Alberto Castro

Brokered Orchestration for End-to-End Service Provisioning Across Heterogeneous Multi-Operator (Multi-AS) Optical Networks

This paper proposes a new networking paradigm introducing the broker-plane above the management planes of Autonomous Systems (ASes). The brokers communicate with the manager of each AS to assist coordinate end-to-end resource management and path provisioning across the multi-AS networks involving multiple operators. The broker plane updates the virtual network topology, manages the resource information of inter-AS links and aggregated (abstracted) intra-AS links, and computes end-to-end routing, modulation formats, and spectrum assignment (RMSA). Notwithstanding, due to the different dynamicity of each AS, the probability of finding a multi-AS transparent path fulfilling the spectrum continuity and contiguity constraints might be low. To improve the grade of the inter-domain connectivity service, spectrum converters can be installed in inter-domain nodes or per-AS defragmentation can be performed with a global view. In this paper, we introduce a mechanism where each AS can advertise its internal capabilities, e.g., spectrum conversion, their ability to implement spectrum defragmentation or any other network feature. The Multi-AS RMSA with Defragmentation Capability problem is presented and mathematically modeled. A heuristic algorithm is designed to solve it. The mechanisms workflow is comprehensively tested using simulations. Results show connection blocking reduction as high as 26%, clearly validating the benefits of the proposed mechanism. Finally, its experimental assessment was conducted on a distributed multi-continental testbed.

Incentive-Driven Bidding Strategy for Brokers to Compete for Service Provisioning Tasks in Multi-Domain SD-EONs

It is known that the multi-broker-based management plane can potentially provide a realistic solution to facilitate incentive-driven cross-domain network orchestration in multi-domain software-defined elastic optical networks (SD-EONs). Such network orchestration assures the autonomy of each domain and supports economical service provisioning across multiple domains as well. In this study, we consider the economic principle in multi-broker-based multi-domain SD-EONs and study how to realize incentive-driven service provisioning with broker competitions. We first present the theoretical model of the network operations to describe the noncooperative game in which the brokers compete for interdomain provisioning tasks with only incomplete information on their competitors. Then, we analyze the Nash equilibrium in a simplified version of the game, and show that to maximize the brokers profits in long-term repeated games, an effective bidding strategy is needed for the brokers to predict their competitors behaviors and price their services in the optimal way. The bidding strategy is designed by leveraging the kernel density estimation scheme. Finally, to demonstrate the effectiveness of the proposed bidding strategy, we implement it in an OpenFlow-based multi-domain SD-EON control plane testbed. The experimental results verify that our system performs well and the brokers can obtain higher profits with the proposed bidding strategy in repeated games.

Elastic optical networking by dynamic optical arbitrary waveform generation and measurement

This paper discusses elastic optical networking (EON) by dynamic optical arbitrary waveform generation and measurement (DOAWG/DOAWM) technologies for flexible and agile bandwidth-variable transponders. The ability to generate and measure flexible bandwidth signals with arbitrary modulation formats and subwave-length granularity, as well as superchannels, makes DOAWG/DOAWM an attractive technology for EON. We introduce the DOAWG/DOAWM concept and its application to EON, and we discuss the use and advantages of DOAWG/DOAWM as the technology for a sliceable bandwidth variable transponder (SBV-T). Then we report our most recent experimental demonstration of a two-spectral-slice OAWG-SBV-T experiment to generate a single-carrier 60 Gbaud channel with dual-polarization quadrature phase-shift keying and dual-polarization 16 quadrature amplitude modulation formats. Finally, we discuss our current progress on the development of a chip-scale DOAWG on a heterogeneous Si3N4-InP integration platform.

On-demand incremental capacity planning in optical transport networks

Incremental planning is performed periodically to decide how a backbone optical network has to be updated to serve the forecast traffic during the next planning period. Based on reliable traffic prediction, new equipment is installed and its capacity is ready to be used. Nonetheless, due to the introduction of new services among other reasons, exact prediction is not usually available. This leads to the installation of more capacity than required, thus increasing network expenditures. In this paper, we propose to reduce expenses by incrementing the capacity of the network as soon as it is required to meet the target performance. Hence, performance metrics are monitored and the incremental capacity (INCA) planning problem is solved on-demand when some metrics drop under a threshold. The INCA problem is mathematically modeled and a heuristic algorithm is proposed to solve the problem in practical computation times. Since solving the INCA problem requires access to both operation and inventory databases, an architecture to support on-demand network planning as well as a model for the inventory is proposed. Exhaustive simulation results, together with its experimental assessment, validate the proposed on-demand INCA planning.

