To address the challenges posed by the deployment of microservices of future end-user applications in the cloud continuum, a performance prediction model working together with a network elasticity controller will be needed. With that aim, this work introduces Layered Queuing-Graph Neural Networks (LQ-GNN), a novel Machine Learning (ML) approach to develop a generalized performance prediction model for microservicebased applications. Unlike previous works focused on individual applications, our proposal aims for a versatile model applicable to any microservice-based application, integrating the Layered Queueing Network (LQN) modeling with Graph Neural Networks (GNN). LQ-GNN allows to efficiently estimate the response time of applications under different resource allocations and placements on the computing continuum. The obtained evaluation results indicate that the proposed model achieves a prediction error below 10% when considering different evaluation scenarios. Compared to existing methodologies, our approach balances prediction accuracy and computational efficiency, making it viable for real-time deployments. Consequently, ML-based performance prediction can significantly enhance the resource management and elasticity control of microservice-based architectures, leading to more resilient and efficient systems.

Future applications to be supported by 6G networks are envisaged to be realized by loosely-coupled and independent microservices. In order to achieve an optimal deployment of applications, smart resource management strategies will be required, working in a cost-effective and resource-efficient manner. Current cloud computing services are challenged to meet the explosive growth and demand of future use cases such as virtual/augmented/mixed reality (VR/AR/MR). The purpose of edge computing (EC) is to better address latency and transmission requirements of those future stringent applications. However, a high flexibility and a rapid decision-making will be required since EC suffers from limited resources availability. For this reason, this work proposes an artificial intelligence (AI) technique, based on reinforcement learning (RL), to make intelligent decisions on the optimal tier and edge-site selection to serve any request according to the application’s category, constraints, and conflicting costs. In addition, when deployed at the edge-network, a heuristic has been proposed for the mapping of microservices within the selected edge-site. That heuristic will exploit a ranking methodology based on the network topology and available network and compute resources while preserving the revenue of the mobile network operator (MNO). Simulation results show that the performance of the proposed RL approach is close to the optimal solution by reaching the cost minimization objective within a 8.3% margin; moreover, RL outperforms considered benchmark algorithms in most of the conducted experiments.

Cognizant of the ease with which softwarized functions can be dynamically scaled according to real time resource requirements, and the fact that multiple services can have common VNFs in their chaining, this paper tackles the problem of cost effective deployment of online services from the perspective of sharing their VNF instances. First, we formally formulate the deployment problem under VNFs sharing. Secondly, given the NP-hard nature of the above problem, we propose a reinforcement learning (RL) algorithm capable of making intelligent placement decisions while considering multiple conflicting costs. Costs of transmission, VNF instantiation or energy consumption, among others. Thanks to the intelligence of the RL algorithm, simulation results show that the performance of the proposed algorithm is within a 14% margin and similar to an optimal solution in terms of request provisioning cost and acceptance ratio, respectively. Moreover, the algorithm results in more than a 20% and a 70% improvement in terms of request deployment cost and time compared to a state-of-the-art algorithm, and up to more than a 40% improvement in terms of cost compared to an algorithm that greedily minimizes the transmission or VNF activation costs.

This work tackles the problem faced by network/infrastructure providers of jointly selecting routing and functional split level to satisfy requests from virtual mobile network operators (vMNOs). We build a novel system model that brings together all the involved elements and features, embracing split levels defined by the 3GPP and packet switch fronthaul network. To our best knowledge, this is the first work that provides a solution for multiple vMNO requests considering the two aforementioned sub-problems (i.e., split selection and routing). We use the model defined to formulate an optimization problem, which is characterized by the exponential size of its search space. We propose two heuristic approaches to address this problem: (1) a greedy scheme, and (2) an evolutionary algorithm, which is also improved with a specialized initialization. We conduct extensive experiments to assess the performance and behavior of the proposed methods, over varying network instances. When possible, we also perform comparisons with respect to the optimal solution and a well-known commercial solver. Our results indicate that the proposed techniques represent appropriate trade-offs between solution quality and execution time, and can serve complementary goals: the quality of the results yielded by our evolutionary method are better, but at the cost of longer execution times; in contrast, our greedy algorithm offers a reasonably appropriate performance, with an execution time that is notably lower. Our experiments show that it is possible to produce near-optimal results to the above complex problem through computationally efficient algorithmic solutions.

