Serverless computing is a recently introduced deployment model to provide cloud services. The autoscaling of function instances allows adapting allocated resources to workload, so as to reduce latency and improve resource usage efficiency. However, autoscaling mechanisms could be affected by undesired ‘cold starts’ events, causing latency peaks due to spawning of new instances, which can be critical in edge deployments where applications are typically sensitive to latency. In order to regulate autoscaling of functions and mitigate the latency for accessing services, which may hinder the adoption of the serverless model in edge computing, we resort to the usage of reinforcement learning. Our experimental system is based on OpenFaaS, the most popular open-source Kubernetes-based serverless platform. In this system, we introduce a Q-Learning (QL) agent to dynamically configure the Kubernetes Horizontal Pod Autoscaler (HPA). This is accomplished via a QL model state space and a reward function definition that enforce service level agreement (SLA) compliance, in terms of latency, without allocating excessive resources. The agent is trained and tested using real serverless function invocation patterns, made available by Microsoft Azure. The experimental results show the benefits provided by the proposed solution over state-of-the-art in terms of compliance to the SLA, while limiting resource consumption and service request losses.

Modern cloud and edge computing infrastructures operate under rigorous Service Level Agreements (SLAs), which define Quality of Service (QoS) standards and key performance indicators (KPIs) such as latency, resource efficiency, and reliability. Meeting these requirements is increasingly challenging due to highly variable, bursty, and latency-sensitive workloads demanding intelligent, efficient, and adaptive resource management. To address these evolving needs, we introduce a novel autoscaling framework that combines the Proximal Policy Optimization (PPO) algorithm with a double-stacked Long Short-Term Memory (LSTM) network and an attention mechanism, enabling coordinated and proactive autoscaling in Kubernetes-based environments. The proposed approach utilizes a multidimensional discrete action space to simultaneously tune the Horizontal Pod Autoscaler (HPA) CPU targets, throughput multipliers, learning rate schedules, and policy enhancements, thereby effectively adapting to both short-term and long-term fluctuations in network traffic. Additionally, a forecasting module integrates LSTM-driven workload predictions with recent observation trends, allowing the autoscaler to predict dynamic changes and accommodate resources accordingly. Comprehensive simulations using real Azure Functions invocation traces from production environments justify that our system consistently maintains SLA, QoS, and KPI objectives, while delivering operational stability and enhanced resource efficiency for cloud-edge networks. Under strict SLA constraints, our proposed methodology achieves an average latency reduction of $\mathbf{8 7 . 5 \%}$ and a median latency reduction of $\mathbf{7 1 . 5 \%}$ compared to the baseline.

Serverless computing is an emerging service model that is gaining consensus in both edge and core clouds. In fact, it allows developers focusing on application codes, breaking down services in multiple functions, without the burden of platform management. Services are run in edge clouds, closer to end-users’ devices, when service latency is an important constraint. However, latency control cannot be achieved with ample resource allocation, as in edge environments resources are limited and thus operational efficiency is essential. For these reasons, autoscaling of serverless functions has a central role, as it can lead to both reduced latency and efficient resource usage. In this work, we focus on the usage of reinforcement learning to drive resource-based autoscaling on OpenFaaS, the most-adopted open-source serverless platform, running on Kubernetes clusters. We use the Proximal Policy Optimization algorithm to dynamically configure the value of the Kubernetes Horizontal Pod Autoscaler, trained on Azure traffic traces. We discuss the algorithm configuration, focusing on state definition and relevant performance evaluation, including robustness with respect to traffic burstiness, as well as performance comparison with baseline approach and heuristics.

The service function (SF) area has gained increasing attention in the last years due its ability to combine the advantages of cloud computing with network softwarization. By decoupling SFs from the physical equipment where they are executed, it is possible to make network services scalable and flexible. These advantages become even more evident in the forthcoming 6G networks, where the overall environment is expected to become more dynamic and cloud-based, with SFs deployed as cloud-native functions. However, in order to efficiently manage and compose services using these SFs, it is necessary to monitor the available resources of the nodes where they can be deployed, in addition to exchange information relevant to the operational status of active SFs. To this aim, we propose a lightweight monitoring architecture by using agents in charge of monitoring the status of SFs running in co-located clusters. These monitoring agents exchange their information by means of a gossip protocol, which allows increasing the reliability of the process. In this way, it is possible to keep service decisions as local as possible, limiting the interactions with centralized decision and orchestration platforms, and thus increasing network scalability and responsiveness. Performance evaluation shows the effectiveness of the proposed solution, and demonstrates that the network overhead of the distributed monitoring process is definitely affordable.

