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 field of Intent Based Networking (IBN) has recently focused on the use of systems powered by Generative Artificial Intelligence and Large Language Models (LLMs) to generate and configure the network. While being a powerful tool to assist Network Administrators, these methods are far from perfect. They tend to hallucinate and generate bad or sub-optimal configurations. To avoid these problems, we propose the integration of Test-Driven development to the world of Softwarized Networks, as a feedback for automated assistants such as LLMbased configuration generator, leveraging technologies such as Atomic Predicates (AP) and Retrieval Augmented Generation (RAG). In this paper, we describe the usage of an assistant over a softwarized network, making it work in conjunction with Network Policy Enforcement, generating an effective Test-Driven Development for Softwarized Network. Our findings highlight the potential of these combined approaches, mutually benefit each other to reach the goal of a powerful co-pilot for Complex Network Configuration.

Intent-Based Networking (IBN) has simplified network management and orchestration at a high level, but configuring User Equipment (UE), like 5G modems, is still a complex and demanding task due to dynamic requirements and intricate device-specific settings, and scalability challenges, especially when dealing with distributed, edge-based devices. This paper explores the potential of using Intelligent Chatbots powered by Generative Artificial Intelligence and Large Language Models (LLMs) operating as co-pilots to automate and optimize modem configurations. We propose a scalable chatbot system that translates user intents into actionable configurations, enhancing security, performance, and adaptability. To this end, we introduce a middleware that bridges LLMs with 5G Modem interfaces, eliminating retraining needs while ensuring engaging, real-time interaction with users. Additionally, we analyze key challenges in integrating LLM-based chatbots with UE and discuss the benefits of query caching in optimizing response times. Our findings highlight the potential of Intelligent Chatbots in extending IBN principles to UE, enabling a more automated and user-friendly approach to network configuration.

This paper presents a comparative analysis of novel LLM-based architectures designed specifically for system configuration purposes. Generative Artificial Intelligence (Gen AI) has rapidly evolved, offering transformative capabilities in content generation across various domains. Large Language Models (LLMs) stand at the forefront of this evolution, revolutionizing natural language understanding and enabling sophisticated conversational systems. Leveraging the potential of LLMs, our study introduces a novel system architecture centered around an intelligent chatbot tailored to assist learners in complex network configurations. By integrating Generative Pre-trained Transformer-based models with Retrieval Augmented Generation (RAG) and Function Calling features, our architecture aims to provide a co-pilot-like experience, guiding users through understanding requirements and generating configuration scripts. Through a comparative analysis of three LLM architectures, each tailored to handle system network configuration, we evaluate their effectiveness, strengths, and limitations. Our findings offer valuable insights into the potential applications of Generative AI in network operations and highlight avenues for future research and development.

Intent-based Networking (IBN) has emerged as an innovative approach to automate the provisioning of network services while simplifying the interaction between the users and the network, allowing users (e.g., administrators) to define high-level desired outcomes (i.e., intents), and translating expressed intents into automated network configurations. One of the main challenge in IBN is the correct acquisition of the user intents and subsequently the accurate translation into actionable configurations to enforce into the network. Despite some efforts in improving user-to-IBN system interaction, a gap still remains in ensuring satisfactory user experiences and contextually appropriate and coherent responses or translation results. To this purpose we consider using recent advancements in Generative AI, and in particular in Large Language Models, a promising approach to enhance IBN in the scope of intent acquisition and translation. Accordingly, this work investigates the integration of IBN systems with LLM-based Conversational Agents (i.e., intelligent chatbots), on the one hand to enhance the user experience while injecting intents and, on the other hand, to assure an accurate understanding of user intents and their translation into a coherent set of network configurations, which are generated automatically. The chatbot operation according to the proposed approach is illustrated in a DHCP configuration use case.

Intent-based networking has attracted interest in the academic research for enhancing network management operations with user-oriented features. One of the main challenge in this field is the acquisition of the user intents and subsequently the relative translation into policies for the automatic management of the network. Concerning this task, the primary technique employed is relying on Graphical User Interfaces (GUI)s. In addition, the use of Natural Language Processing techniques has been extensively adopted for improved user experience. Recently, some preliminary studies have shown that using Large Language Models (LLMs) for this purpose leads to achieve interesting results. However, based on a comprehensive analysis of the state of the art, it has emerged that the works utilizing the LLMs do not fully exploit all the capabilities these tools could potentially offer. For this reason, the doctoral work aims to address the following challenges: enhancing user experience through the utilization of intelligent chatbots, improving the correct understanding of user intents and ensuring the translation of user intentions into a coherent set of network configurations, which are generated automatically.