The traditional telecommunications business is evolving towards offering a richer set of services beyond basic connectivity, leveraging on network programmability and virtualization. A versatile execution environment is required, capable of running different workloads in different locations in the network. Cloud computing is the key paradigm that allows fostering this trending change. One interesting question to solve is to what extent those computing environments have to move towards the network edge. Some services can be enabled by environments with increased capillarity, while others can be implemented in environments with more relaxed constraints (e.g., in terms of latency). This paper explores this topic by differentiating service edge from physical network edge and proposing an architecture based on the ALTO server for assisting orchestration systems in discriminating the suitable environments for each service. We present a network-flow strategy for assigning services to infrastructure elements following those precepts, together with an initial scalability evaluation of the proposed assignment solution to show its feasibility.

To support future 5G computing and communication scenarios, cloud-network management tools should deploy cloud-network services adopting uncomplicated ways, reducing not only the time to market but also broadening the community capable of deploying new services. In this paper, we present the support of NECOS Platform, an EU-Brazil jointly funded project, towards slice-as-a-service creation from non-structured service description. We describe how NECOS architecture allows such functionality during the slice creation loop, and we present the initial efforts we took for structuring such a mechanism.

Network slicing has recently been proposed as one of the main enablers for 5G networks; it is bound to cope with the increasing and heterogeneous performance requirements of these systems. To "slice" a network is to partition a shared physical network into several self-contained logical pieces (slices) that can be tailored to offer different functional or performance requirements. Moreover, a defining characteristic of the slicing paradigm is to provide resource isolation as well as efficient use of resources. In this context, the thesis described in this paper contributes to the problem of slicing WiFi networks by proposing a solution to the problem of enforcing and controlling slices in WiFi Access Points. The focus of the research is on a variant of network slicing called QoS Slicing, in which slices have specific performance requirements. In this document, we describe the two main contributions of our research, a resource allocation mechanism to assign resources to slices, and a solution to enforce and control slices with performance requirements in WiFi Access Points.

Network slicing has recently been proposed as one of the main enablers for 5G networks. The slicing concept consists of the partition of a physical network into several self-contained logical networks (slices) that can be tailored to offer different functional or performance requirements. In the context of 5G networks, we argue that existing ubiquitous WiFi technology can be exploited to cope with new requirements. Therefore, in this paper, we propose a novel mechanism to implement network slicing in WiFi Access Points. We formulate the resource allocation problem to the different slices as a stochastic optimization problem, where each slice can have bit rate, delay, and capacity requirements. We devise a solution to the problem above using the Lyapunov drift optimization theory, and we develop a novel queuing and scheduling algorithm. We have used MATLAB and Simulink to build a prototype of the proposed solution, whose performance has been evaluated in a typical slicing scenario.

Network Function Virtualization (NFV) and Machine Learning (ML) are envisioned as possible techniques for the realization of a flexible and adaptive 5G network. ML will provide the network with experiential intelligence to forecast, adapt and recover from temporal network fluctuations. On the other hand, NFV will enable the deployment of slice instances meeting specific service requirements. Moreover, a single slice instance may require to be deployed across multiple substrate networks; however, existing works on multi-substrate Virtual Network Embedding fall short on addressing the realistic slice constraints such as delay, location, etc., hence they are not suited for applications transcending multiple domains. In this paper, we address the multi-substrate slicing problem in a coordinated manner, and we propose a Reinforcement Learning (RL) algorithm for partitioning the slice request to the different candidate substrate networks. Moreover, we consider realistic slice constraints such as delay, location, etc. Simulation results show that the RL approach results into a performance comparable to the combinatorial solution, with more than 99% of time saving for the processing of each request.

In forthcoming 5G networks, slicing has been proposed as a means to partition a shared physical network infrastructure into different self-contained logical parts (slices), which are set up to satisfy certain requirements. Although the topic has been thoroughly investigated by the scientific community and the industry, there are not many works addressing the challenges that appear when trying to exploit slicing techniques over WiFi networks. In this paper, we propose a novel method of allocating resources for WiFi networks to satisfy minimum bit rate requirements. We formulate an optimization problem, and we propose a solution based on the theory of Lyapunov drift optimization. The validity of the proposed solution is assessed by means of a simulation-based evaluation in Matlab.