The joined use of cloud computing and Internet of Things (IoT) led to the definition of Cloud of Things (CoT), a powerful combination which builds on the strengths of both technologies. Active research in this field provides brand new solutions or improves the ones already in place, but it is hampered by the lack of standardization and by the heterogeneity of adopted technologies. The focus of this work is on the application of a service mesh network to include IoT edge devices in a multi-cloud cluster federation. As the adoption of multi-cloud is rising day by day, the integration of IoT applications in it will surely follow. Available solutions are often restricted to specific use cases and technologies or require IoT middleware to work. The goal of this paper is to propose an architecture which can be used to achieve connectivity, interaction and data exchange between multiple IoT edge devices hosted in distinct environments, through the realisation of a network service mesh. A logical architecture is proposed, defining the components needed, discussing potential applications. An implementation is realised to demonstrate the feasibility of the system. Measurements show that with a negligible increase of computational resources and time, the benefits of a service mesh can be extended to IoT edge devices and the applications deployed on them.

When looking at cloud computing, aside from the commercial solutions like Amazon Web Services and Microsoft Azure, there are also promising open source alternatives. In this paper, our hands-on experiences are summarized with consuming, deploying and managing an on-premise Infrastructure as a Service (IaaS) cloud solution based on the open source OpenStack platform in combination with Ceph as a distributed storage solution. We introduce means on how to achieve high-availability of this small-scale on-premise cloud infrastructure solution and provide network architecture and storage recommendations. Finally, performance measurements of these network and storage solutions are presented, indicating observable throughput and latency differences between the various configurations.

Fifth generation (5G) and beyond systems require flexible and efficient monitoring platforms to guarantee optimal key performance indicators (KPIs) in various scenarios. Their applicability in Edge computing environments requires lightweight monitoring solutions. This work evaluates different candidate technologies to implement a monitoring platform for 5G and beyond systems in these environments. For monitoring data plane technologies, we evaluate different virtualization technologies, including bare metal servers, virtual machines, and orchestrated containers. We show that containers not only offer superior flexibility and deployment agility, but also allow obtaining better throughput and latency. In addition, we explore the suitability of the Function-as-a-Service (FaaS) serverless paradigm for deploying the functions used to manage the monitoring platform. This is motivated by the event oriented nature of those functions, designed to set up the monitoring infrastructure for newly created services. When the FaaS warm start mode is used, the platform gives users the perception of resources that are always available. When a cold start mode is used, containers running the application’s modules are automatically destroyed when the application is not in use. Our analysis compares both of them with the standard deployment of microservices. The experimental results show that the cold start mode produces a significant latency increase, along with potential instabilities. For this reason, its usage is not recommended despite the potential savings of computing resources. Conversely, when the warm start mode is used for executing configuration tasks of monitoring infrastructure, it can provide similar execution times to a microservice-based deployment. In addition, the FaaS approach significantly simplifies the code logic in comparison with microservices, reducing lines of code to less than 38%, thus reducing development time. Thus, FaaS in warm start mode represents the best candidate technology to implements such management functions.

5G technology offers innovative network services to vertical players, able to boost their service portfolio in critical areas that could not be fully addressed with 4G systems. However, 5G networks are complex systems, massively relying on the virtualization of network and computing resources, which requires specific skills to fully exploit their potential. This may represent a hard barrier for vertical stakeholders to effectively test and use innovative services on 5G networks. Our solution addresses this issue, by simplifying the way vertical players approach 5G services though simple yet flexible service templates that allow not only to specify and deploy a service, but also to test it in a variety of realistic conditions. Vertical players interact with these templates named Experiment Blueprints, which are manipulated by our tool and then translated into network service descriptors to be deployed by a service orchestrator, keeping unaware the vertical experimenter of the underlying operations. We use a vertical service in the area of Industry 4.0 as a running example to ease the understanding of the proposed approach.

