Ricerc@Sapienza

Self-driving networks represent the next step of network management techniques in the close future. A fundamental point for such an evolution is the use of Machine Learning based solutions to extract information from data coming from network devices during their activity. In this work we focus on a new type of data, available thanks to the definition of the novel SRv6 paradigm, referred to as SRv6 Traffic Counters (SRTCs). SRTCs provide aggregated measurements related to forwarding operations performed by SRv6 routers.

Segment routing (SR) is a new routing paradigm to provide traffic engineering (TE) capabilities in an IP network. The main feature of SR is that no signaling protocols are needed, since extensions of the interior gateway protocol routing protocols are used. Despite the benefit that SR brings, introducing a new technology into an operational network presents many difficulties. In particular, the network operators consider both capital expenditure and performance degradation as drawbacks for the deployment of the new technology; for this reason, an incremental approach is preferred.

The Ingress Egress Traffic Matrix (IE TM) assessment is a fundamental step of the network management for an ISP network, since it represents the key input parameter used by any Traffic Engineering solution to optimize the resource utilization and to improve the Quality of Service. The actual TM assessment procedures are based on estimation algorithms or measurement based approaches. This paper presents a method to measure the intensity of traffic flows, that overcomes the limits of the classical measurement/estimation based approaches.

In this work we investigate the use of Segment Routing version 6 (SRv6) interface counters to improve the Traffic Matrix (TM) assessment of an ISP network. SRv6 is a source routing solution for IPv6 networks: it allows defining a network path as a sequence of routers, represented by Segments Identifiers (SID), to be crossed, i.e. a Segment List (SL). SRv6 provides a new set of interface counters able to measure the packets/ bytes of Ingress/Egress flows exploiting the forwarding operations performed on the Segment Identifiers (SIDs) reported in the SLs.

Traffic Matrix (TM) assessment is a key issue for optimizing network management costs and quality of service. This paper presents a method to measure the intensity of ingress-egress traffic flows on an ISP network that overcomes the limits of the classical measurement based approaches. The proposed algorithm, called SEgment Routing PErturbatioN Traffic (SERPENT), uses a routing perturbation approach enabled by the Segment Routing (SR) paradigm: the paths of a subset of flows are changed so that their intensities can be determined measuring the variation of the load of the network links.

Network Function Virtualization is a new technology allowing for a elastic cloud and bandwidth resource allocation. The technology requires an orchestrator whose role is the service and resource orchestration. It receives service requests, each one characterized by a Service Function Chain, which is a set of service functions to be executed according to a given order. It implements an algorithm for deciding where both to allocate the cloud and bandwidth resources and to route the SFCs.