a cognitive future internet architecture

This Chapter proposes a novel Cognitive Framework as reference architecture for the Future Internet (FI), which is based on so-called Cognitive Managers. The objective of the proposed architecture is twofold. On one hand, it aims at achieving a full interoperation among the different entities constituting the ICT environment, by means of the introduction of Semantic Virtualization Enablers, in charge of virtualizing the heterogeneous entities interfacing the FI framework. On the other hand, it aims at achieving an inter-network and inter-layer cross-optimization by means of a set of so-called Cognitive Enablers, which are in charge of taking consistent and coordinated decisions according to a fully cognitive approach, availing of information coming from both the transport and the service/content layers of all networks. Preliminary test studies, realized in a home environment, confirm the potentialities of the proposed solution

Electric Vehicles Charging Control based on Future Internet Generic Enablers

In this paper a rationale for the deployment of Future Internet based applications in the field of Electric Vehicles (EVs) smart charging is presented. The focus is on the Connected Device Interface (CDI) Generic Enabler (GE) and the Network Information and Controller (NetIC) GE, which are recognized to have a potential impact on the charging control problem and the configuration of communications networks within reconfigurable clusters of charging points. The CDI GE can be used for capturing the driver feedback in terms of Quality of Experience (QoE) in those situations where the charging power is abruptly limited as a consequence of short term grid needs, like the shedding action asked by the Transmission System Operator to the Distribution System Operator aimed at clearing networks contingencies due to the loss of a transmission line or large wind power fluctuations. The NetIC GE can be used when a master Electric Vehicle Supply Equipment (EVSE) hosts the Load Area Controller, responsible for managing simultaneous charging sessions within a given Load Area (LA); the reconfiguration of distribution grid topology results in shift of EVSEs among LAs, then reallocation of slave EVSEs is needed. Involved actors, equipment, communications and processes are identified through the standardized framework provided by the Smart Grid Architecture Model (SGAM).Comment: To appear in IEEE International Electric Vehicle Conference (IEEE IEVC 2014

Distributed control in virtualized networks

The increasing number of the Internet connected devices requires novel solutions to control the next generation network resources. The cooperation between the Software Defined Network (SDN) and the Network Function Virtualization (NFV) seems to be a promising technology paradigm. The bottleneck of current SDN/NFV implementations is the use of a centralized controller. In this paper, different scenarios to identify the pro and cons of a distributed control-plane were investigated. We implemented a prototypal framework to benchmark different centralized and distributed approaches. The test results have been critically analyzed and related considerations and recommendations have been reported. The outcome of our research influenced the control plane design of the following European R&D projects: PLATINO, FI-WARE and T-NOVA

Optimal Fully Electric Vehicle load balancing with an ADMM algorithm in Smartgrids

In this paper we present a system architecture and a suitable control methodology for the load balancing of Fully Electric Vehicles at Charging Station (CS). Within the proposed architecture, control methodologies allow to adapt Distributed Energy Resources (DER) generation profiles and active loads to ensure economic benefits to each actor. The key aspect is the organization in two levels of control: at local level a Load Area Controller (LAC) optimally calculates the FEVs charging sessions, while at higher level a Macro Load Area Aggregator (MLAA) provides DER with energy production profiles, and LACs with energy withdrawal profiles. Proposed control methodologies involve the solution of a Walrasian market equilibrium and the design of a distributed algorithm.Comment: This paper has been accepted for the 21st Mediterranean Conference on Control and Automation, therefore it is subjected to IEEE Copyrights. See IEEE copyright notice at http://www.ieee.org/documents/ieeecopyrightform.pd

Distributed workload control for federated service discovery

The diffusion of the internet paradigm in each aspect of human life continuously fosters the widespread of new technologies and related services. In the Future Internet scenario, where 5G telecommunication facilities will interact with the internet of things world, analyzing in real time big amounts of data to feed a potential infinite set of services belonging to different administrative domains, the role of a federated service discovery will become crucial. In this paper the authors propose a distributed workload control algorithm to handle efficiently the service discovery requests, with the aim of minimizing the overall latencies experienced by the requesting user agents. The authors propose an algorithm based on the Wardrop equilibrium, which is a gametheoretical concept, applied to the federated service discovery domain. The proposed solution has been implemented and its performance has been assessed adopting different network topologies and metrics. An open source simulation environment has been created allowing other researchers to test the proposed solution