Due to the growing number of devices accessing the Internet through wireless networks, the radio spectrum has become a highly contended resource. The availability of low cost radio spectrum monitoring sensors enables a geographically distributed, real-time observation of the spectrum to spot inefficiencies and to develop new strategies for its utilization. The potentially large number of sensors to be deployed and the intrinsic nature of data make this task a Big Data problem. In this work we design, implement, and validate a hardware and software architecture for wideband radio spectrum monitoring inspired to the Lambda architecture. This system offers Spectrum Sensing as a Service to let end users easily access and process radio spectrum data. To minimize the latency of services offered by the platform, we fine tune the data processing chain. From the analysis of sensor data characteristics, we design the data models for MongoDB and Cassandra, two popular NoSQL databases. A MapReduce job for spectrum visualization has been developed to show the potential of our approach and to identify the challenges in processing spectrum sensor data. We experimentally evaluate and compare the performance of the two databases in terms of application processing time for different types of queries applied on data streams with heterogeneous generation rate. Our experiments show that Cassandra outperforms MongoDB in most cases, with some exceptions depending on data stream rate.

This paper shows a codebook-based proposal for identifying simultaneous faults in data networks. It includes three main contributions. The first consists of the probabilitstic reduced search space heuristic (PRSSH), which aims to significantly reduce the cardinality of the candidate set of solutions through a so-called compatibility filtering. It is applied to the codebook optimized by the second contribution, which is a solution of the codebook optimization problem. It is built on the weighted set covering optimization problem and consists of a heuristic, named minimum Hamming distance increment maximization heuristic (MHDIM-HEU). Performance has been evaluated both by applying the proposed techniques to some sample networks, simulated by using the end-to-end connectivity service model, and by using an experimental codebook generated by using data collected from a real, nation-wide, next generation network. This codebook has been used to simulate fault effects, which were used to analyze the proposal. We compared the PRSSH approach with a previous proposal, named incremental hypothesis update (IHU), and the MHDIM-HEU with a random heuristic and an optimal branch and bound solution (only for very small network size). Results show the effectiveness of our proposals: PRSSH can decrease the false positive rate up to 66% with respect to IHU, with a significantly reduced processing time (two orders of magnitude). As for MHDIM-HEU, for the same target minimum Hamming distance it requires about half of the symptoms of the random heuristic, with performance very close to the optimal approach. As a third contribution, we evaluated the performance of the PRSSH approach over the codebook optimized by means of MHDIM-HEU, in order to evaluate the impact of the codebook compression on the fault localization performance. Numerical results confirm the goodness of the joint application of both approaches.

Experts have warned that processing of genetic data will soon exceed the computing needs of Twitter and YouTube. This is due to the drop of the costs for sequencing DNA of any living creature and its huge impact in many application areas. Designing suitable network architectures for distributing such data is therefore of paramount importance. Management of genomic data sets is a typical big data problem, characterized not only by a huge volume, but also by the large size of each genomic file. Since it is unthinkable that any professional who needs to process genomes can own the infrastructure for massive genome analysis, a cloud-based access to genomic services is envisaged. This will have a significant impact on the underlying networks, which could become the system bottleneck. In this paper, we propose Genome Centric Networking (GCN), a novel network function virtualization framework for cloud-based genomic data management, designed with the aim of limiting the exchanged traffic by using distributed caching. The key element of GCN is a novel signaling protocol, which allows both discovering network resources and managing caches. We evaluated GCN on a real testbed. GCN allows halving the exchanged traffic and reducing the transfer time of genomic datasets significantly.

The management of network infrastructures has become increasingly complex over time, which is mainly attributed to the introduction of new functionality to support emerging services and applications. To address this important issue, research efforts in the last few years focused on developing software-defined networking solutions. While initial work proposed centralized architectures, their scalability limitations have led researchers to investigate a distributed control plane. Controller placement algorithms and mechanisms for building a logically centralized network view are some examples of challenges addressed in this context. A critical issue that requires specific attention concerns the communication between distributed entities involved in decision-making processes. To this end, we propose SigMA, a signaling framework that supports communication between the different entities of a decentralized management and control system. We also define the communication primitives and interfaces involved in such a decentralized environment. The benefits of SigMA are illustrated through three realistic network resource management use cases with different communication requirements. Based on simulation, we demonstrate the flexibility and extensibility of our solution in satisfying these requirements, thus effectively supporting advanced decentralized decision-making processes.

