Intent-Based Networking (IBN) enables operators to specify high-level outcomes while the system translates these intents into concrete policies and configurations. As IBN deployments grow in scale, heterogeneity and dynamicity, ensuring continuous alignment between network behavior and user objectives becomes both essential and increasingly difficult. This paper provides a technical survey of assurance and conflict detection techniques in IBN, with the goal of improving reliability, robustness, and policy compliance. We first position our survey with respect to existing work. We then review current assurance mechanisms, including the use of AI, machine learning, and real-time monitoring for validating intent fulfillment. We also examine conflict detection methods across the intent lifecycle, from capture to implementation. In addition, we outline relevant standardization efforts and open-source tools that support IBN adoption. Finally, we discuss key challenges, such as AI/ML integration, generalization, and scalability, and present a roadmap for future research aimed at strengthening robustness of IBN frameworks.

The demand for continuous patients monitoring in healthcare has increased significantly, originated mainly from the need for proactive and personalized treatments. In fact, traditional periodical monitoring often fails to detect rapid physiological changes, resulting in a risk especially for patients with chronic conditions or post-surgical needs. This paper presents a voice-driven mobile health monitoring application that enables daily tracking of six health parameters, addressing the limitations of traditional periodic monitoring. Designed to cater to diverse environments, including rural and urban areas, the app ensures reliable functionality storing data locally and synchronizing with a centralized database once connectivity is available. The app integrates seamlessly with Bluetooth devices and $4 \mathrm{G} / 5 \mathrm{G}$ networks, offering scalability. It also relies on the QUIC protocol for a more secure data transmission and provides a voice recognition feature for an easy collection of health parameters thus further enhancing user experience and contributing to the growing field of mHealth.

The widespread connectivity provided by fixed and mobile communication technologies can facilitate the utilization of e-health and mobile-health services that are radically changing the way healthcare may be provided. Such services are particularly important for inner areas, where it is difficult to guarantee physical availability and proximity of services while ensuring the sustainability of the system. However, e-health and m-health service deployment requires careful planning, as connectivity in inner areas can be spotty. This paper reports how multiple e/m-health solutions have been planned in some inner areas of Tuscany within the PROXIMITY-CARE project. In particular, it introduces a newly developed QGIS-based analysis tool, which allows correlating connectivity data with patient needs and healthcare facilities location. Moreover, the paper presents a tele-tutoring system for the emergency service and a mobile application to monitor patient vital parameters. Such tools facilitate the maximization of the reached population, thus improving benefits for the patients.

Intent-based Networking (IBN) has emerged as an innovative approach to automate the provisioning of network services while abstracting the details of the underlying infrastructure and simplifying the interaction between the users and the network. In this paper, we present an intent-based framework that allows for the deployment of SDN-based and QoS-aware network slices. The main objective of the work is to describe the role of artificial intelligence techniques such as Natural Language Processing (NLP) and user profiling in helping non-expert users easily interact with the IBN system and express their desired operational goals. Such innovative solutions offer a customized support to the users to improve their Quality of Experience (QoE) while increasing the automation in the network configuration process.

Network slicing plays a key role in the 5G ecosystem for vertical industries to introduce new services. However, one widely-recognized challenge of network slicing is to provide traffic isolation and concurrently satisfy diverse performance requirements, e.g., bandwidth and latency. In this work, we showcase the capability to retain these two goals at the same time, via extending the 5Growth baseline architecture and designing a new data-plane pipeline, i.e., virtual queue, over the P4 switch. To demonstrate the effectiveness of our approach, a proof-of-concept is presented serving different service requests over a mixed data path, including P4 switches and Open vSwitches (OvSs).

