Edge assurance and authentication solutions offer reduced network CAPEX investment, optimised service performance, and new monetisation opportunities.
The era of edge computing
The launch of advanced 5G networks is enabling the evolution of Mobile Edge Computing (MEC) – also becoming known as Multi-access Edge Computing (MEC) – which allows operators and service providers to use computing resources, such as edge servers, sensors and even AI capabilities, at the edge of the network, avoiding the need to use core network infrastructure and resources.
This has numerous benefits. For one thing, by positioning distributed computing resources closer to the source of demand, which means traffic does not need to traverse through the core network enabling new low latency use cases, such as industrial IoT and autonomous vehicles, to be delivered. Similarly, new QoS control can also be enabled for traditional services, such as video streaming. Furthermore, new services can also be enabled – a point to which we shall return.
However – and crucially for network operators - it also unlocks the potential to reduce investment in the 5G core. By controlling traffic at the edge and routing according to different criteria, less will flow to the core – reducing the need to provide core resources.
Validating identity and authenticating at the edge
Of course, this means that issues of identity and authentication assumes greater importance. For many applications, validation needs to take place at the edge, while for others, it makes sense to move to the edge so that new data can be taken into consideration.
For example, as devices use resources at the edge of the network, these MEC resources must also therefore be able to validate identity – i.e. does this device belong to the right user? Similarly, there’s the potential to authenticate other kinds of transactions and permit service access.
And, we also need to assure the edge, through efficient monitoring and the optimisation of service performance and delivery… again, without using core network resources. This will extend to network resources, edge computing services, IoT and, in time, AI capabilities, while ensuring identity validation, and service performance.
Complex mix of edge services
In complex scenarios, edge computing may need to ensure the identity, validity and performance of IoT, smart city and autonomous vehicle applications, some of which are likely to be critical in terms of low-latency network and processing response times – arguably, the “raison d’être” of edge computing. But, simpler applications can also be enabled – and can be compelling. Not only validating devices, but also transactions and identity can be moved to the edge, bypassing core resources.
This can apply to something as commonplace as a credit card transaction, as well as the subscription status for a user who is accessing, for example, Netflix or Disney Channel – all while ensuring that performance and QoE levels are optimised by managing network resources. Similarly, these sessions will need to be timed, billed and paid for where appropriate. So how can operators and service providers ensure edge assurance and service performance for such a complex mix of products and services?
More effective monetisation with metadata
Tambora’s ‘state machine’ obtains data from mobile devises that can be correlated with consent from mobile network elements, in the control plane, such as HSS/OSS/BSS. It also delivers metadata for third party applications over standard API. The metadata can then be used for external authentication and validation – which means third-party service providers (for example, banks), can check user and customer actions in real-time. The metadata available covers subscribers, applications, network resources, and devices, ensuring an end-to-end, single view of each network session.
It can also be used to support edge assurance capabilities. By reporting key data, actions can be taken to ensure that SLA and performance requirements are met. With new enterprise customers critically dependent on MEC capabilities, ensuring that the target KPIs and performance requirements are delivered will be of fundamental importance. So, collecting key data from devices in the RAN is essential to provide a complete picture.
Tambora’s state machine solution gathers data through query and response. The data is correlated multi-dimensionally, and the state change of data over time is captured and analysed. As such, applications include identity validation, location-based services and data-driven advertising. Our reference architecture and standard interfaces also simplify data mining, analytics and presentation.
Support new business relationships
Some of the parameters covered by the Tambora solution, include (for subscribers) Session identity and Customer ID; (for applications) QoS/QoE and Application details/Web behaviour; (for the network) RAN details, Network QoS and Billing details; and, (for the device) Identity of mobile device, Location, and Tools and Capabilities. This data can then be used to analyse and optimise internal processes, or be shared – through APIs –with external systems and business customers, allowing service providers to support new business relationships with other partners.
Put simply, it enables MNO to better monetise their data, while supporting internal processes to ensure optimal end-user QoS/QoE. In short, there’s a multitude of use cases and applications that can be served by deploying Tambora’s solution – from new monetisation opportunities, as well as cost reduction through reducing dependence on core resources. Get in touch
to find out how Tambora can help you to reduce CAPEX, optimise internal processes and services, and support new business relationships and opportunities.