The management of network infrastructures has become increasingly complex over time, which is mainly attributed to the introduction of new functionality to support emerging services and applications. To address this important issue, research efforts in the last few years focused on developing Software-Defined Networking solutions. While initial work proposed centralized architectures, their scalability limitations have led researchers to investigate a distributed control plane, with controller placement algorithms and mechanisms for building a logically centralized network view, being examples of challenges addressed. A critical issue that has not been adequately addressed concerns the communication between distributed decision-making entities to ensure configuration consistency. To this end, this paper proposes a signaling framework that can allow the exchange of information in distributed management and control scenarios. The benefits of the proposed framework are illustrated through a realistic network resource management use case. Based on simulation, we demonstrate the flexibility and extensibility of our solution in meeting the requirements of distributed decision-making processes.

This paper shows the methodology used for analyzing the technical and non-technical skills necessary for defining a university program providing a Data Science certification. The original aspects of the approach consists of the close collaboration between the organizing universities and the collaborating companies. For what concerns the technical skills, the statistics collected by the already existing programs have been validated by processing thousands of job offers worldwide. The humanistic perspective has completed the picture of the set of skills that have led to the program shown.

In this paper, we present a communication protocol between a pair of biological nanomachines, i.e., a transmitter and a receiver, built upon molecular communications in an aqueous environment. In our proposal, the receiver, acting as a control node, sends a connection setup signal to the transmitter, which stokes molecules, to start molecule transmission. The molecules transmitted by the transmitter propagate in the environment and are absorbed by the receiver through its receptors. When the receiver absorbs the desired quantity of molecules, it releases a tear-down signal to notify the transmitter to stop the transmission. The proposed protocol implements a bidirectional communication by using a number of techniques originally designed for the TCP. In fact, the proposed protocol is connection-oriented and uses the TCP-like probing to find a suitable transmission rate between the transmitter and the receiver to avoid receiver congestion. Unlike the TCP, however, explicit acknowledgments are not used since they would degrade the communication throughput due to the large delay, which is a characteristic feature of molecular communications. Thus, the proposed protocol uses implicit acknowledgments, and feedback signals are sent by the receiver to throttle the transmission rate at the transmitter, i.e., explicit negative feedback. We also present the results of an extensive simulation campaign, used to validate the proposed protocol and to properly dimension the main protocol parameters.

In this paper we analyze the probability of consistency of sensor data distribution systems (SDDS), and determine suitable evaluation models. This problem is typically difficult, since a reliable model taking into account all parameters and processes which affect the system consistency is unavoidably very complex. The simplest candidate approach consists of modeling the state sojourn time, or holding time, as memoryless, and resorting to the well known solutions of Markovian processes. Nevertheless, it may happen that this approach does not fit with some working conditions. In particular, the correct modeling of the SDDS dynamics requires the introduction of a number of parameters, such as the packet transfer time or the packet loss probability, the value of which may determine the suitability of unsuitability of the Markovian model. Candidate alternative solutions include the Erlang phase-type approximation of nearly constant state holding time and a more refined model to account for overlapping events in semi-Markov processes.

In this paper, we evaluate the suitability of the vehicular devices for supporting data storage and distribution applications. Vehicular storage systems have recently emerged as means for making the information related to the vehicular environment available to vehicular users. Information could either be collected by sensors mounted onboard vehicles or coming from the surrounding environment. Modeling a vehicular data storage and distribution system requires the introduction of a number of parameters, such as the vehicle concentration and transmission range, the value of which may determine the suitability or unsuitability of the vehicular environment for establishing a communication infrastructure with the desired quality. In this paper we show how to solve this problem by resorting to a Markovian model and some results achieved through its application.

This paper shows an innovative solution for distributing dynamic sensor data by using distributed caches. Our proposal is based on the concepts of service modularization and virtualization of network nodes made available by the NetServ hosting environment, which has been defined and implemented with the aim of extending the functions of the network nodes. Through a lab experiment involving tens of nodes, we have demonstrated a significant performance improvements in term of traffic saving and download time in comparison with a legacy, Internet-based, approach. Beyond this performance improvements, the proposed solution holds also functional improvements, in terms of dynamic deployment and easy integration with services making use of sensor data.

