A major challenge for telecommunications operators is to dimension and plan network capacity for all types of content delivered over the network, much of this being so-called “over-the-top” (OTT) traffic from third party content providers and aggregators. While Content Delivery Networks (CDN) are a very useful means of realising efficient delivery of large volumes of traffic, they can also be limited in flexibility and cost-efficiency due to the hardware-oriented nature of the architecture. Virtual CDNs (vCDNs) enable a more flexible and optimal delivery model whereby telco compute infrastructure offers a hosting environment for softwarised CDN caches. Such an approach also lends itself to increased levels of distribution and de-centralisation; edge compute to host vCDNs can provide both service quality advantages on the one hand, and network capacity planning benefits, on the other. This latter advantage arises from the opportunity for “local turn-around” of traffic due to cache hits on popular cached content. Only real-world trials of vCDN can determine these offload benefits in quantitative terms. This paper explains a major trial with two CDN partners (one delivering video content, the other delivering game content) performed in summer 2024 for a “metro” area; significant cache efficiency levels ranging from 50% to above 90% were observed confirming that significant traffic offload and thus capacity planning benefits - can be realised.

A growing number of network functions built to run on commodity compute infrastructure, are increasingly adopting cloud native principles, and therefore often run inside containers. Containerised Network Functions (CNFs) can be hosted directly on the server’s host OS- Bare Metal (BM)- or can run inside a Virtual Machine (VM). The choice of BM or VM to host containers depends on many factors linked to security, tenant isolation, available resources and performance. This paper explores this important consideration by conducting comparative tests in a specific domain, namely at the network edge where resources are tightly constrained. Using a small form-factor micro server, we demonstrate how BM can clearly out-perform the use of a VM but that this occurs when there are distinct set-up dependencies around small fixed frame sizes and very stringent packet loss constraints. The performance margin is notably shrunk however, when a more realistic traffic load is used and non-zero packet loss permitted: the VM performance reaches within 89% of the BM throughput, while also achieving an average latency 14% lower than the BM setup. These results emphasise it is not simply a clear-cut case of BM always being “better”, with many other factors requiring attention including security and tenant isolation. We use the insights gleaned from lab testing alongside qualitative criteria to better inform design decisions around using VMs or BM to host CNFs.

As an increasing number of software-oriented telecoms workloads are run as Containerised Network Functions (CNFs) on cloud native virtualised infrastructure, performance tuning is vital. When compute infrastructure is distributed towards the edge of networks, efficient use of scarce resources is key meaning the available resources must be fine-tuned to achieve deterministic performance; another vital factor is the energy consumption of such compute which should be carefully managed. In the latest generation of Intel x86 servers, a new capability called Speed Select Technology Turbo Frequency (SST-TF) is available, enabling more targeted allocation of turbo frequency settings to specific CPU cores. This has significant potential in multi-tenant edge compute environments increasingly seen in 5G deployments and is likely to be a key building block for 6G. This paper evaluates the potential application of SST-TF for competing CNFs – a mix of high and low priority workloads - in a multi-tenant edge compute scenario. The targeted application of SST-TF is shown to yield performance benefits compared to the legacy turbo frequency capability in earlier generations of processor (by up to 35%), and when combined with other intelligent resource management tooling can also achieve a net reduction in server power consumption (of 1.7%).

Network softwarization has revitalized the interest of the network community towards emulation as an effective mechanism for network experimentation. Relevant platforms automate the deployment of virtual network topologies on a host, providing users the ability to manually run experimental scenarios. Whilst this may suit prototyping, modern development and deployment practices such as CI/CD depend on fully automated testing processes, built around high-level testing APIs and abstracting the challenges involved with synchronizing complex node interaction scenarios. In this paper, we present Network Emulation System (NES): a cloud-native, and highly-parallelizable Network Emulation as a Service (NEaaS) platform designed from the ground up to facilitate codeless experiment specification and to automate network testing workflows in cloud CI/CD environments. We demonstrate that NES offers a 8x speedup improvement in topology instantiation times in comparison to existing emulation platforms, and its life-cycle model can automate testing processes for complex service configurations using existing CI/CD platforms such as GitHub Actions.

A key requirement for 5G networks supporting a range of network slices with distinct service characteristics, is to provide continuous monitoring and assurance of slice key performance indicators (KPIs). This paper describes a novel integrated framework using complementary methods of monitoring performance assurance. End-to-end active monitoring using a vendor-specific capability, is complemented by an open-source solution to passively collect and visualize platform telemetry. Via a proof-of-concept testbed, it is demonstrated that combining the reporting and visualization of performance KPIs applicable to different parts of the network infrastructure, provides a very powerful and holistic insights framework for 5G slicing assurance.

A major challenge with Network Functions Virtualisation (NFV) is ensuring protection of Virtual Network Function (VNF) resources against "Noisy Neighbor" effects. This is essentially the result of shared resources being consumed in extremis within a multi-tenant setup, meaning one VNF's resources are restricted by that of another VNF. One of the major shared resource bottlenecks is the central processor's Last Level Cache (LLC)- this paper details a testbed which enables "Cache Allocation Technology" (CAT), so as to deterministically prioritize LLC resources between competing workloads. A number of CAT "Class of Service" (CoS) paradigms are explained for a range of service chain scenarios, involving virtual Firewall and virtual Router VNFs alongside a Noisy Neighbor VNF. Significant performance benefits are confirmed bringing the performance of target VNFs in the presence of a LLC-hungry Noisy Neighbor, into alignment with the baseline scenario of a "Noise-Free" neighboring VNF.