Virtual network embedding (VNE) has attracted a lot of attention in the last decade. Nevertheless, recent analysis demonstrates that the performance of VNE solutions in key metrics like virtualized network acceptance ratio decreases drastically with medium-to-large sizes of substrate and virtual networks. This paper proposes a constraint management approach that grades the quality of VNE candidate solutions according to the degree of fulfillment of their constraints and exploits this information to drive the metaheuristics to more promising regions of the search process enhancing their performance. Through simulation and formal statistical analysis, our approach has been proved to enhance VNE acceptance ratio practically at no time overhead. Formal statistical analysis and comparison with the literature demonstrate that our approach enhances the quality of embeddings and that such enhancements are more accentuated in large sizes of substrate networks, where the performance of standard metaheuristics decreases drastically.

Network slicing has recently appeared as one of the most important features that will be provided by 5G networks and is attracting considerable interest from industry and academia. At the wireless edge of these networks, most of the contributions in this area are related to cellular technologies leaving behind WiFi networks. In this work, we present a resource allocation mechanism based on airtime assignment to achieve infrastructure sharing and slicing in WiFi Access Points. The approach is simple and has the potential to be straightforwardly used within scenarios of wireless access infrastructure sharing.

Network function virtualization (NFV) and software defined networking (SDN) have been proposed to increase the cost-efficiency, flexibility, and innovation in network service provisioning. This is achieved by leveraging IT virtualization techniques and combining them with programmable networks. By doing so, NFV and SDN are able to decouple the network functionality from the physical devices on which they are deployed. Service function chains (SFCs) composed out of virtual network functions (VNFs) can now be deployed on top of the virtualized infrastructure to create new value-added services. Current NFV approaches are limited to mapping the different VNF to the physical substrate subject to resource capacity constraints. They do not provide the possibility to define location requirements with a certain granularity and constraints on the colocation of VNF and virtual edges. Nevertheless, many scenarios can be envisioned in which a service provider (SP) would like to attach placement constraints for efficiency, resilience, legislative, privacy, and economic reasons. Therefore, we propose a set of affinity and anti-affinity constraints, which can be used by SP to define such placement restrictions. Furthermore, a semantic SFC validation framework is proposed that allows the virtual network function infrastructure provider (VNFInP) to check the validity of a set of constraints and provide feedback to the SPs. This allows the VNFInP to filter out any non-valid SFC requests before sending them to the mapping algorithm, significantly reducing the mapping time.

New architectural and design approaches for radio access networks have appeared with the introduction of network virtualization in the wireless domain. One of these approaches splits the wireless network infrastructure into isolated virtual slices under their own management, requirements, and characteristics. Despite the advances in wireless virtualization, there are still many open issues regarding the resource allocation and isolation of wireless slices. Because of the dynamics and shared nature of the wireless medium, guaranteeing that the traffic on one slice will not affect the traffic on the others has proven to be difficult. In this paper, we focus on the detailed definition of the problem, discussing its challenges. We also provide a review of existing works that deal with the problem, analyzing how new trends such as software defined networking and network function virtualization can assist in the slicing. We will finally describe some research challenges on this topic.

The virtualization of Radio Access Networks (RANs) has been proposed as one of the important use cases of Network Function Virtualization (NFV). In Virtualized Radio Access Networks (VRANs), some functions from a Base Station (BS), such as those which make up the Base Band Unit (BBU), may be implemented in a shared infrastructure located at either a data center or distributed in network nodes. For the latter option, one challenge is in deciding which subset of the available network nodes can be used to host the physical BBU servers (the placement problem), and then to which of the available physical BBUs each Remote Radio Head (RRH) should be assigned (the assignment problem). These two problems constitute what we refer to as the VRAN Placement and Assignment Problem (VRAN-PAP). In this paper, we start by formally defining the VRAN-PAP before formulating it as a Binary Integer Linear Program (BILP) whose objective is to minimize the server and front haul link setup costs as well as the latency (or distance) between each RRH and its assigned BBU. Since the BILP could become computationally intractable, we also propose a greedy approximation for larger instances of the VRAN-PAP.