Experimental demonstration of brokered orchestration for end-to-end service provisioning and interoperability across heterogeneous multi-operator (multi-AS) optical networks

A broker on top of opaquely-managed optical domains advertising their capabilities is proposed to provision multi-AS connections in multi-operator scenarios. In case of no spectrum continuity, intra-domain spectral defragmentation is performed. Experimental assessment was conducted on a distributed multi-continental infrastructure.

Soft failure localization during commissioning testing and lightpath operation

In elastic optical networks (EONs), effective soft failure localization is of paramount importance to early detection of service level agreement violations while anticipating possible hard failure events. So far, failure localization techniques have been proposed and deployed mainly for hard failures, while significant work is still required to provide effective and automated solutions for soft failures, both during commissioning testing and in-operation phases. In this paper, we focus on soft failure localization in EONs by proposing two techniques for active monitoring during commissioning testing and for passive in-operation monitoring. The techniques rely on specifically designed low-cost optical testing channel (OTC) modules and on the widespread deployment of cost-effective optical spectrum analyzers (OSAs). The retrieved optical parameters are elaborated by machine learning-based algorithms running in the agents node and in the network controller. In particular, the Testing optIcal Switching at connection SetUp timE (TISSUE) algorithm is proposed to localize soft failures by elaborating the estimated bit-error rate (BER) values provided by the OTC module. In addition, the FailurE causE Localization for optIcal NetworkinG (FEELING) algorithm is proposed to localize failures affecting a lightpath using OSAs. Extensive simulation results are presented, showing the effectiveness of the TISSUE algorithm in properly exploiting OTC information to assess BER performance of quadrature-phase-shift-keying-modulated signals, and the high accuracy of the FEELING algorithm to correctly detect soft failures as laser drift, filter shift, and tight filtering.

Experimental Demonstration of Machine-Learning-Aided QoT Estimation in Multi-Domain Elastic Optical Networks with Alien Wavelengths

In multi-domain elastic optical networks with alien wavelengths, each domain needs to consider intradomain and interdomain alien traffic to estimate and guarantee the required quality of transmission (QoT) for each lightpath and perform provisioning operations. This paper experimentally demonstrates an alien wavelength performance monitoring technique and machine-learning-aided QoT estimation for lightpath provisioning of intradomain/ interdomain traffic. Testbed experiments demonstrate modulation format recognition, QoT monitoring, and cognitive routing for a 160 Gbaud alien multi-wavelength light- path. By using experimental training datasets from the testbed and an artificial neural network, we demonstrated an accurate optical-signal-to-noise ratio prediction with an accuracy of ~95% when using 1200 data points.

On the performance of flexgrid-based optical networks

The ever increasing IP traffic volume has finally brought to light the high inefficiency of current wavelength-routed rigid-grid networks in matching the client layer requirements. Such an issue results in the deployment of large-size, expensive and power-consuming IP/MPLS layers to perform the required grooming/aggregation functionality. To deal with this problem, the emerging flexgrid technology, allowing for reduced size frequency grids, usually referred to as frequency slot, has recently attracted great attention among network operators, component and equipment suppliers, and the research community. In this paper, we report the main contributions performed in the context of EU STRONGEST project regarding flexgrid optical networks.

Experimental assessment of degradation-triggered reconfiguration in optically interconnected cloud-RAN

C-RAN control architecture is proposed and experimentally assessed. A local controller in each location receives latency, jitter, and BER monitoring data from local BBUs and detects a CPRI degradation, which triggers a mobile network reconfiguration.

Brokered orchestration for end-to-end service provisioning across heterogeneous multi-operator networks

This paper proposes a new networking paradigm introducing the broker-plane above the management planes of Autonomous Systems (ASes). The brokers communicate with the manager of each AS to coordinate end-to-end resource management and path provisioning across the multi-AS networks involving multiple operators. The broker plane updates the virtual network topology, manages the resource information of inter-AS links and aggregated (abstracted) intra-AS links, and computes end-to-end routing, modulation formats, and spectrum assignment (RMSA). To improve the grade of the inter-domain connectivity service, spectrum converters can be installed in inter-domain nodes or per-AS defragmentation can be performed with a global view. In this paper, we introduce a mechanism where each AS can advertise its internal capabilities, e.g., spectrum conversion, their ability to implement spectrum defragmentation or any other network feature. The Multi-AS RMSA with Defragmentation Capability problem is presented.