Vertical industries are attracted by the flexibility and customization offered by network operators through network slicing to run their application platforms in virtual infrastructure assets tailored to their needs. On the other hand, in addition to the desired virtual capacity and component network functions into the slice, verticals may also want to specify connectivity and QoS slice requirements in abstract terms and without dealing with details of network service descriptors and technicalities of the underlying infrastructure.In this work, we propose an intent-based QoS-aware and SDN-enabled slicing implementation that allows customized specifications and establishment of network slices toward flexible delivery of vertical services. The aim is to simplify and automate the deployment of the network slices through a declarative approach while unburdening verticals to deal with technology-specific low-level networking directives. The paper focuses on the implementation of the intent layer using an ETSI NFV MANO platform and presents preliminary experimental results assessing the feasibility and effectiveness of our approach.

From tenant (i.e., vertical) perspective, one of the attractive feature of network slices is the possibility to use SDN solutions, i.e., network programmability, to facilitate dynamic connectivity in the slice of the application software components in a flexible and scalable way. In this paper, we present an automated deployment of tenant-managed SDN network slices that allows network operators to enhance the service offerings, and tenants to benefit of in-built SDN capabilities. The SDN slice is built as a Network Service automatically deployed by Open Source MANO as a set of VNFs dynamically configured as SDN nodes (switches and controller) connecting tenant software components. We describe how to automatically and programmat-ically set-up SDN capabilities in the slice through the use of Juju Charms and provide some preliminary performance results.

Due to the impressive demand for communication-intensive applications deployed in the cloud, cross-layer orchestration solutions for Cloud data centers (DCs) are essential for the effective usage of both network and cloud resources while addressing service requirements and user expectations. In this regard, the software-defined networking (SDN) can play a key role thanks to programmable network control operations and to a more effective inter-working between network controllers and cloud management platforms. On the other hand, due to the relevant size of Cloud DCs, a significant evaluation of SDN-based orchestration solutions requires testing environments with proper scales, and significant level of fidelity. This paper discusses the opportunities of using virtual testbeds to carry out Cloud-related experimentations while addressing with significant scale requirements of DC infrastructures. First, we present a set of results of a test campaign we carried out using the Fed4FIRE experimental facility aiming at a comprehensive performance evaluation of an SDN-based orchestration solution for Cloud DCs. Second, we provide a comparison between virtual testbeds and other testing environments, i.e., laboratory testbeds, simulators and emulators, in terms of offered advantages, and effectiveness in experimentations. Moreover, we discuss the appropriateness and advisability of using virtualized testbeds for research on novel SDN and Cloud orchestration solutions at scale, by highlighting advantages of virtual testbeds in comparison with laboratory, simulation and emulation testing facilities in terms of effectiveness of experimentations and accuracy of results.

Supporting end-to-end network slices and services across operators has become an important use case of study for 5G networks as can be seen by 5G use cases published in 3GPP, ETSI as well as NGMN. This paper presents the in- depth architecture, implementation and experiment on a multi-domain orchestration framework that is ab le to deploy such multi-operator service as well as monitor the service for SLA compliance. Our implemented architecture allows operators to abstract their sensitive details while exposing the relevant amount of information to support inter-operator slice creation. Our experiment shows that the implemented framework is capable of creating services across operators while fulfilling the respective service requirements.

The future 5G transport networks are envisioned to support a variety of vertical services through network slicing and efficient orchestration over multiple administrative domains. In this paper, we propose an orchestrator architecture to support vertical services to meet their diverse resource and service requirements. We then present a system model for resource orchestration of transport networks as well as low-complexity algorithms that aim at minimizing service deployment cost and/or service latency. Importantly, the proposed model can work with any level of abstractions exposed by the underlying network or the federated domains depending on their representation of resources.

In this paper, we present an experimental set-up reproducing a convergent 5G service scenario spanning over SDN-based Edge network, Cloud and IoT domains. To address reliability and robustness requirements of future 5G networks, the set-up also includes an SDN orchestrator able to adaptively provision data delivery paths connecting service components running in those different domains. In particular, we demonstrate SDN orchestration capabilities in adapting data paths across IoT, Cloud and network domains based on the real-time load state of switches thereby recovering from congestions and assuring reliable data delivery services.