The popularity of multimedia services offered over the Internet have increased tremendously during the last decade. The technologies that are used to deliver these services are evolving at a rapidly increasing pace. However, new technologies often demand updating the dedicated hardware (e.g., transcoders) that is required to deliver the services. Currently, these updates require installing the physical building blocks at different locations across the network. These manual interventions are time-consuming and extend the Time to Market of new and improved services, reducing their monetary benefits. To alleviate the aforementioned issues, Network Function Virtualization (NFV) was introduced by decoupling the network functions from the physical hardware and by leveraging IT virtualization technology to allow running Virtual Network Functions (VNFs) on commodity hardware at datacenters across the network. In this paper, we investigate how existing service chains can be mapped onto NFV-based Service Function Chains (SFCs). Furthermore, the different alternative SFCs are explored and their impact on network and datacenter resources (e.g., bandwidth, storage) are quantified. We propose to use these findings to cost-optimally distribute datacenters across an Internet Service Provider (ISP) network.

In this paper we propose the use of a two-agent learning scheme for the management of radio resources on cellular access networks. The management is materialized by the implementation of a self-configuration system governing the setup of several parameters on each base station. The two agents have independent goals; one is trying to maximize the quality of service and the other the economic benefit. Thanks to the combined use of the fuzzy logic technique and reinforcement learning, both agents will work in a complementary mode, achieving both goals simultaneously.

Network virtualisation is a promising technique for dealing with the resistance of the Internet to architectural changes. This is achieved by enabling a novel business model in which infrastructure management is decoupled from service provision. One of the main challenges in network virtualisation is efficient sharing of physical network resources by the different virtual networks. This work contributes to efficient resource sharing in network virtualisation by dividing the resource management problem into three sub-problems: virtual network embedding (VNE), dynamic resource allocation (DRA), and virtual network survivability (VNS); and then proposing a solution for each one of them. Specifically, we propose a path generation-based approach for VNE, machine learning-based self-management approaches for DRA, and a multi-entity negotiation algorithm for VNS. Through simulations, all our proposals are compared with related approaches, showing improvements in resource utilisation efficiency, which would directly result into better profitability for physical resource owners.

Network function virtualization has received attention from both academia and industry as an important shift in the deployment of telecommunication networks and services. It is being proposed as a path towards cost efficiency, reduced time-to-markets, and enhanced innovativeness in telecommunication service provisioning. However, efficiently running virtualized services is not trivial as, among other initialization steps, it requires first mapping virtual networks onto physical networks, and thereafter mapping and scheduling virtual functions onto the virtual networks. This paper formulates the online virtual function mapping and scheduling problem and proposes a set of algorithms for solving it. Our main objective is to propose simple algorithms that may be used as a basis for future work in this area. To this end, we propose three greedy algorithms and a tabu search-based heuristic. We carry out evaluations of these algorithms considering parameters such as successful service mappings, total service processing times, revenue, cost etc, under varying network conditions. Simulations show that the tabu search-based algorithm performs only slightly better than the best greedy algorithm.

In this work we focus on the application of an intra-flow linear random coding scheme over wireless mesh networks. We propose a cross-layer technique to balance the load between relaying nodes, considering the quality of the wireless links. We assess the performance of our proposal by means of an extensive simulation campaign carried out over the ns-3 platform, exploiting a channel model based on a Hidden Markov Process, which accurately mimics the bursty behavior that is observed over real indoor channels. The results show the benefits of the proposed cross-layer technique. In addition, we also discuss the trade-off (between accuracy and overhead) that needs to be considered when obtaining the information that such scheme rely on. Our simulations yield a 10% performance gain when exploiting the link quality information, as it is already obtained by various routing protocols.

