Optical connections support virtual links in MPLS-over-optical multilayer networks and therefore, errors the optical layer impact on quality of services deployed such networks. Monitoring performance physical allows verifying proper operation connections, as well detecting bit error rate (BER) degradations anticipating connection disruption. In addition, failure identification facilitates localizing cause by providing a short list potential failed elements enables self-decision making to...

In elastic optical networks (EONs), effective soft failure localization is of paramount importance to early detection service level agreement violations while anticipating possible hard events. So far, techniques have been proposed and deployed mainly for failures, significant work still required provide automated solutions both during commissioning testing in-operation phases. this paper, we focus on in EONs by proposing two active monitoring passive monitoring. The rely specifically...

Network slices combine resource virtualization with the isolation level required by future 5G applications. In addition, use of monitoring and data analytics help to maintain network performance, while reducing total cost ownership. this paper, an architecture enable autonomic slice networking is presented. Extended nodes make local decisions close devices, whereas centralized domain systems collate export metered transparently customer controllers, all them leveraging customizable isolated...

Emerging services and applications demanding high bitrate stringent quality of service requirements are pushing telecom operators to upgrade their core networks based on wavelength-division multiplexing (WDM) a more flexible technology for the dynamic variable traffic that is expected be conveyed. Finally, academy- industry-driven research elastic optical (EON) has turned out into mature enough ready gradually WDM-based networks. Among others, key EON features include spectrum allocation,...

The availability of coarse-resolution cost-effective Optical Spectrum Analyzers (OSA) allows its widespread deployment in operators' networks. In this paper, several machine learning approaches for failure identification and localization that take advantage OSAs are presented.

With the incremental amount of applications running over telecom cloud architecture it is becoming paramount importance being able to run simulations aiming at evaluating performance such applications. To that end, one key elements in simulation how generate network traffic. In this paper we propose realistic traffic functions can be used for purposes and present those have been integrated our OMNET++-based simulator.

Early optical layer BER degradation detection is proposed to trigger affected demands re-routing, targeting at reducing SLA violation. Results show that the and re-routing algorithms noticeably reduce bandwidth number of affected.

Data visualization is applied to BER measures in a bigdata repository. Bubble charts are produced identify lightpaths with increasing and spectrum color maps then used the most likely degraded link.

An architecture supporting the OAA loop is proposed. It consists on extending nodes and domain controller with analytics capabilities for local network-wide operation automation. The experimentally assessed through a use case.

CASTOR MDA allows collecting huge amounts of measurements from devices. Such data needs to be preprocessed and analyzed discover summarize knowledge that can consumed by human operators. Helper tools are demonstrated on a realistic multilayer network scenario.

Monitoring the physical layer is key to detect bit error rate (BER) degradation caused by failures and identify cause of failure localize failed elements. Once has been detected, actions can be taken reduce as much possible its impact on network. Commercially available optical equipment are able correct degraded signals means Forward Error Correction (FEC) algorithms. A value pre-FEC BER over a pre-defined threshold would imply non-error-free post-FEC transmission and, result, communication...

Failure detection is essential in optical networks as a result of the huge amount traffic that connections support. Additionally, cause failure needs to be identified so failed resources can excluded from computation restoration paths. In case soft-failures, their prompt detection, identification, and localization make recovery triggered before excessive errors translate into on supported services or even become disrupted. Therefore, Monitoring Data Analytics (MDA) paramount importance...

Soft failure localization to early detect service level agreement violations is of paramount importance in elastic optical networks (EONs), while it allows anticipating possible hard events. Nowadays, effective and automated solutions for soft during lightpaths' commissioning testing operation are still missing. In this paper, we focus on presenting algorithms based two different active monitoring techniques. First, the Testing optIcal Switching at connection SetUp timE (TISSUE) algorithm...

Multiple OD traffic anomalies can arise exceeding pre-planned capacity and causing congestion. We propose to detect anomalous suspicious ODs reduce virtual network reconfiguration total losses. Results show savings higher than 25%.

Machine learning (ML) offers a great variety of algorithms that can be used in the context optical networks. In particular, ML might applied for classification and to detect patterns, among others. Both, help facilitate improving its performance, as well understand behavior this paper, we review two these algorithms, one other clustering. Illustrative examples application such supervised unsupervised networks are presented.

Machine Learning (ML) has already proven its benefits for network operation, being a sub-domain of artificial intelligence, it is highly suitable complex system representation. In this paper, basic ML concepts are reviewed, as well integration into existing control and management planes. Then, use case focused on soft-failure detection presented in detail covering optical spectrum analysis algorithms; the technique relies widespread deployment cost-effective analyzer (OSA). Finally,...

Traffic anomalies can create network congestion, so its prompt and accurate detection would allow operators to make decisions guarantee the performance avoiding services experience any perturbation. In this paper, we focus on origin-destination (OD) traffic anomalies; efficiently detect those, study two different anomaly methods based data analytics combine them with three monitoring strategies. view of short period needed reduce detection, which entails large amount be collected analyzed in...

We propose and demonstrate cross-stratum Broker orchestration for scientific applications heterogeneous resources reservation in DCs, HPC facilities networks belonging to different operators. Experiments were performed a distributed set-up spanning across three continents.

Optical connections support virtual links in MPLS-over-optical multilayer networks and therefore, errors the optical layer impact on quality of services deployed such networks. Monitoring performance physical allows verifying proper operation connections, as well detecting bit error rate (BER) degradations. Anticipating BER degradation facilitates self-decision making to keep committed service level. In this paper, we analyze several failure causes affecting propose BANDO algorithm focused...

Control and orchestration of metro network to support dynamic provisioning reconfiguration services based on Virtual Network Functions are demonstrated through a CDN example. Interaction among CASTOR MDA, OSM ONOS is exhibited.

The use of data visualization techniques is explored to guide human operators in failure localization tasks. In this paper, we consider the case where a subset lightpaths' experience gradual BER degradation. We aim at using find out most likely resource that responsible for such degradation, as well start Note challenge analyze an amount might be huge (e.g., 1 sample every 15 min last, let us say, 4 weeks, lightpath network) and display charts seconds, while revealing meaningful information...