At Spry Fox Networks, we are excited to announce the reference translation function implementation for the CAMARA Quality on Demand (QoD) API subproject. We are proud to be associated with the CAMARA community and are excited to further contribute by sharing this implementation to the open community.
Background of QoS in 5G
A distinguishing feature of mobile wireless networks is their ability to provide end-to-end Quality of Service (QoS) on the connectivity between the mobile device and the data network. This has been a key enabler to providing enhanced broadband services and a variety of application use cases.
QoS is implemented by QoS Flows between the Access Network (AN) and the Core Network (UPF) and is defined by a QoS profile which includes various QoS parameters (e.g. resource type, priority level, Packet Delay Budget (PDB), Packet Error Rate (PER), averaging window, and Maximum Data Burst Volume (MDBV)) to define the quality characteristics of a service. QoS is also grouped into Non-GBR (Guaranteed Bit Rate) and GBR based on the type of service required by the applications.
Different applications require different QoS for the data connectivity between the application running on the mobile device and the application server running on the internet, edge, or WAN, and the QoS mechanism makes this possible. For example, the quality of service required by a conversational voice/video application is different from that required for live streaming of a sport event or for the control of a drone or remote-controlled car.
So far in wireless networks including 4G, the assignment of these QoS profiles to the application flow has been static and predetermined by the Policy Control Function (PCRF).
In 5G, the QoS can be applied dynamically and QoD use-case described below does just that. As an example, it could be very useful in the case of FWA, where various traffic flows are carried over the pipe with the same QoS characteristics. QoD allows different QoS for different types of traffic in a much more dynamic way. This is even more important as the networks start to become congested.
Quality on Demand - Capability Exposure
With the introduction of Network Exposure Function in the 5G core, applications are now able to dynamically configure and control their Quality of Service (QoS) for their connection to mobile devices. This unlocks a variety of advanced use cases and transforms mobile networks from a passive data pipe into a 'programmable connectivity platform'.
Spry Fox Networks have developed the QP-NEF, a 5G Network Exposure Function, and the QP Cloud MONET, a cloud-based network monetization API Gateway application. QP Cloud MONET implements the Quality on Demand (QoD) service API from the CAMARA project for applications and developers.
Spry Fox Networks is now sharing a Quality on Demand translation function reference implementation, built in Go language. This implementation provides the CAMARA community-defined QoD service APIs to the Application function, and translates into Quality-of-Service Network APIs defined by 3GPP on the other side. Our implementation allows a more granular control of QoS upto individual flows.
Our implementation is located at:
https://github.com/camaraproject/QualityOnDemand_PI3
Quality on Demand - FWA use-case
Quality on Demand service APIs can enable or enhance a range of next generation use cases, such as the Fixed Wireless Access (FWA) application illustrated in the diagram.
In FWA, the Customer Premises Equipment (CPE) acts as a subscriber device, connecting to the 5G Access and Core networks and providing data connectivity to devices connected on the local premises. Depending on the deployment scenarios (e.g., residential, enterprise, or factory), different applications using this connectivity require specific Quality of Service (QoS) levels.
Quality on Demand service provides the ability to dynamically assign specific QoS profiles to individual application flows based on their service requirements. Through CPE management applications or Application Detection functionality, mobile networks can detect these application flows, dynamically control the level of quality provided and enhance the Quality of Experience (QoE) for the service.
By further leveraging other network exposed capabilities, such as EDGE APIs, location services APIs, and network analytics APIs, we can further enhance the QoD use case.
Quality on Demand – other use-cases
QoD can enable other use-cases and unlock new revenue opportunities for Operators, Telco Cloud providers, and Application providers. Such as:
1. Premium streaming offered by an OTT platform or a live event streaming application
2. A mobile live stream broadcast studio could detect and configure higher quality of service for its uplink or downlink broadcast
3. A remote operator can dynamically enhance the quality of connectivity for a remote-controlled drone or vehicle
4. A mobile medical unit that generates multiple sources of UL/DL data can be dynamically configured to provide higher quality of service on demand and redirected to the nearest EDGE server location
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