Next-generation networks (NGNs) will support quality of service over a mixed wired and wireless IP-based infrastructure. A relative model of service differentiation in differentiated services architecture is a scalable solution for delivering multimedia traffic. However, considering the dynamic nature of radio channels specifically, it is difficult to achieve a given service provisioning working at the IP and lower layers separately as in the classical approach without a run-time adaptation of the system towards the target quality. This work describes an IP cross-layer scheduler able to support a Proportional Differentiation Model (PDM) for delay guarantees also over wireless. The key idea is to leverage feedbacks from the lower layers about the actual delays experienced by packets in order to tune at run-time the priority of the IP service classes in a closed-loop control with the objective of supporting a PDM at the interface on the whole, considering the cumulative latency across multiple layers, as relevant for the end-user. A simulation analysis demonstrates the prominent improvements in reliability and robustness of the proposal in the case of time-variant performance of the MAC and PHY layers with respect to the classical non-cross-layer approach and open-loop control. Furthermore, considerations on the required functionality and likely deployment scenarios highlight the scalability and backward compatibility of the designed solution, addressing a sustainable approach and smooth migration to NGNs.

Next-Generation Networks (NGNs), comprising for example, B4G and 5G cellular systems, will support Quality of Service (QoS) over a heterogeneous wired and wireless IP-based infrastructure. A relative model of service differentiation in DiffServ architecture is a scalable solution for delivering multimedia traffic. However, the dynamic nature of radio channels makes it difficult to achieve the target quality provisioning working separately at the IP and lower layers, as in the classical approach. This work describes an IP cross-layer scheduler able to support a Proportional Differentiation Model (PDM) for delay guarantees also over wireless. The key idea is to leverage feedbacks from the lower layers about the actual delays experienced by packets in order to tune at run-time the priority of the IP service classes in a closed-loop control. The objective is to implement a PDM on the whole at the network interface, as relevant for the end-users. A simulation analysis demonstrates the prominent improvements in reliability and robustness of the proposal with respect to both the classical and the open loop approaches. Considerations on the required functionality and possible deployment scenarios highlight the scalability and backward compatibility of the designed solution.

Next-Generation Networks (NGNs) will support Quality of Service (QoS) over a mixed wired and wireless IP-based infrastructure. A relative model of service differentiation in Differentiated Services architecture is a scalable solution for delivering multimedia traffic. However, considering the dynamic nature of radio channels typically, it is difficult to achieve a given service provisioning working at the IP and lower layers separately as in the classical approach, without a run-time adaptation of the system towards the target quality. This work describes an IP cross-layer scheduler able to support a Proportional Differentiation Model (PDM) for delay guarantees with content-awareness, also over wireless. The key idea is to leverage feedbacks from the lower layers about the actual delays experienced by packets in order to tune at run-time the priority of the IP service classes in a closed-loop control with the objective of supporting a PDM at the network node on the whole, considering the cumulative latency in crossing the first three layers of the protocol stack, as relevant for the end-user. A simulation analysis demonstrates the prominent improvements in reliability and robustness of the proposal in the case of time-variant performance of the MAC and PHY layers with respect to the classical non-cross-layer approach and the open- loop control. Furthermore, considerations on the required functionality and likely deployment scenarios highlight the scalability and backward compatibility of the designed solution in supporting the concept of network transparency for the delivering of critical applications, as of the e-health domain.

Next-Generation Networks (NGNs) will support Quality of Service (QoS) over a mixed wired and wireless IP-based infrastructure. A relative model of service differentiation in Differentiated Services architecture is a scalable solution for delivering multimedia traffic. However, considering the dynamic nature of radio channels specifically, it is difficult to achieve the target quality provisioning working at the IP and lower layers separately as in the classical approach. In this work, an IP cross-layer scheduler able to support a Proportional Differentiation Model (PDM) for delay guarantees also over wireless is described. The key idea is to leverage feedbacks from the lower layers about the actual delays experienced by packets in order to tune at run-time the priority of the IP service classes with the objective of supporting a PDM at the network node on the whole across multiple layers. A simulation analysis demonstrates the prominent improvements in reliability and robustness of the proposal in the case of highly time-variant performance of the MAC and PHY layers with respect to the classical approach. Furthermore, considerations on the required functionality and likely deployment scenarios highlight the scalability and backward compatibility of the designed solution.

Next-Generation Networks (NGNs), comprising for example, 4G and B4G mobile systems, will support Quality of Service (QoS) over a heterogeneous wired and wireless IP-based infrastructure. A relative model of service differentiation in Differentiated Services architecture is a scalable solution for delivering multimedia traffic. However, the dynamic nature of radio channels makes it difficult to achieve the target quality provisioning working separately at the IP and lower layers, as in the classical approach. In this work, an IP cross-layer scheduler able to support a Proportional Differentiation Model (PDM) for delay guarantees is introduced. The key idea is to leverage feedback from the lower layers indicating the actual transmission delays experienced by packets in order to dynamically tune the priority of the IP service classes with the objective of supporting the PDM at the network node on the whole across multiple layers. A simulation analysis demonstrates the prominent improvements in reliability and robustness of the proposal with respect to the classical approach. Considerations on the required functionality and possible deployment scenarios highlight the scalability and backward compatibility of the designed solution. Therefore, it addresses the requirements and challenges for NGNs.