Tokenized Intelligence (TI) aims to enhance network performance by combining machine learning and blockchain-based tokenomics in software-defined networks (5G/6G). This paper examines the potential for incentivizing decentralized edge computing through economic rewards, which can facilitate the efficient training of AI models. TI enables the coordination of a decentralized network of nodes, which allows for collaborative sharing of resources and decreases the expenses linked to centralized cloud-based solutions. TI is utilized to design customized logical networks that effectively optimize the use of computing, storage, and networking resources within a common physical infrastructure. This framework, which is decentralized and distributed, speeds up data analysis and reduces delays. It also provides economic rewards for edge nodes that participate in model training activities. The core of TI lies in its ability to improve network slicing strategies, such as best effort, high availability, and low latency, while also incentivizing edge nodes based on their contributions to the training process of the machine learning model. This economic incentive mechanism guarantees the efficient allocation of resources according to the specific needs of machine learning applications, thereby enhancing overall network performance.

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 softwarization is one of the key enablers of the future Internet evolution, also supporting the road from the fifth generation (5G) to the next-generation communication systems, namely 6G, with their main objective of bringing hyper-connected experience to every corner of society.

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.

The Softwarization of networks is enabled by the SDN (Software-Defined Networking), NV (Network Virtualization), and NFV (Network Function Virtualization) paradigms, and offers many advantages for network operators, service providers and data-center providers. Given the strong interest in both industry and academia in the softwarization of telecommunication networks and cloud computing infrastructures, a series of special issues was established in IEEE Transactions on Network and Service Management, which aims at the timely publication of recent innovative research results on the management of softwarized networks.

Empowered bynetwork softwarization, 5G systems have become the key enabler to foster the digital transformation of the vertical industries by expanding the scope of traditional mobile networks and enriching the network service offerings. To make this a reality, we propose anautomationsolution for vertical services provisioning and hierarchical Service Level Agreement (SLA) management.Service scalingis one of the most essential operations to adapt the service deployments and resource allocations to ensure SLA fulfilment. Three different scaling levels are addressed in this work: application-, service- and resource-level. We have implemented our solution in a proof-of-concept of a virtualized mobile network platform, spanning over three geographically-distributed sites. To evaluate our solution, we leverage field tests, focusing onautomotive vertical servicescomprising a mission-critical application (collision-avoidance) and an entertainment one (video streaming). The results demonstrate the excellent performance of our solution, and its ability to automatically deploy vertical services and ensure their SLAs through different levels of service scaling.

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.

In this demo we show the functionalities of the Open Source MANO extended with advanced authorization capabilities able to enhance the security support in terms of preservation of virtual resources and slices integrity in a dynamic context of users, services and resources. The presented extension consists of a Usage Control System integrated with Open Source MANO enhancing traditional authorization operations with ongoing usage control on established slices, virtual resources and user behaviour by continuously reconsidering the granting of resources in light of mutable attribute of users, resources and environment (e.g., presence of viruses, set-up of weak passwords).

The softwarization of networks is enabled by the SDN (Software-Defined Networking), NV (Network Virtualization), and NFV (Network Function Virtualization) paradigms, and offers many advantages for network operators, service providers and datacenter providers. Given the strong interest in both industry and academia in the softwarization of telecommunication networks and cloud computing infrastructures, a series of special issues was established in IEEE Transactions on Network and Service Management, which aims at the timely publication of recent innovative research results on management of softwarized networks.

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.

Heterogeneity of current software solutions for 5G is heading for complex and costly situations, with high fragmentation, which in turn creates uncertainty and the risk of delaying 5G innovations. This context motivated the definition of a novel Operating Platform for 5G (5G-OP), a unifying reference functional framework supporting end-to-end and multi-layer orchestration. 5G-OP aims at integrated management, control and orchestration of computing, storage, memory, networking core and edge resources up to the end-user devices and terminals (e.g., robots and smart vehicles). 5G-OP is an overarching architecture, with agnostic interfaces and well-defined abstractions, offering the seamless integration of current and future infrastructure control and orchestration solutions (e.g., OpenDaylight, ONOS, OpenStack, Apache Mesos, OpenSource MANO, Docker, LXC, etc.) The paper provides also the description of a prototype that can be seen as a simplified version of a 5G-OP, whose feasibility has been demonstrated in Focus Group IMT2020 of ITU-T.