In this paper, we propose a new gossip-based signaling dissemination method for the Next Steps in Signaling protocol family. In more detail, we propose to extend the General Internet Signaling Transport (GIST) protocol, so as to leverage these new dissemination capabilities from all NSIS Signaling Layer Protocol applications using its transport capabilities. The extension consists of two main procedures: a bootstrap procedure, during which new GIST-enabled nodes discover each other, and a dissemination procedure, which is used to effectively disseminate signaling messages within an Autonomous System. To this aim, we defined three dissemination models, bubble, balloon, and hose, so as to fulfill requirements of different network and service management scenarios. An experimental campaign carried out on GENI shows the effectiveness of the proposed solution.

Autonomic management capabilities of the Future Internet can be provided through a recently proposed service architecture called NetServ. It consists of the interconnection of programmable nodes which enable dynamic deployment and execution of network and application services. This paper shows how this architecture can be further improved by introducing the OpenFlow architecture and implementing the OpenFlow controller as a NetServ service, thus improving both the NetServ management performance and its flexibility. These achievements are demonstrated experimentally on the GENI environment, showing the platform self-protecting capabilities in case of a SIP DoS attack.

In emergency scenarios, like those following a earthquake, road accident in tunnel, large fire and so on, the possibility to track personnel engaged in providing first aid and rescue services is of paramount importance, also in order to promptly manage unexpected and potentially hazardous situations. While in open areas the precision, accuracy and availability of GPS service is enough in most cases, in partially obstructed environments, such as urban canyon, or indoor, GPS service is not available or the quality of provided estimates could be quite coarse. While the literature reports a lot of solutions able to overcome these limitations of the GPS system in standard settings, in emergency scenarios these solutions could be partially or completely unavailable, raising serious concerns about their suitability in these situations. In this paper, we propose a localization and tracking system based on the usage of IEEE 802.11 technology for augmenting the GPS coverage where it is scarce, and to completely substitute it where it is missing, e.g. indoor. The system is characterized by ease of deployment and usage by non-technical personnel, such as that engaged in rescue services in emergency scenarios. In order to assess the feasibility of the proposed solution, we implemented a proof-of-concepts prototype made up of low-cost commercial off-the-shelf components. The preliminary performance tests we performed confirm the effectiveness of proposed system.

Within the activities of the Java APIs for Integrated Networks (JAIN), the Java community offers a set of standard frameworks and open protocol APIs to create advanced telecommunications services. However, recent works have pointed out that Java-based implementations of the Session Initiation Protocol (SIP) stack, the fundamental signalling protocol in the convergent telephone-IP world, perform poorly if they are executed by large multi-core servers, typically used in data centres. The problem lies in the combination of the SIP protocol semantics with the Java language features, which does not allow fully exploiting the computing capabilities of multi-core architectures. To face this problem, we propose a solution to improve the throughput and signalling latency of applications implemented by using Java-based SIP application servers. It consists of the joint usage of virtualization and parallelization techniques. We have performed an extensive measurement campaign by using an open source application server compliant with the JSLEE (JAIN Service Logic Execution Environment) specifications. The rationale of this choice is that JSLEE application servers are currently regarded as very promising candidates for deploying telecom services. Results show that it is possible improving performance in terms of throughput and signalling latency by running more instances of the JSLEE server in parallel, each of them into separate virtual machines deployed on the same server. This improvement can increase throughput values of about 64% and, in the maximum throughput condition, the call set up latency can be nearly halved.

The WiMAX technology has all the necessary features to effectively provide multicast/broadcast services: (i) it is a broadband access technology, (ii) being wireless, it has intrinsic broadcast capabilities, and (iii) it can provide differentiated quality of service levels. Leveraging on these features, we propose a signaling architecture for multicast/broadcast services exploiting the MBS specification in the Mobile WiMAX standard. The signalling is orchestrated by a JAIN SLEE server. We illustrate this architecture, which is highly modular and based on standard communication protocols (i.e. HTTP, SIP, IGMP), and focus on the design and implementation of the signaling part for a multicast video streaming service.