As the virtualization of networks continues to attract attention from both industry and academia, the virtual network embedding (VNE) problem remains a focus of researchers. This paper proposes a one-shot, unsplittable flow VNE solution based on column generation. We start by formulating the problem as a path-based mathematical program called the primal, for which we derive the corresponding dual problem. We then propose an initial solution which is used, first, by the dual problem and then by the primal problem to obtain a final solution. Unlike most approaches, our focus is not only on embedding accuracy but also on the scalability of the solution. In particular, the one-shot nature of our formulation ensures embedding accuracy, while the use of column generation is aimed at enhancing the computation time to make the approach more scalable. In order to assess the performance of the proposed solution, we compare it against four state of the art approaches as well as the optimal link-based formulation of the one-shot embedding problem. Experiments on a large mix of virtual network (VN) requests show that our solution is near optimal (achieving about 95% of the acceptance ratio of the optimal solution), with a clear improvement over existing approaches in terms of VN acceptance ratio and average substrate network (SN) resource utilization, and a considerable improvement (92% for a SN of 50 nodes) in time complexity compared to the optimal solution.

This paper presents a methodology used to create a site independent assessment process of the capabilities of service management systems in federated e-infrastructures that can contribute to introduce or improve service management in these application domains. Based on ISO/IEC 20000 concepts it consist of an actors and relationships model, a set of management processes with their corresponding requirements and a capability model that all converge in an easy to use assessment tool. The methodology has been evaluated through its adoption in an existing federated e-infrastructure.

Network virtualisation is considerably gaining attention as a solution to ossification of the Internet. However, the success of network virtualisation will depend in part on how efficiently the virtual networks utilise substrate network resources. In this paper, we propose a machine learning-based approach to virtual network resource management. We propose to model the substrate network as a decentralised system and introduce a learning algorithm in each substrate node and substrate link, providing self-organization capabilities. We propose a multiagent learning algorithm that carries out the substrate network resource management in a coordinated and decentralised way. The task of these agents is to use evaluative feedback to learn an optimal policy so as to dynamically allocate network resources to virtual nodes and links. The agents ensure that while the virtual networks have the resources they need at any given time, only the required resources are reserved for this purpose. Simulations show that our dynamic approach significantly improves the virtual network acceptance ratio and the maximum number of accepted virtual network requests at any time while ensuring that virtual network quality of service requirements such as packet drop rate and virtual link delay are not affected.

The current Internet does not enable easy introduction and deployment of new network technologies and services. This paper aims to progress the Future Internet (FI) by introduction of a service composition and execution environment that re-use existing components of access and core networks. This paper presents essential service-centric platforms and software systems that have been developed with the aim to create a flexible environment for an Autonomic Internet.

Several intra- and inter-domain quality of service (QoS) provisioning mechanisms for IP networks have been researched and developed using Differentiated Services (DiffServ) technology. However, the incremental efforts needed to manage DiffServ networks from a business-oriented viewpoint have received relatively little attention. This paper addresses this gap and presents a framework for achieving business-driven QoS provisioning in DiffServ over MPLS networks. We provide a rich model of SLA and business indicators as well as reasonable mapping functions that define, with key degrees of importance, the impact of business indicators over service management policies. Business and service indicators are used to control static and dynamic admission of services. The paper advances the state of the art by considering the influence of business-level objectives on the policy refinement process. We evaluate and discuss the effectiveness of our approach through a simulation environment that we developed over OPNET.

This paper proposes an algorithm that enables the support for a service market place in which service providers can negotiate and form coalitions in a self-centred approach. We present the main features of the algorithm and evaluate the proposed solution under different technical aspects including social network topology, scalability and convergence to optimal results.

Ontology engineering has been proposed as a formal mechanism for both reducing the complexity of managing the information needed in network management and autonomic systems and for increase the portability of the services across homogeneous and heterogeneous networks. In this paper we propose an ontology for supporting the creation, delivery and management of context-aware services and also for the integration of the user's context information in service management operations for heterogeneous networks. This ontology provides formal semantics that capture concepts of context information for helping in the service management operations and also augments the information model for adding domain-specific user's context data. Using this ontology, we have created a "knowledge plane" that supports the reasoning needed by autonomic networks. We have studied the use of ontology autonomic elements for gathering raw context and integrating it to improve and/or enhance the user's context representation. Finally, we provide a study and analysis for ensuring the efficient handling and dissemination of context information to overlay applications in autonomic environments for self-managing or self-configuring service operations.

