Cristina Rottondi

Polytechnic University of Turin | polito · DET - Department of Electronics and Telecommunications

Ensuring inclusiveness in networked musical education and practices raises unprecedented technical, artistic and pedagogical challenges. Due to its immense social and cultural impact, the research community is urged to tackle such challenges with holistic and multidisciplinary approaches, encompassing the know-how and competences of experts in seve...

In networked music performance (NMP) applications, which entail real-time audio streaming over the Internet, strict latency requirements are needed to ensure a realistic interaction between geographically dispersed musicians. Thus, NMP applications typically leverage uncompressed audio and unreliable transport protocols to avoid unnecessary process...

Traffic prediction is an evergreen research topic in networking, with modern allocation algorithms often utilizing forecasts for optimized decisions. However, the employed machine learning (ML) models are usually operated as black boxes – without any insight into their internal operations. Such an approach creates a risk of using excessive input fe...

Adapting to concept drift is a challenging task in machine learning, which is usually tackled using incremental learning techniques that periodically re-fit a learning model leveraging newly available data. A primary limitation of these techniques is their reliance on substantial amounts of data for retraining. The necessity of acquiring fresh data...

Networked Music Performances (NMPs) involve geographically-displaced musicians performing together in real-time. To date, scarce research has been conducted on how to integrate NMP systems with immersive audio rendering techniques able to enrich the musicians’ perception of sharing the same acoustic environment. In addition, the use of wireless tec...

This paper provides an overview on inclusiveness in remote music education and networked music performances, highlighting issues and difficulties encountered by users with visual, auditory or motor disabilities when approaching such practices. Currently available technologies that can be leveraged to enhance the accessibility of web-based platforms...

Current sound-based practices and systems developed in both academia and industry point to convergent research trends that bring together the field of Sound and Music Computing with that of the Internet of Things. This paper proposes a vision for the emerging field of the Internet of Sounds (IoS), which stems from such disciplines. The IoS relates...

We apply Quantile Regression (QR) for lightpath quality-of-transmission (QoT) estimation with the aim of identifying uncertain decisions and then exploit Shapley Additive Explanations (SHAP) to quantify lightpath features' importance by means of SHAP values and validate the model's decisions in a post-processing phase. Numerical results show that o...

In the past two decades, we have witnessed the diffusion of an increasing number of technologies, products, and applications at the intersection of music and networking. As a result of the growing attention devoted by academy and industry to this area, three main research fields have emerged and progressively consolidated: the Networked Music Perfo...

We demonstrate the potentialities of explainable AI when applied to distill knowledge from a trained supervised machine learning model for lightpath quality of transmission estimation in optical networks, with synthetic datasets.

Following the emergence of Elastic Optical Networks (EONs), Machine Learning (ML) has been intensively investigated as a promising methodology to address complex network management tasks, including, e.g., Quality of Transmission (QoT) estimation, fault management, and automatic adjustment of transmission parameters. Though several ML-based solution...

This special issue contains a collection of invited and contributed papers, including a review article and eight research articles, on the application of machine learning to the estimation of quality of transmission in optical networks.

Estimating the quality of transmission (QoT) of a candidate lightpath prior to its establishment is of pivotal importance for effective decision making in resource allocation for optical networks. Several recent studies investigated machine learning (ML) methods to accurately predict whether the configuration of a prospective lightpath satisfies a...

We perform a machine-learning-based network pruning that significantly reduces the complexity of routing and wavelength assignment in large optical networks. A significant computational time reduction is achieved by accepting a minor deterioration of the obtained solution.

Machine learning (ML) is currently being investigated as an emerging technique to automate quality of transmission (QoT) estimation during lightpath deployment procedures in optical networks. Even though the potential network-resource savings enabled by ML-based QoT estimation has been confirmed in several studies, some practical limitations hinder...

Machine learning (ML) is increasingly applied in optical network management, especially in cross-layer frameworks where physical layer characteristics may trigger changes at the network layer due to transmission performance measurements (quality of transmission, QoT) monitored by optical equipment. Leveraging ML-based QoT estimation approaches has...

Single-task UAVs are increasingly being employed to carry out surveillance, parcel delivery, communication support, and other specific tasks. When the geographical area of operation of single-task missions is common, e.g., in post-disaster recovery scenarios, it is more efficient to have multiple tasks carried out as part of a single UAV mission. I...

Single-task UAVs are increasingly being employed to carry out surveillance, parcel delivery, communication support, and other specific tasks. When the geographical area of operation of single-task missions is common, e.g., in post-disaster recovery scenarios, it is more efficient to have multiple tasks carried out as part of a single UAV mission. I...