The growing interest in developing value-added services based on Internet telephony brings into sharp focus several issues related to service creation. It becomes compelling for developers to take advantage of a platform that could offer high-level APIs and standard interfaces, in order to reduce the time-to-market and extend the service portability over multiple networks and devices. The Java community is tackling those issues within the Java APIs for integrated networks (JAIN) activity, utilizing Java enterprise edition technologies in order to ease the development process of telecommunication services. This paper describes a SIP-based call control service for Internet telephony, designed for an IP-PSTN converged scenario. The service has a back-to-back user agent (B2BUA) architecture and is deployed into a service logic execution environment (SLEE). Our SLEE is based on Mobicents, an open-source platform for telecom applications, which offers an implementation of the JAIN SLEE specifications. We present the design and a comparative performance evaluation of different architectural implementations of the service, carried out with SIPp, an open-source SIP traffic generation tool.

Fault Localization (FL) is a critical task for operators in the context of e-TOM (enhanced Telecom Operations Map) assurance process, in order to reduce network maintenance costs and improve availability, reliability, and performance of network services. This paper investigates, in a practical perspective, the use of a well known FL technique, named codebook technique, for the IMS control layer of a real Next Generation Network, deploying wireline VoIP and advanced communication services. Moreover, we propose some heuristics to generate optimal codebooks, i.e. to find the minimum set of symptoms (alarms) to be monitored in order to obtain the desired level of robustness to spurious or missing alarms and modelling errors in the root cause detection, and we evaluate their performance through extensive simulations. Finally, we provide a list of some practical Key Performance Indicators, the value of which is compared against specific thresholds. When a threshold is exceeded, an alarm is generated and used by the FL processing.

Nonlinear devices, such as power amplifiers, typically generate spurious signal components known as inter modulations. This phenomenon is particularly important when multiple signals, allocated at different frequencies, pass through nonlinear devices simultaneously. In this paper we extend a known fast counting algorithm (FCA) of intermodulation components and compare it with other counting algorithms. The results obtained show significant improvement on the processing time. The carrier configuration is modelled by using indicator polynomials. We show that the distribution of high order intermodulation products can be computed in a reduced amount of time, by extending the algorithmic results relevant to third order intermodulations. In addition, we notice that in particular situations even order intermodulations are also important. They occupy the adjacent harmonic zones, generally allocated to other services, so that the achievable performance deteriorates. We extend an algorithm which computes the position of even and odd order intermodulations, and we make it faster and computationally more efficient. These results may improve both the optimisation of the spectrum shape and the analysis of the nonlinear effects. Comparisons with some other direct counting algorithms are made in terms of accuracy and speed.

This paper shows a novel approach for routing datagrams in ad-hoc networks, called distributed ant routing (DAR). This approach belongs to the class of routing algorithms inspired by the behavior of the ant colonies in locating food and storing food. The algorithm aims at minimizing complexity in the nodes and this is achieved at the expenses of the optimality of the derived solution. The work also describes an analytical approach to the problem: The validity of the heuristic approach, ant routing, is supported by mathematical proofs and the same methods helps in the selection of the algorithm parameters. Simulation results are presented at the end to confirm the mathematical calculations.

In this paper, we present a solution to control automatically a wireless access network and we focus on load balancing target. The reference scenario is that of a single administrative domain that offers a heterogeneous wireless access. We propose a monitoring procedure able to track the access network context, i.e., the current state of resources, the amount of service demand, and the wireless access points available to mobile terminals. To this end, we exploit a cooperative brokerage framework, distributed between terminals and network. The access network context is the input of a selection process that aims to distribute suitably mobile users among available access points. The objective is to balance the users demand, thus improving the quality of the service. The numerical analysis shows the effectiveness of the proposed system in an 802.11b access network.

An improved IP network service (e.g., for real time services) is expected in the near future in both wired and wireless environments. In this regard, handover capabilities are extremely important and challenging, in particular if their use in operation must be seamless. One of the main steps to achieve seamless handover is the quick discovery of the IP addresses and service capabilities of candidate access routers to hand over to. We present a push-mode-multicast based solution to discover and update timely information about wireless resources. We evaluate the effectiveness of the proposed approach in terms of signaling burden and discovery time with respect to solutions already presented in the literature.