Current Web services are able to interoperate successfully with most basic data types. However, due to the limited functionality of existing data binding tools, they still experiment difficulties manipulating more complex XML data types, forcing programmers to work at the XML level. In this paper we propose a business model for web services where data binding tools not only generate the WSDL, but also provide portable binding extensions for manipulating theXSD types. These binding extensions can be integrated into any other binding tool, overcoming their limitations. Because these extensions are written in XML, this model conforms to the principle of platform independence. In addition, this model does not suppose any extra programming effort to neither service providers or clients. The approach has been validated with the creation of several extensions, which has been ported into Java and PHP clients. Our preliminary results show no performance penalty.

The Madeira project, part of the Celtic Initiative1, investigates the use of a fully distributed, policy-based network management framework that exploits the peer-to-peer paradigm with the aim of providing a successful solution to Next Generation Networks (NGN) challenges. This paper is focused on the distributed policy-based approach adopted in the project. Thanks to this approach, the management system is flexible and adaptable to different management applications of networks with time-varying topologies. Currently available results coming from the execution of specific scenarios in the area of Fault Management reveal that the policy-based system architecture works properly in the highly distributed peer-to-peer environment where it is deployed.

Goal-oriented requirements engineering methodologies have been suggested as an alternative to address the policy refinement paradigm. Moreover, practical approaches that capture the administrative and technical requirements to make policy refinement a systematic process are still missing although such integrated solutions are rather convenient to make policy-based management systems really useful. In this paper, we present GOREMOCH, a goal-oriented policy refinement environment grounded in goal-oriented requirements engineering methodologies, linear temporal logic and reactive systems analysis techniques. We describe the rationale of this integrated solution and the necessary mechanisms to achieve policy refinement in a systematic manner

The nature of the integral communications each time more oriented to mobile services, requires new technologies and platforms conceived for supporting the services in a more dynamic, adaptive and efficient way. This opens the road to the Context-Aware Services, applications that change with the dynamism of the information from users and services. To support these applications, programmable networks emerge as the next generation networks support. This paper introduces an architecture for managing Context-Aware Services in next generation networks using the facilities of programmable networks. The work and the results come from EU CONTEXT IST-Project, in which the creation of a context information model, for achieving a consistent representation of the context and the policy methodology for creating and managing efficiently context-aware services, play an important roll for providing to users and the operators operational supports for managing pervasive services.

The Madeira project addresses a novel approach for the management of network elements of increasing number, heterogeneity and transience. As next-generation networks exhibit major challenges for today's centralized network management systems, we investigate the feasibility of a peer-to-peer (P2P) approach, facilitating self-management and dynamic behavior of elements within networks. In this short paper we give an overview of the system architecture developed in Madeira and describe the key concepts, like Madeira platform services, Adaptive Management Components and policies that provide the base for building distributed network management applications.

This paper presents an alternative method to setup label switched paths (LSPs) with quality of service (QoS) constraints in multiprotocol label switching (MPLS) enabled networks. The motivation behind this work is to gather the advantages of the control plane based approach and the management plane based approach to establish LSPs. In other words we aim for a mechanism with setup times as shorter as those realizable by control plane signalling and with traffic engineering capabilities as powerful as in management systems. The concept has been prototyped and initial tests have been performed in a simulated network environment. The outcome of these tests show that our system can be nearly as fast as conventional control plane setup mechanisms and by construction it can take advantage of all the network information got by the management plane for constrained-based routing (CBR) purposes. Therefore, a trade-off between speed and resource optimisation is feasible. The implementation of the concept in real networks requires platforms with standard control and management interfaces, that have the role of peer network nodes and management agents at a time.

Individual wireless access networks show limitations that can be overcome through the integration of different technologies into a unified platform [i.e., fourth-generation (4G) system]. Nevertheless, the integration of heterogeneous networks poses many challenges such as adding complexity to the processes of deciding when to handoff, selecting the best network, and minimizing roaming effects using appropriate handover methods. This paper presents PROTON, a novel solution that supports decision-making processes related to roaming between heterogeneous technologies. PROTON deploys a formal policy representation model, based on finite-state transducers, that evaluates policies using information from the context to manage mobiles' behavior in a transparent manner, hiding 4G systems' complexities. We blend concepts of autonomic computing into the design of the solution and manage to improve user experience in typical 4G scenarios, while keeping transparency.