Networked Music Performance (NMP) is envisioned as a potential game changer among Internet applications: it aims at revolutionizing the traditional concept of musical interaction by enabling remote musicians to interact and perform together through a telecommunication network. Ensuring realistic conditions for music performance, however, constitute...

We compare the level of accuracy achieved by active learning and domain adaptation approaches for quality of transmission estimation of an unestablished lightpath, in presence of small-sized training datasets.

We evaluate the performance of two domain adaptation approaches for machine learning assisted quality of transmission estimation of an optical lightpath, for a fixed/variable number of available training samples from the source/target domain.

We investigate a Machine Learning regression model for Optical Signal-to-Noise Ratio (OSNR) distribution estimation of unestablished lightpaths. The regressor exposes the estimation uncertainty and how close to a threshold each lightpath resides.

By performing in-network caching, Internet Service Providers (ISPs) allow Content Providers (CPs) to serve contents from locations closer to users. In this way, the pressure of content delivery on ISPs’ network is alleviated, and the users’ Quality-of-Experience (QoE) improved. Due to its impact on QoE, caching has been recently considered as a for...

Estimating the quality of transmission (QoT) of a lightpath before its establishment is a critical procedure for efficient design and management of optical networks. Recently, supervised machine learning (ML) techniques for QoT estimation have been proposed as an effective alternative to well-established, yet approximated, analytic models that ofte...

Abstract An algorithm for the non-intrusive disaggregation of energy consumption into its end-uses, also known as non-intrusive appliance load monitoring (NIALM), is presented. The algorithm solves an optimisation problem where the objective is to minimise the error between the total energy consumption and the sum of the individual contributions of...

Abstract In this paper we present insights drawn from recent research projects aimed at developing visualization and gamification tools to stimulate individual behaviour change and promote energy and water saving. We address both the design of resource-saving programmes and the methodologies to assess their effectiveness. We conclude by presenting...

Evaluating Network Neutrality requires comparing the quality of service experienced by multiple users served by different Internet Service Providers. Consequently, the issue of guaranteeing privacy-friendly network measurements has recently gained increasing interest. In this paper we propose a system which gathers throughput measurements from user...

UAVs are increasingly being employed to carry out surveillance, parcel delivery, communication-support and other specific tasks. In certain cases, the same geographical area may be in need of multiple services, which can be carried out by the same drones. In this paper, we propose and investigate a joint planning of multitask missions leveraging a...

Failure management plays a role of capital importance in optical networks to avoid service disruptions and to satisfy customers' service level agreements. Machine Learning (ML) promises to revolutionize the (mostly manual and human-driven) approaches in which failure management in optical networks has been traditionally managed, by introducing auto...

UAVs are increasingly being employed to carry out surveillance, parcel delivery, communication-support and other specific tasks. Their equipment and mission plan are carefully selected to minimize the carried load an overall resource consumption. Typically, several single task UAVs are dispatched to perform different missions. In certain cases, (pa...

UAVs are increasingly being employed to carry out surveillance, parcel delivery, communication-support and other specific tasks. Their equipment and mission plan are carefully selected to minimize the carried load an overall resource consumption. Typically, several single task UAVs are dispatched to perform different missions. In certain cases, (pa...

The distribution of video contents generated by Content Providers (CPs) significantly contributes to increase the congestion within the networks of Internet Service Providers (ISPs). To alleviate this problem, CPs can serve a portion of their catalogues to the end users directly from servers (i.e., the caches) located inside the ISP network. Users...

Metro-area networks are likely to create the right conditions for the deployment of Few-Mode Transmission (FMT) due to limited metro distances and rapidly-increasing metro traffic. To address the new network design problems arising with the adoption of FMT, Integer Linear Programming (ILP) formulations have been already developed to optimally assig...

We use active learning to reduce the number of probes needed for machinelearning-based QoT estimation. When building an estimation model based on Gaussian processes, only QoT instances that minimize estimation uncertainty are iteratively requested.

Computer and social sciences offer a wide range of tools to help face the world’s challenges arising in smart city scenarios and involving environment, energy, food, water, transportation, infrastructures, society, healthcare, education, governance, and economy. Indeed, purely technical solutions might be of little effect without proper considerati...

Multicore Fibers (MCFs) are one of the main technological enablers for Space Division Multiplexing. In principle, MCFs could scale the fiber capacity by a factor equal to the number of cores, but in practice such increase is hindered by transmission impairments due to the inter-core crosstalk between adjacent lit cores. The entity of such crosstalk...