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.

The adoption of the virtualization paradigm in both computing and networking domains portends a landscape of heterogeneous service capabilities and resources pervasively distributed and interconnected and deeply integrated through the 5G network infrastructure. In this service ecosystem, dynamic service demand can be flexibly and elastically accomplished by composing heterogeneous services provisioned over a distributed and virtualized resource infrastructure. Indeed, with the term Virtual Functions we refer to virtual computing as well as network service capabilities (e.g., routers and middlebox functions provided as Virtual Network Functions). In order to cope with the increasingly resource intensive demand, these virtual functions will be deployed in distributed clusters of small-scale datacenters typically located in current exchanges at the network edge and will supplement those deployed in traditional large cloud datacenters. In this work we formulate the problem of composing, computing and networking Virtual Functions to select those nodes along the path that minimizes the overall latency (i.e. network and processing latency) in the above mentioned scenario. The optimization problem is formulated as a Resource Constrained Shortest Path problem on an auxiliary layered graph accordingly defined. The layered structure of the graph ensures that the order of VFs specified in the request is preserved. Additional constraints can be also taken into account in the graph construction phase. Finally, we provide a use case preliminary evaluation of the proposed model.

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.

Within the ITU-T next generation network (NGN) architecture, the resource admission control function (RACF) has been designated to perform the application-driven QoS control across both access and core networks. However, an actual RACF implementation acting on MPLS metro-core networks does not exist since RACF lacks of the capability to configure QoS policies on MPLS network nodes. This prevents an effective end-to-end QoS control in a metro-core scenario on a per-application basis. This work presents a specific implementation of RACF operating over an MPLS network domain. This RACF implementation is applied to a testbed where a video client application requests a real-time video data transfer from a video server through an MPLS network. The admission control is performed upon service request based on video requirements and network resource availability. The differentiated traffic treatment on per-flow basis is realized through setting of MPLS DiffServ-aware traffic engineering (TE) capabilities using the NETCONF protocol. Effective traffic differentiation is achieved in a multi-service network scenario and thus it validates NETCONF as candidate protocol for policy provisioning in MPLS networks.

The simple network management protocol (SNMP) Framework, is one of the most diffused and successful protocol for network management generally available in current network devices.This work studies the dynamic evolution of the SNMP management information based (MIBs) of commercial IP/MPLS routers and evaluates the effectiveness of the relevant implementation. In addition, it characterizes the MIB modules involved in the provisioning of a connectivity and investigates the compliance of MIB implementation as regard the standard specifications. The obtained results were achieved by means of a testbed comprising a software tool developed by the authors. In particular, these results revealed that current MIB implementations do not respect standard specifications in terms of accessibility of the MIB objects. In addition, MIB are often used as a database for storing implementation-specific information, not foreseen by standard specification, rather than to support router operations. Finally, it was found that the configuration of simple connectivity requires the creation and modification of hundreds of different MIB objects thus making the use of SNMP limited to the collection of management information and general notifications.

Next generation network (NGN) Release 1 is the ITU- T architecture for packet-switched networks that supports the provisioning of broadband and QoS-guaranteed multimedia services, such as Video on Demand and TV streaming, independently of the underlying network transport technologies. Control plane (CP)-enabled transport networks might be a candidate to support NGN services in the Metro/Core segment since are able to setup automatically connections. Typically, these networks are based on automatically switched optical network (ASON) architecture and/or on generalized multiprotocol label switching (GMPLS) protocol suite. This work presents a snapshot of the current status of standardization reached by the NGN architecture and proposes an NGN enhancement to include CP-enable transport networks among the NGN supported transport technologies. An NGN prototype implementing the proposed architectural enhancement is also presented as a proof of concept. The prototype highlights how set-up multimedia over IP (MoIP) services using GMPLS-controlled transport objects.