By constraining the output rate of mobile hosts in a cell via DiffServ configuration mechanisms, it is possible to keep 802.11 networks in a non-saturation state. We present a policy-based management solution for video streaming service provisioning and the system evaluation as a feasible alternative to contribute providing QoS in real time services in wireless environments. A prototype intended for proof of concept has been evaluated in a simulated WLAN making use of real video applications.

In order to bring together the higher speed of WLAN and the wider coverage of GPRS, solution from service's perspective is necessary. And this kind of integrated service should be context-aware in order to automatically adapt itself to the changing environment. This paper proposes to explore the applicability of using network-centric context-aware service to integrate WLAN and GPRS network environments. Starting from typical scenario description and requirement analysis, a policy-based context model is presented, which takes into account the real implementation of context-aware service in the underlying networks. A context-aware service scenario called modern professor is explored to exemplify this methodology based on the policy-based context-aware service system architecture.

This paper examines the different approaches for the provisioning of Internet services over the optical layer. Most of the research in the area is focused in the control plane by extending the distributed Internet network control approach to the optical layer using signalling mechanisms either in an overlay model or a peer model. In addition, this paper proposes a novel paradigm for providing Internet services over the optical transport network, in which the management plane takes the leading role and the control plane is used for secondary supporting actions. The paradigm extends the telecom-style network management approach to the IP layer through the use of MPLS, which may be treated as a connection-oriented technology. The appropriate synergy and integration of the MPLS and WDM layers is performed with management functions capable of performing integrated provisioning of label switched paths over optical channels (lambdas), as well as integrated multi-layer fault and performance management. This approach is a midterm solution until the control mechanisms become technically and market-wise mature and gradually dominate the IP over optical area pushing the management plane to a secondary role, mostly for visualising/monitoring the control plane. The proposed management solution has been adopted and implemented by WINMAN, an ongoing European research and development project, whose aim is to offer an integrated network management solution for the provisioning of end-to-end IP connectivity services derived from service level agreements (SLAs).

This paper describes the policy-based management architecture devised for management of IP over WDM networks and is part of the work carried out in the IST Project WINMAN, whose aim is to develop and validate an open and flexible integrated management system for this type of networks. The IETF has been working in the policy based management area, through two of its groups, in order to provide the means for managing IP based networks, offering some QoS guarantees. At the same time hybrid networks such as those placing IP directly over WDM are emerging as the solution to the increasing need for bandwidth. Management of such networks in an integrated fashion is a large research area. We are interested in integrating the policy management paradigm for managing integrated networks, such as IP over WDM networks.

This paper outlines the initial architectural results of WINMAN, an European research and development project started in July 2000, whose aim is to offer an integrated network management solution for the provisioning and maintenance of IP over WDM end-to-end transport services derived from service level agreements (SLAs). Management requirements for IP over WDM have been identified and a two-tier architecture has been conceived for the system that is intended for proof concept of the WINMAN solution. The first layer contains the technology dependent managers, that is one for the IP technology and another manager for the WDM. These two management systems will interact with existing network element management systems the southbound WINMAN interface. On top of this layer there is a second interface whose purpose is the integration of the above mentioned management systems. This system will be in turn integrated in different experimental test beds and fully tested in real life conditions.

This contribution presents a prototype of network management framework based on distributed plug-in component technology. The main innovative aspect is the exhibited capacity to facilitate network management applications to be reconfigured at runtime by changing the communication channels used by the constituent components to communicate. This adds great flexibility because the system functionality is not "closed" at the system design time. The ensemble constitutes a development framework for component-based management applications. A scenario is presented to demonstrate the system in action.

The specification and implementation of Xcoop interfaces has received great attention in the last few years. In fact, the appropriate design of this system component is a key aspect for efficient and seamless co-operative management. In this context it is worth mentioning the EURESCOM P408 project and the standards of the European Telecommunication Standards Institute (ETSI) in Europe and the ITU-T and Telemanagement Forum related work worldwide. The Xcoop specification presented in this paper, produced as part of the results of the project MISA co-funded by the Commission of the European Union, is a step ahead in the evolution of this system interface. Distinguished from preceding works, this one allows interactions between management systems independently to the underlying network technology, ATM, SDH or hybrid. This is achieved by defining appropriate functionality and an information model, indeed, where the specific characteristics of ATM and SDH resources are abstracted and merged in common classes.