Why data storage isn’t a ‘one size fits all’ solution for IoT
Behind the complex network of connected technologies and devices, which makes up the Internet of Things (IoT) landscape, lies a similarly large and sprawling network of data infrastructure. The amount of data produced by the IoT correlates to the large-scale growth that this segment is experiencing. Whilst capturing data is a key part of the process, so is ensuring it can be stored, accessed, and transformed into valuable insights. As data is the largest and most unique resource in each IoT application, enterprises must pay attention to how to store it appropriately to get maximum value from it.
The purpose of IoT applications differ – from security systems to automated supply chains to medical wearable devices – and so do their demands. Therefore, there must be a comprehensive architecture at each junction that can accommodate an extensive range of demands and requirements. Without storage solutions that cater to specific demands, it is impossible to realise the full potential of IoT data. The following storage properties demonstrate why storage solutions must be specific and tailored.
To get the most value out of connected technologies, it is crucial that some of the data is retained and stored on a long-term basis. Often this data is used to identify daily, monthly, and yearly trends, meaning that whilst it might not need to be analysed immediately, it’s very important that it is stored reliably and securely.
‘Cold’ storage plays a key role here. Cold storage is for data that is accessed occasionally, and it is more economical to store it on a lower cost medium such as an HDD, compared to live, ‘hot’ data that needs to be accessed frequently, and stored on SSDs. As the amount of data is ever increasing, it’s becoming necessary to store higher amounts of it in cooler storage tiers until needed.
A key example where long-term retention is a priority is for medical devices, such as those that track sleep patterns, daily movements, or nutrition and blood oxygen levels, to identify opportunities to improve health habits.
Durability and resilience
Certain storage solutions are designed with the properties of endurance and resilience at the forefront. These offerings, including the highly reliable and industrial-grade e.MMC (embedded Multimedia Card) and UFS (Universal Flash Storage) embedded flash drives, can endure harsh environments, including those with extreme temperatures or vibrations, such as in a factory setting.
One common use case that requires such solutions is in industrial-use drones. These drones, for example, are used by oil-rig workers to complete inspections more quickly and without risking worker safety. Similarly, search and rescue drones require high-performance in varying environments, such as those with fluctuating and extreme weather patterns.
Low latency at the edge
One way to achieve low latency is to bring compute and storage nearer to the place it is used, like the network edge, or to devices closer to the edge. This helps enable rapid real-time data transfers and analysis at the edge, where low latency is a fundamental requirement.
Smart cities, for example, use and act on real-time data. Emergency services can communicate with traffic lights to synchronise and provide quicker and more direct access to critical locations whilst holding traffic at bay. Smart parking systems allow customers to find available spots faster in crowded garages in real-time.
Likewise, smart retail can be enabled by monitoring activity such as in-store shopper foot-traffic, which can provide insights about the impact of store displays, or bolster growth strategies based on the purchase history of customers. Getting access to real-time consumer behavioural data will result in enhanced in-store customer experiences.
To benefit from low latency and real-time data, data storage considerations must be made in advance.
Specialised storage architecture
In summary, there are various storage characteristics that can best support different IoT use cases. Selecting the right storage is critical in order to create optimum value from IoT data.
When the requirements for different applications diverge so much, a standard, general-purpose storage solution is no longer sufficient. One size does not fit all.
To take maximum advantage of the evolving IoT landscape and transform data into powerful and valuable insights, a data storage strategy must be devised and purpose-built architectures for specific use cases must be considered and correctly deployed. Delays in moving from general-purpose to purpose-built storage risks losing out on the value of data, by failing to store and preserve it sufficiently.
This article originally appeared on information-age.com, to read the full article, click here.
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