Today’s telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users’ behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions...

Caching strategies have been always regarded as an important tool to reduce network traffic and to guarantee an improved Quality of Service (QoS) to customers. However, being an inherently selective process, it results in service differentiation and, potentially, discriminatory treatment of user-requested content. Despite of this, in-network cachin...

In a world affected by the constant growth and concentration of the population in urban areas, the problem of preserving natural resources has become a priority. A promising approach to resource conservation is demand management, i.e., the ability to positively influence the behaviour of the population towards more sustainable consumption. Informat...

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions...

Predicting the quality of transmission (QoT) of a lightpath prior to its deployment is a step of capital importance for an optimized design of optical networks. Due to the continuous advances in optical transmission, the number of design parameters available to system engineers (e.g., modulation formats, baud rate, code rate, etc.) is growing drama...

The possibility of flexibly assigning spectrum resources with channels of different sizes greatly improves the spectral efficiency of optical networks, but can also lead to unwanted spectrum fragmentation.We study this problem in a scenario where traffic demands are categorised in two types (low or high bit-rate) by assessing the performance of thr...

The possibility of flexibly assigning spectrum resources with channels of different sizes greatly improves the spectral efficiency of optical networks, but can also lead to unwanted spectrum fragmentation.We study this problem in a scenario where traffic demands are categorised in two types (low or high bit-rate) by assessing the performance of thr...

We model and solve the core and spectrum assignment problem in a multicore flexi-grid link, considering distance-adaptive reaches for different modulation formats and crosstalk impairments. Problem complexity and exemplifying numerical results on 19-core fibers are discussed.

We propose a heuristic approach for Routing, Modulation format, Baud rate and Spectrum Allocation in few-mode networks considering inter-modal coupling impairments. Performance is assessed in terms of spectrum utilization and transceiver cost.

In the presence of time-variable energy tariffs, users will try to schedule the usage of their electrical appliances with the goal of minimising their bill. If the variable price component depends on the peak aggregate demand during each given hour, users will be incentivised to redistribute their consumption during the day, thus lowering the overa...

Serious games can be used to push consumers of common-pool resources towards socially responsible consumption patterns. However, gamified interactions can result in privacy leaks and potential misuses of player-provided data. In the Smart Grid ecosystem, a smart metering framework providing some basic cryptographic primitives can enable the impleme...

This paper presents the research objectives of the enCOMPASS project, which aims at implementing and validating an integrated socio-technical approach to behavioural change for energy saving. To this end, innovative user-friendly digital tools will be developed to 1) make energy data consumption available and understandable for different types of u...

The possibility of flexibly assigning spectrum resources with channels of different sizes greatly improves the spectral efficiency of optical networks. The drawback of this flexibility is the risk of spectrum fragmentation. We study this problem in the two-service scenario. Our first contribution consists of exact Markov models for different assign...

The Smart Meter (SM) is an essential tool for successful balancing the demand-offer energy curve. It allows the linking of the consumption and production measurements with the time information and the customer’s identity, enabling the substitution of flat-price billing with smarter solutions, such as Time-of-Use or Real-Time Pricing. In addition to...

Networked Music Performance (NMP) is a potential game changer among Internet applications, as it aims at revolutionizing the traditional concept of musical interaction by enabling remote musicians to interact and perform together through a telecommunication network. Ensuring realistic performance conditions, however, constitutes a significant engin...

Application of few-mode transmission (FMT) in transport optical network is currently under scrutiny, especially for metro networks where shorter distances and pressing traffic increase (e.g., due to a growing need for metro datacenter interconnection) represent promising conditions for FMT deployment. In this paper, we analyze, from a network-level...

When energy prices change during the day, users will schedule their appliances with the aim of minimizing their bill. If the variable price component depends on the peak demand during each given hour, users will distribute their consumption more evenly during the day, resulting in lower peak consumption. The process can be automated by means of an...

The proposed framework enables innovative power management in smart campuses, integrating local renewable energy sources, battery banks and controllable loads and supporting Demand Response interactions with the electricity grid operators. The paper describes each system component: the Energy Management System responsible for power usage scheduling...

Serious games are potentially powerful tools to influence users' preferences and attitudes. However, privacy concerns related to the misuse of data gathered from the players may emerge in online-gaming interactions. This work proposes a privacy-friendly framework for a gaming platform aimed at reducing energy and water usage, where players are grou...