Category: Articles

With companies in various sectors looking to benefit from the advantages offered by mobile private networks (MPNs), they should plan their buying strategies for these services carefully. Different requirements mean a new approach may be needed from simply buying connectivity from their traditional telecoms provider, writes Antony Savvas.

The numbers in terms of new devices to connect to IoT and the volume of the data they will generate are massive but only parts of the data and the insights held within it are valuable. The next IoT challenge therefore becomes managing devices and the data they create to generate valuable insights without the costs running away with themselves, writes George Malim.

Although later than projected, IoT connections are finally starting to ramp up in volume as the IoT industry moves from trials and pilots to real world deployments at scale. However, the proliferation of connections is only one part of an IoT solution. Alongside huge numbers of connections come huge numbers of IoT devices and these devices will generate data at hyperscale. Organisations making IoT deployments therefore have to prepare in terms of device and data management if they are to succeed in the mass IoT market

Hima Mukkamala, the senior vice president and general manager of IoT Cloud Services at Arm, tells George Malim that device management is critical for organisations that deploy IoT devices, collect their data onpremises or in the cloud, and analyse it for business use. However, as device volumes increase and the sheer diversity of IoT applications and devices fragments the landscape, IoT device management is becoming far more complex than the traditional discipline of enterprise IT device management. What’s needed are a set of tools, processes and disciplines to manage the volume and variety, while also ensuring ease of use, validity of data and security.

Security starts even before establishing the root of trust to secure devices and the data they generate, store and transmit from the chip right through to data hitting the cloud, writes Annie Turner.

The consensus on the best way to manage IoT device data has flipped. Advocates for managing the information on computers in-house have lost their majority in a massive swing in consensus. The conventional wisdom about cloud management has changed from why to why not, writes Nick Booth.

Potentially billions of IoT devices have to be securely deployed and managed from the chip right through to the data, whether that’s on-premise, at the edge or in the cloud. Antony Savvas explores device management throughout the device lifecycle.

As IoT matures and the numbers of connected devices start to soar from a relatively low level into the billions, the greater challenge for organisations employing IoT could be more in managing the device data than in managing the devices themselves. If there are billions of devices there will be trillions of data points transmitted on a daily basis. George Malim explores how all of this will be managed from the chip on the device through to the cloud, edge or onpremise data processing capability.

Edge intelligence is being trumpeted as the next big step in enabling IoT but definitions of the edge are nebulous and the current base of deployed devices are dumb and inflexible. George Malim goes closer to the edge to understand how greater intelligence will open up new opportunities.

A few years ago, it was fashionable to argue that all IoT data must end up in the cloud and that all the really smart stuff was therefore in the cloud. This was a throwback to machine-to-machine (M2M), when we expected data from all connected devices to be sent to a central server for processing and subsequent distribution of the information created.

Prasad Kandikonda is the vice president of engineering at MultiTech. His team has recently developed the company’s mPower Edge Intelligence embedded software that adds to its application enablement platform to bring new programmability, enhanced security and ease of management to large-scale deployments at the edge. The software is network-technology agnostic and means organisations can add more intelligence at the edge, enabling more decentralised decision making, he tells George Malim.

Networks can call on a growing armoury of connection technologies, but there’s another revolution happening too – a much greater role is emerging for data processing at the network edge than was envisaged for the Industrial Internet of Things (IIoT). Jeremy Cowan reports.