Applications such as grid computing, storage or video-on-demand may need the provisioning by a transport network of ad-hoc secure end-to-end connections with guaranteed bandwidth, latency and resilience. The service plane (SP) is a functional layer, proposed by the authors, that enhances the automatically switched transport network (ASTN) for the provisioning of network services with a level of abstraction suitable for being invoked by applications. This paper details the distributed signaling running in the SP that implements the SP service abstraction and network resources virtualization capabilities. In particular, it focuses on the design of the signaling architecture among the centralized and distributed entities of the SP for the provisioning of on-demand Layer 3 (L3) virtual private network (VPN). A specific SP implementation is also presented and it is demonstrated by a testbed in which a video client application requests an L3 VPN in order to be connected with a video server across an MPLS-based transport network.

This paper presents the architecture, some specific supporting functions and an experimental validation of a new functional plane, namely the service plane, for realizing an added-value service provisioning (e.g., grid connectivity) for telecommunication operators. First, it is shown as the service plane can be a viable solution for decoupling service and transport development, by masking the transport-related implementation details from the abstract request of a service by a customer or by a qualified application. To this purpose, the service plane exports a high-level interface for supporting application-initiated invocation of QoS-enabled virtual private networks (VPN) or connection-less services. As a significant use case for a grid user, a VPN set-up through the service plane is experimentally demonstrated. Second, some of the main functions that the service plane should support are presented in detail and experimentally assessed, namely a centralized topology discovery service (C-TDS) and path computation service (PCS). As an example, from a grid user perspective, the C-TDS can provide up-to-date information on the grid topology according to various levels of abstraction (physical topology, MPLS topology, and logical topology). Several techniques for the grid topology discovery and various update policies are investigated. PCS elaborates upon the logical topology obtained by TDS and runs linear programming (LP) formulations to identify optimal traffic engineering solutions according to specific objective functions. The combination of C-TDS and PCS represents an an enhanced level of network- awareness in the (network) middleware supporting global grid computing (i.e., grid computing in wide area networks). Experiments performed on IP/MPLS metropolitan network based on commercial routers exhibit a topology delivery performance within a time span in the order of a few seconds and a PCS operation in the order of ten seconds.

The control plane (CP) of transport networks consists in a set of entities, communicating through a signaling network, that is responsible for the set-up, release, supervision and maintenance of connections. Given the increased number of capabilities supported by the CP, the management of the CP, i.e. the ability of the management plane (MP) to keep under control the CP operation, is becoming an issue for network operators. Indeed, a proper information model (IM) for the CP is needed to support the management of the CP. In this paper we present a comprehensive proposal of an IM that represents both the CP network itself in terms of components and capabilities and the transport resources as perceived by the management plane (MP) through the CP. The methodology is based on critical review of the standardization efforts already done by ITU-T, TMF, and IETF in order to identify both convergence aspects and gaps that the proposed IM attempts to fill. Specifically, we extend the ITU-T Rec. G.8080 functional components for a CP node, by introducing new objects related to the CP interfaces and control information processing. We then propose a CP functional layering according to the switching capability of the controlled transport network, with the aim of improving the scalability of the CP management. Finally, we define a functional model for the management of routing and connectivity for multi domain scenarios. The contribution is organized in new IM fragments containing a set of managed objects that constitute the abstract representation of the CP network functionalities

In the last few years customers are willing to use broadband connections to support concurrent and heterogeneous services. At the same time telecommunication operators would like to use the same transport infrastructure (possibly with minor changes) to deliver these emerging services in an integrated way. To this purpose, enhancements of the existing ASTN architecture are proposed. Specifically the intelligent network conceptual model is used to introduce an intermediate layer, named service layer, to interface the network customer to a service-independent transport network. The service plane has the task of masking the transport-related implementation details from the abstract request of a service by a customer. In addition, the service layer inherently suggests the separation of the telecommunication operators role in two distinct activities: the network provider and the service provider. The proposed service-oriented architecture is described in terms of functional blocks and interfaces and it consists in an open framework subjects to be implemented using whatever technology, both hardware and software. For a proof of concept, a testbed, named SOON (service oriented optical networks) running the newly developed service-oriented software modules has been implemented as an example of direct interaction between customer and optical network for a dynamic service request. The validation of the architecture is done by demonstrating a working service, namely a virtual private network (VPN) service.