The promise of SDN/NFV to offer enhanced functionalities to the service provider networks is now tangible as both technologies have started being steadily investigated and experimentally demonstrated. However, a number of research challenges have not been fully addressed yet. More specifically, a limited interest has been devoted on how to assure reliability and QoS performance while data traverse service chain paths. In this work, we present an SDN orchestrator that periodically evaluate the availability status of the network and, accordingly, adapt service chain paths to recover from congestion events and to preserve QoS performance thus avoiding SLA violations. A prototype is presented along with a performance evaluation of the orchestrator in terms of improved data transfer capabilities against the cost of path adaptations and the controller overhead.

We present an SDN-based orchestration system that enables automated and coordinated arrangement of both computing and network resources in virtualized DC environments. The orchestrator is validated through a set of simulations, as well as through experiments carried out in a real laboratory. Results show that the proposed orchestration system improves the service requests acceptance rate and the utilization of network resources, while minimizing degradations of the user experience. Thus, DC resources can be effectively exploited, and different management objectives (e.g., load balancing, energy saving) can be reached.

Recent advances in network control and management technologies, such as software defined networking (SDN) and network function virtualization (NFV), are expected to make the network effectively able to cope with application service requirements in a more flexible and timely manner. We argue that SDN and NFV capabilities can be exploited in Next Generation Service Overlay Networks (NGSONs) for addressing contex-aware end-to-end data delivery services with adaptive composition of middlebox services when dynamically provisioned as virtual functions. In this paper we present a Service-Oriented SDN controller that allows for the programmable provision of data delivery paths through a dynamically established sequence of virtual middlebox functions, thereby accomplishing the deployment of adaptive network service chains in NGSON. In this way, an extended set of QoS requirements can be addressed that include specifications on processing functions to be traversed by service data while taking advantages from context-awareness and self-adaptation capabilities of NGSON. A use case analyis have been carried out on an experimental testbed about the effectiveness of the proposed approach in differentiating service data processing while optimizing the use of forwarding tables in the switches.

Nowadays, Data Centers are the primary infrastructures for Cloud Computing services provisioning. In this challenging scenario, Data Centers have to deal with highly dynamic workloads, thus not only should they adopt advanced software virtualization solutions, but also network control capabilities. Elastic, agile network connectivity control should be integrated with the computing management infrastructure to make it achieve its goals. This paper presents an OF-based controller, called OFVN, that enables novel virtualization-aware networking functions in Cloud DCs. Virtual Machines allocations are performed considering the availability of computational resources on physical server, but also selecting a forwarding path for VMs data flows based on network links utilization. The focus of the paper is on the implementation and assessment of the controller in an experimental testbed. The behaviour of different allocation strategies is also investigated.

Path Computation Element (PCE) architecture enables effective traffic engineering in multi-domain networks while limiting the exposure of intra-domain information. However, returned path computations might reveal confidential information if artfully correlated by a malicious PCE. Thus, the selection of domains sequence as the result of PCEs cooperation should depend not only on the capability of providing quality paths but also on factors related to expected revenues or perceived risks. In this scenario, cooperation among PCEs could benefit from a trust model by evaluating the quality of the past interactions. This work introduces the concepts of Quality of Interaction and trust ranking and elaborates a trust management model including effectiveness and security objectives regulating the cooperation among PCEs. Specifically, the proposed trust model aims at stimulating effective interactions among PCEs as a result of a common interest in contributing to successful and profitable path computations while avoiding misuse of path computation services. The simulation results show that our trust model is effective in detecting malicious PCE thereby tuning the amount of information returned in the path computation replies.