This short paper introduces a novel use of timeline-based planning as the core element of a dynamic training environment for crisis managers called PANDORA. A trainer is provided with a combination of planning and execution functions that allow him/her to maintain and adapt a "lesson plan" as the basis for the interaction between the trainer and a class of trainees. The training session is based on the concept of Scenario, that is a set of events and alternatives deployed on a timeline-based system, that shapes an abstract plan proposed to trainees. Throughout a training session a continuous planning, execution, re-planning loop takes place, based around trainer observation of trainees and self-reporting by trainees, which provides analysis of both their behavioral and psychological changes. These, combined with the trainee decisions about what actions to take to manage the crisis, are used to maintain an updated model of each user. In addition the trainer has the ability to directly intervene in a training session to, for example, interject new scenario events. The training session is therefore managed through a combination of automated analysis of trainee behaviour and decisions, coupled with trainer input and direction.

Next-Generation Networks (NGNs) will support Quality of Service (QoS) for multimedia traffic over an IP-based infrastructure. A scalable solution to provide also stringent guarantees is required. DiffServ architecture can offer different levels of service at low complexity, but it is not basically able to efficiently provide end-to-end absolute QoS for real-time traffic. Many research activities have addressed this issue, proposing either an absolute or a relative approach. While the former is complicated to implement in the global Internet, the latter is simpler and can be easily realized without arising scalability concerns because exploiting the Proportional Differentiation Model (PDM), in which the performance distance between classes is proportional to quality differentiation parameters that Network Service Provider (NSP) can configure. This work aims to achieve absolute delay guarantees relying on a PDM that can be easily deployed in DiffServ architecture using a proportional scheduler, like Advanced Waiting Time Priority (AWTP). The key idea is to enhance the end-to-end delay differentiation provided by PDM, with a run-time class adaptation, which dynamically assigns the service class to critical traffic in order to fulfil its end-to-end delay requirements. Simulation results have been collected to analyse the trade-off between the fast reaction to load changes and the system stability with different measurement processes, employed to decide for a class promotion or downgrade. The validity and good performance of our proposal have been demonstrated over various scenarios also in the critical case of network congestion.

Next-Generation Networks will support Quality of Service (QoS) over an IP-based infrastructure. A scalable solution to assure stringent delay requirements for real-time applications is needed. In this work, a Proportional Differentiation Model (PDM) in DiffServ architecture is employed to provide even absolute QoS guarantees by a dynamic assignment of service class.

The number of "intelligent" devices with computing and communication capabilities, that surround people in the home environment, are continuously growing. This kind of devices is characterized by software running on them but this needs to be configured and updated from time to time. The user who wants to configure and update these devices has to face the variety of devices configuration procedures and to find the software updates from different manufacturers. This intrinsic difficulty in configuring and updating devices, together with their spreading, make the necessity of an automatic configuration system grow. The COMANCHE project has proposed a complete architecture for software configuration management in the home environment, which aims to overcome the heterogeneity of configuration and upgrading procedures and will allow the deployment of value added services. This paper will give a screenshot of the defined architecture, comparing it also with other configuration and updating existing solutions, like OMA and TR-69.

Ambient intelligence manifests itself through a collection of everyday devices incorporating computing and networking capabilities that enable them to interact with each other, make intelligent decisions and interact with users through user friendly multimodal interfaces. Ambient intelligence is driven by users' needs and the design of its capabilities should be driven by users' requirements. An example of an application exhibiting ambient intelligence is home automation. A consequence of embedding computing capabilities in everyday devices is the development of software to be installed and run on them. The presence of software requires certain procedures for managing its installation, versions and configurations. The COMANCHE project aims to design and develop a software configuration management infrastructure which can be used in the home automation domain. In such an environment, certain issues should be considered before installing new software versions on a given device, such as the user profile, co-existing devices and the way the new ones should interact with them, etc. This paper describes these issues together with trends in ambient intelligence, and finally presents the COMANCHE project objectives and preliminary architecture.

Ambient intelligence implies that a collection of everyday devices incorporates inside computing and networking capabilities that enable them to interact with each other, make intelligent decision and interact with users through user friendly multimodal interfaces. Ambient intelligence is driven by users’ needs and their design should be driven by users’ requirements. An example of an application exhibiting ambient intelligence technologies is home automation. The consequence of putting computing capabilities in everyday devices is the development of some software to install and run on them. The presence of software requires certain procedures for managing its versions and configurations. The COMANCHE project aims to design and develop a software configuration management infrastructure which can be used in the home automation domain. In such an environment, certain issues should be considered before installing new software versions on a given device, such as the user profile, existing devices, how the new one should interact with them, etc. This paper describes these issues together with trends in ambient intelligence, and finally presents the COMANCHE project objectives and preliminary architecture. Keywords— Ambient Intelligence, Software configuration management, pervasive computing, semantic modeling, home