A P4-based 5G User Plane Function

MacDavid, Robert; Cascone, Carmelo; Lin, Pingping; Padmanabhan, Badhrinath; ThakuR, Ajay; Peterson, Larry L.; Rexford, Jennifer; Sunay, Oğuz

doi:10.1145/3482898.3483358

“…In the context of mobile core networks, P4 switches have been used for real-time attack detection and mitigation [4], identification of malicious data [13], enhancing the User Plane Function (UPF) functionality [37] and ensuring QoS at the slice level [49]. A recent study [39] investigated impact of P4-INT on network performance compared to that of the traditional active and passive monitoring approaches.…”

Section: Related Workmentioning

confidence: 99%

Bottleneck Identification in Cloudified Mobile Networks based on Distributed Telemetry

Rukh¹,

Ahmed²,

Dreibholz³

et al. 2023

Preprint

0

View full text Add to dashboard Cite

Cloudified mobile networks, such as 5G, are expected to deliver a multitude of services to several slices in parallel, while having reduced capital and operating expenses. The 5G mobile systems, therefore, need to ensure that the SLAs of customized end-to-end sliced services are met. This requires monitoring the resource usage and characteristics of data flows at the virtualized network components and interfaces of its cloud mobile network, as well as tracking the performance at its radio interfaces and UEs. A centralised monitoring architecture can not scale to support millions of UEs though. This paper, proposes a distributed telemetry framework in which UEs act as early warning sensors. Upon flagging an anomaly, the cloudified mobile network activates a machine learning model to attribute the cause of the anomaly. We employ active, passive and in-band telemetry in our monitoring framework and achieve an impressive performance of 85% F1 score in detecting anomalies caused by different bottlenecks, and an overall 89% F1 score in attributing these bottlenecks. Our distributed framework achieves almost same bottleneck attribution accuracy to that of acentralized monitoring system but with no overhead of transmitting UE-based telemetry data to the centralized controller.

show abstract

“…In the context of mobile core networks, P4 switches have been used for real-time attack detection and mitigation [4], identification of malicious data [13], enhancing the User Plane Function (UPF) functionality [37] and ensuring QoS at the slice level [49]. A recent study [39] investigated impact of P4-INT on network performance compared to that of the traditional active and passive monitoring approaches.…”

Section: Related Workmentioning

confidence: 99%

Bottleneck Identification in Cloudified Mobile Networks based on Distributed Telemetry

Rukh¹,

Ahmed²,

Dreibholz³

et al. 2023

Preprint

0

View full text Add to dashboard Cite

Cloudified mobile networks, such as 5G, are expected to deliver a multitude of services to several slices in parallel, while having reduced capital and operating expenses. The 5G mobile systems, therefore, need to ensure that the SLAs of customized end-to-end sliced services are met. This requires monitoring the resource usage and characteristics of data flows at the virtualized network components and interfaces of its cloud mobile network, as well as tracking the performance at its radio interfaces and UEs. A centralised monitoring architecture can not scale to support millions of UEs though. This paper, proposes a distributed telemetry framework in which UEs act as early warning sensors. Upon flagging an anomaly, the cloudified mobile network activates a machine learning model to attribute the cause of the anomaly. We employ active, passive and in-band telemetry in our monitoring framework and achieve an impressive performance of 85% F1 score in detecting anomalies caused by different bottlenecks, and an overall 89% F1 score in attributing these bottlenecks. Our distributed framework achieves almost same bottleneck attribution accuracy to that of acentralized monitoring system but with no overhead of transmitting UE-based telemetry data to the centralized controller.

show abstract

“…In the control/forwarding plane separation architecture of SDN, the controller is the header of the entire network and distributes forwarding rules to forwarding devices like switches to control complete packet forwarding operation [28]. Specially, In CSVRF, the controller is not only responsible for the distribution of the prime key but also supports the construction and maintenance of the forwarding table, and CSVRF can also be employed in some commercial switches such as Tofino switch 2.0, which supports P4 language and operates in P4 language [1,2]. For example, the P4 switch can be used to generate the required prime key from parsing the packet header based on the data-plane programmable function.…”

Section: Author Contributionsmentioning

confidence: 99%

“…In recent years, with the rapid evolution of the networking industry, driven by advancements like 5G and the emergence of Protocol-independent Packet Processors (P4) language, the demand for high-performance switches and routers has risen significantly [1,2]. The pivotal component in these highperformance switches and routers is the packet forwarding engine (PFE), which directly impacts their overall performance.…”

Section: Introductionmentioning

confidence: 99%

CSVRF: A CAM‐based popularity‐aware egress group‐caching scheme for SVRF‐based packet forward engines

Wu,

Jia

2023

IET Communications

0

View full text Add to dashboard Cite

As a key component of high‐performance switches and routers, the packet forwarding engine (PFE) is mainly responsible for selecting the appropriate output port for tens of thousands of packets within an extremely short time frame. However, the performance of PFE is determined by the selected group membership algorithm. This paper puts forth a hybrid strategy–caching scalar‐pair and vectors routing and forwarding (CSVRF), consisting of virtual output port bitmap caching (VOPBC) and fractional‐N SVRF to address major multicast forwarding issues such as scalability by using content addressable memory. In CSVRF, a virtual output port bitmap cache is introduced, which includes the most popular combinations of output port bitmap and divides the big scalar‐pair into N sub‐groups to achieve parallel compute and the reusability of less bit‐length prime. The results demonstrate that the memory space and the forwarding latency are effectively reduced compared with previous work. In space efficiency, it only required 10% memory space compared with the original SVRF/fractional‐N SVRF, decreased 10% memory usage compared with pure VOPBC and nearly improved 1 to 4 orders of magnitude of packet processing time compared with the original SVRF and the fractional‐N SVRF respectively.

show abstract

A P4-based 5G User Plane Function

Cited by 41 publications

References 7 publications

Bottleneck Identification in Cloudified Mobile Networks based on Distributed Telemetry

Bottleneck Identification in Cloudified Mobile Networks based on Distributed Telemetry

Bottleneck Identification in Cloudified Mobile Networks based on Distributed Telemetry

CSVRF: A CAM‐based popularity‐aware egress group‐caching scheme for SVRF‐based packet forward engines

Contact Info

Product

Resources

About