Oversubscription of intra-Data Center network links and high volatility of VM deployments require a flexible and agile control of Data Center network infrastructures, also integrated with computing and storage resources. In this scenario, the Software-Defined Network paradigm and, specifically, the OpenFlow protocol, opens up new opportunities for the design of innovative resource management platforms that enable dynamic and fine-grain control of DC networks through traffic engineering algorithms. This paper investigates the performance of two different sets of cloud-fluent traffic engineering algorithms. Conceived to work during cloud service deployments, the main target of such algorithms is to achieve a better utilization of network resources by exploiting OpenFlow capabilities for traffic-aware deployments of Virtual Machines. The effectiveness of the proposed solutions is evaluated in terms of network link utilization against VM requests acceptance ratio through simulations and experimental tests carried out by using an ad-hoc emulator.

This demo deals with a new orchestrator, the OFVN controller, specifically designed, according to the SDN principles, to deliver Cloud services with IT and network resources requirements.

The need to preserve information confidentiality among network providers has prevented the actual deployment of effective Traffic Engineering (TE) solutions for QoS-enabled end-to-end connectivity services in multi-domain multi-provider networks. The use of Path Computation Element (PCE) architecture can foster the effective implementation of TE through a centralized engine devoted to end-to-end path computations. However, despite authentication, authorization and encryption, confidentiality issues may arise due to abuses of information included in path computation replies to bogus requests issued by malicious PCEs. This paper first demonstrates the security leak allowing the exposure of intra-domain information in current inter-PCE path computation procedures. Then it proposes an anomaly-based approach, namely PCE Anomaly Detector (PAD) in order to detect malicious utilization of path computation services. The proposed PAD employs a novel double-step multi-dimensional formulation based on the Sequential Hypothesis Testing (SHT) statistical classification procedure, able to recognize a suspicious sequence of requests while aiming at inferring confidential information about other domains. PAD is extensively evaluated through simulations. Results show good performance in terms of detection capabilities while guaranteeing the trade-off between accuracy and responsiveness, minimizing false alarm occurrences. Robustness against smart attacks is also proved with respect to a comprehensive set of attack patterns and under different network load conditions. Finally, intra-domain information exposition is evaluated, showing the PAD ability to preserve confidentiality.

The joint management of IT and network resources is a key aspect for dynamic inter-data center interconnection networks designed to work according to the cloud computing paradigm. Such a scenario calls for the anycast routing of service requests to find a data channel that best suits both connectivity and IT resource requirements. This paper presents different network resource allocation and release policies across an inter-data center interconnection network aimed at a balanced accommodation of network resources to improve performance. Such policies are evaluated and compared in terms of service set-up blocking probability considering also configuration latency of real network devices that play a significant role along with network bandwidth availability across the network. Results show that the best choice is to release network resources as soon as possible, even though this means increasing the service blocking due to network reconfiguration latency.

Inter-domain traffic engineering solutions based on the Path Computation Element (PCE) architecture are exposed to information confidentiality issues between network carriers. Licit PCE Protocol (PCEP) request sequences may hide a malicious intention to discover critical intra-domain information through correlations among replies. This work presents an innovative anomaly-based statistical approach based on the Sequential Hypothesis Testing (SHT) aiming to detect malicious utilization of PCEP by peer clients. A novel combined multi-feature SHT formulation is presented in combination with different decision policies for definitely ascertaining whether the behavior of the Path Computation Client (PCC) is malicious or not. Simulation results show improved performance in terms of detection and falsealarms probabilities while guaranteeing a trade-off between detection accuracy and delay.

This work presents a signaling framework for the Future Internet capable of enabling unified network and IT resource allocation. The proposed signaling scheme is based on existing technologies and carried out through extensions to protocols already operated in current Internet, i.e., SIP, and by resorting to source-initiated GMPLS signaling without introducing network technology- dependent mechanisms. The experimental validation presented in this work has been carried out on a real test-bed. Performance of the service set-up procedure are reported taking into account the response time of real life devices such as commercial routers and protocols. The results provided show that the architecture proposed is compliant with conventional performance levels such as those set by the ITU- T. Finally, scalability performance have been verified by stressing the system with increasing rate of simultaneous service requests.