of many IoT devices will be extremely small. That limits their ability to “think” on their own, and makes them more dependent on servers to process and store data.
- IoT devices have limited power supplies. IoT devices may be powered by batteries, solar panels or other finite power sources. This characteristic places a premium on efficient energy use.
- IoT devices are numerous: The IoT will force networks and the data they transport to scale on a whole new level. The IoT is projected to expand at an average rate of about 23 percent per year through 2021, which means vast increases in the number of devices generating data.
It’s worth pointing out, too, that the IoT devices that have hit the market so far do not fully represent what the IoT will become. To go back to the examples of smart thermostats and connected cars, these devices do not push the boundaries of what the IoT is about. To prepare fully for the IoT revolution, developers need to bear in mind that they will be writing software for IoT devices that are less connected, much smaller and more numerous than the IoT hardware that has debuted to-date.
Strategies for handling the IoT deluge
How can developers respond to the special data syncing challenges that affect IoT devices and apps? Here are some high-level design strategies that can help:
- Prepare for massively distributed networks. Traditional networks are designed according to a client-server model. Network configuration is poised to look very different on the IoT, however. Instead of having centralized servers to store data and distribute it to client devices, the IoT will be composed largely of many tiny, low-power devices. In many cases, those devices will need to maintain state in realtime without the assistance of centralized servers. Developers should therefore leverage streaming and syncing platforms like deepstream to power massively distributed networks.
- Push streaming data out to devices: The low compute resources of IoT devices mean developers should design software running on a device to do as little as possible. One way to minimize load is to stream data to devices from a server, like deepstream, in a way that does not require the device to do anything other than receive that data. In other words, don’t make the device decide whether it needs to sync; design your server and client software so that all the thinking and data pushing takes place on the server side. Deepstream handles these processes for you.
- Tolerate unsynced data: Data syncing software needs to be able to support IoT devices that are intermittently connected, and are therefore unable to sync at the same time as other devices on the network. One way to do this is to require that when apps for IoT devices come back online, they sync before performing any other operations. This is another task that deepstream handles automatically.
- Sync data in real time: The more devices you have on your network, the greater the difficulty of keeping them synced. As a technology designed for real-time syncing on a massively distributed network, deepstream comes in handy here, too. It enables real-time syncing even on networks with very large numbers of devices.
- Use power efficiently: Because IoT devices may have limited power, developers should use that power efficiently. One way to do this when syncing data, which Yasser Fadi discusses in greater detail here, is to adopt a “push” paradigm. This approach avoids data transmissions unless they are explicitly necessary. Fewer transmissions mean less power consumption. Of course, in order to keep data in sync, you need to make sure that syncing occurs in real time when it is necessary. That, again, is what deepstream enables you to do.
The precise strategies that programmers should follow when writing an IoT app will vary according to the particular needs of the hardware and software they are working with, of course. The IoT is a wildly diverse ecosystem, and a range of different data-syncing solutions are bound to emerge out of it as it continues to evolve.
But if one thing is certain as the IoT continues to develop, it’s that programmers can’t count on traditional data syncing strategies to work in all IoT contexts. It’s time for them to start thinking now about alternatives tailored to the IoT.