In this paper, we consider a per-call, usage-based tariff model to charge for IP services with guaranteed quality. This model is based on the virtual delay, which is a quality of service (QoS) index that describes an improved IP service provided by a network domain. We show how to compute the virtual delay, and how to make it dependent on the service demand. Then, we demonstrate the effectiveness of our tariff model to tune revenues, blocking probability, and resource utilization in a meaningful application scenario. Our goal is to give some directions for network resource dimensioning and pricing purposes, which depend on the service demand.

Advanced mobility management is a key issue in providing nomadic users with QoS-enabled services in the future Internet. To improve the mobile IP performance, a crucial role is played by the discovery and selection of the access router to handover. This procedure is of great importance to enable the other additional mobility-related protocols to speed up handover. This paper presents and evaluates a novel approach for carrying out this task, based on a fully distributed process, which also allows timely inter-technology handovers.

In this paper, we present a per-call usage-based tariff model to charge for IP guaranteed services. The tariff is built on the basis of the virtual delay, which is a value characterizing an improved IP service. We propose a model to compute the virtual delay within an administrative domain from purely technical considerations, taking into account traffic, performance and system parameters. In addition, we analyze the sensitivity of the virtual delay and of the tariff to the involved parameters, taking into account both users' benefit and operators' income. Our goal is to provide directions for dimensioning purposes.

Nonlinear devices such as amplifiers and electro-optical transducers introduce spurious signals known as intermodulations, especially when multiple signals at different frequencies access the system. In this paper an extension to the well known fast counting algorithm (FCA) for the intermodulations is presented and a comparison with slow counting algorithms is done. Carrier configuration is represented by means of indicator polynomials, and high-order Intermodulation products distribution can be computed in a fast way, extending the results restricted to third order intermodulations. Moreover, no particular assumption is done on the distribution of the carriers (i.e. they are not required to be equispaced). Comparisons are made in terms of accuracy and speed with slow direct counting algorithms.

We define a business model for a future Internet able to provide customers with a wide variety of application services, which typically need performance guarantees. The reference environment includes a number of entities: customers, network and application service providers, resource and information brokers, and a clearing house. Assuming usage-based tariffs to charge for IP guaranteed services, we propose inter-domain routing algorithms for determining the path along autonomous domains, with the aim of maximizing users' benefit, in terms of QoS perceived and price to be paid.

In the present day Internet, the provision of different levels of performance guarantees, appropriate for the type of supported applications and the willingness of users to pay, is a pressing need. Since flat-rate fees are probably inadequate to charge differentiated services, the need to provide usage-based tariff models to charge IP guaranteed services, and therefore to develop business interactions, is expected. We define the network service commodity, traded in a future Internet scenario, as the transfer of information units between two points of the network, and we present an approach to measure it as a function of so called virtual delay. In our approach, the virtual delay summarizes the parameters characterizing the performance guarantees of the transfer service. Under these assumptions, we propose a pricing law to charge improved IP services depending on the duration of the connection and on the traffic volume exchanged during the communication. The tariff is a function of the actually used and/or reserved network resources, so as to satisfy the requirements of users and network management, respectively.

An innovative architecture to access information transport resources under short-term market conditions is presented. Ultra-wideband (UWB) technology in the centralized wireless access domain is believed to minimize the intrinsic performance limitations of the radio link and to provide flexible access in a very wide range of data rates of over 100 Mb/s, even in a strong multipath environment. The decoupling of user, infrastructure, and service provision in an open mobile access network (OMAN) is proposed to overcome current limitations of radio-based networks. A solution for the joint management of quality-of-service and mobility in the UWB domain is proposed, under the assumption of a resource management compliant with the differentiated services framework. Moreover, a model for the "commoditization" of the network service is introduced. The commodity is identified as the transfer of information units between two end points of the network, measured by a function of the so-called "virtual delay," that summarizes the parameters characterizing the performance of the transfer service. A description is given of this model, together with the definition of a pricing law to charge improved Internet protocol-based services. Such concepts are central in the end-to-end service set-up.

In this paper, we propose a solution to provide deterministic quality of service (QoS) guarantees in Differentiated Services (DiffServ) framework. We define packet classification functions and traffic conditioning functions, with particular emphasis on shaping functions at edge routers. Our proposal is based on aggregated classification states, within core routers. The original aspect of our contribution is the introduction of a connection admission control (CAC) procedure on the selected paths, in order to provide performance guarantees to traffic aggregates. Another key aspect is the low involvement of core routers in traffic management, obtained by pushing complexity and processing load towards the boundary of the DiffServ domain. We analyze which guarantees can be provided to flow aggregates in these conditions. To this end, we make use of network calculus for deriving bounds on delay and losses within each network node.

Current satellite systems operate according to circuit switching transfer modes. To improve flexibility and efficiency, several kinds of packet switching systems have been proposed. However, it appears that full packet switches are still too complex and expensive to be implemented on board the satellites, in the near future. For the time being, dynamic bandwidth allocation capabilities (DBAC) provide a compromise solution when satellite systems are based on classical circuit switches, since the DBAC payload allows changing dynamically the capacity of each connection, without tear-down and set-up. We consider a DBAC satellite system and define algorithms to allocate the bandwidth so as to provide deterministic QoS guarantees. Standard dual leaky buckets (DLBs) regulate the traffic sources. We define bandwidth-handling policies, design connection admission control rules and evaluate the system performance analytically. Results show a significant increase in the bandwidth utilization of our system, when compared with a plain circuit switching solution.

Current satellite systems operate according to circuit switching transfer modes. To improve flexibility and efficiency, several kinds of packet switching systems have been proposed. However, it appears that full packet switches are still considered complex and expensive, when implemented on board the satellites. For the time being, a compromise has been found in satellite networks with dynamic bandwidth allocation capabilities (DBAC). Such systems are based on classical circuit switches, but the DBAC payload allows the changing dynamically of the capacity of each connection, without the need for tearing-down and setting-up again the connection itself. In this paper we consider a DBAC satellite system and define algorithms to allocate the bandwidth so as to provide deterministic and statistical QoS guarantees. The traffic sources are regulated by standard dual leaky buckets (DLB). We define bandwidth-handling policies, design connection admission control rules and evaluate analytically the system performance. As expected, the numerical results show a significant increase of the overall utilisation factor of our system, when compared with a plain circuit-switching solution.

Current satellite systems operate according to circuit switching transfer modes. To improve flexibility and efficiency, several kinds of packet switching systems have been proposed. However, it appears that full packet switches are still too complex and expensive to be implemented on board the satellites in the near future. For the time being, dynamic bandwidth allocation capabilities (DBAC) provide a compromise solution when satellite systems are based on classical circuit switches, since the DBAC payload allows changing dynamically the capacity of each connection, without teardown and setup. We consider a DBAC satellite system, and define algorithms to allocate the bandwidth so as to provide deterministic and statistical QoS guarantees. Standard dual leaky buckets (DLBs) regulate the traffic sources. We define bandwidth-handling policies, design connection admission control rules, and evaluate the system performance analytically. Results show a significant increase in bandwidth utilization of our system, when compared to a plain circuit switching solution.

This paper analyses the performance of orthogonal multicarrier DS-CDMA systems for personal communications. The basic system operates using the orthogonal multicarrier technique combined with direct sequence code division multiple access. The non-stationary behaviour of the channel is tracked by a periodic sounding. This technique leads to relatively simple receivers that can be implemented with current VLSI and DSP technology. Taking into account the challenges related to an up-link implementation, the system performance in the down-link is investigated both for synchronous and asynchronous DS-CDMAs. In particular, the schemes which work with Walsh sequences (in the synchronous case) are compared with the schemes operating by binary Gold sequences and 4-phase near-optimal sequences (in the asynchronous case). The comparison is carried out on the basis of significant parameters such as bit error rate, spectral efficiency and multipath counteraction for different system configurations.

This paper presents an analysis of the performances of a digital mobile radio link based on DS-CDMA technique and the RAKE receiver. The adopted signature sequences are complex and characterized by different correlation properties, that lead to different performances in terms of bit error rate and spectral efficiency. Moreover, a preliminary analysis of the performances under non-linear channel behaviour and different modulation schemes is provided.>