Smart Vehicle to Grid Interface Project: Electromobility Management System Architecture and Field Test Results

This paper presents and discusses the electromobility management system developed in the context of the SMARTV2G project, enabling the automatic control of plug-in electric vehicles' (PEVs') charging processes. The paper describes the architecture and the software/hardware components of the electromobility management system. The focus is put in particular on the implementation of a centralized demand side management control algorithm, which allows remote real time control of the charging stations in the field, according to preferences and constraints expressed by all the actors involved (in particular the distribution system operator and the PEV users). The results of the field tests are reported and discussed, highlighting critical issues raised from the field experience.Comment: To appear in IEEE International Electric Vehicle Conference (IEEE IEVC 2014

Approaches for Future Internet architecture design and Quality of Experience (QoE) Control

Researching a Future Internet capable of overcoming the current Internet limitations is a strategic investment. In this respect, this paper presents some concepts that can contribute to provide some guidelines to overcome the above-mentioned limitations. In the authors' vision, a key Future Internet target is to allow applications to transparently, efficiently and flexibly exploit the available network resources with the aim to match the users' expectations. Such expectations could be expressed in terms of a properly defined Quality of Experience (QoE). In this respect, this paper provides some approaches for coping with the QoE provision problem

Multi-agent quality of experience control

In the framework of the Future Internet, the aim of the Quality of Experience (QoE) Control functionalities is to track the personalized desired QoE level of the applications. The paper proposes to perform such a task by dynamically selecting the most appropriate Classes of Service (among the ones supported by the network), this selection being driven by a novel heuristic Multi-Agent Reinforcement Learning (MARL) algorithm. The paper shows that such an approach offers the opportunity to cope with some practical implementation problems: in particular, it allows to face the so-called “curse of dimensionality” of MARL algorithms, thus achieving satisfactory performance results even in the presence of several hundreds of Agents

Attack-Surface Metrics, OSSTMM and Common Criteria Based Approach to “Composable Security” in Complex Systems

In recent studies on Complex Systems and Systems-of-Systems theory, a huge effort has been put to cope with behavioral problems, i.e. the possibility of controlling a desired overall or end-to-end behavior by acting on the individual elements that constitute the system itself. This problem is particularly important in the “SMART” environments, where the huge number of devices, their significant computational capabilities as well as their tight interconnection produce a complex architecture for which it is difficult to predict (and control) a desired behavior; furthermore, if the scenario is allowed to dynamically evolve through the modification of both topology and subsystems composition, then the control problem becomes a real challenge. In this perspective, the purpose of this paper is to cope with a specific class of control problems in complex systems, the “composability of security functionalities”, recently introduced by the European Funded research through the pSHIELD and nSHIELD projects (ARTEMIS-JU programme). In a nutshell, the objective of this research is to define a control framework that, given a target security level for a specific application scenario, is able to i) discover the system elements, ii) quantify the security level of each element as well as its contribution to the security of the overall system, and iii) compute the control action to be applied on such elements to reach the security target. The main innovations proposed by the authors are: i) the definition of a comprehensive methodology to quantify the security of a generic system independently from the technology and the environment and ii) the integration of the derived metrics into a closed-loop scheme that allows real-time control of the system. The solution described in this work moves from the proof-of-concepts performed in the early phase of the pSHIELD research and enrich es it through an innovative metric with a sound foundation, able to potentially cope with any kind of pplication scenarios (railways, automotive, manufacturing, ...)

Control architecture to provide E2E security in interconnected systems: the (new) SHIELD approach

Modern Systems are usually obtained as incremental composition of proper (smaller and SMART) subsystems interacting through communication interfaces. Such flexible architecture allows the pervasive provisioning of a wide class of services, ranging from multimedia contents delivery, through monitoring data collection, to command and control functionalities. All these services requires that the adequate level of robustness and security is assured at End-to- End (E2E) level, according to user requirements that may vary depending on the specific context or the involved technologies. A flexible methodology to dynamically control the security level of the service being offered is then needed. In this perspective, the authors propose an innovative control architecture able to assure E2E security potentially in any application, by dynamically adapting to the underlying systems and using its resources to “build the security”. In particular, the main novelties of this solution are: i) the possibility of dynamically discovering and composing the available functionalities offered by the environment to satisfy the security needs and ii) the possibility of modelling and measuring the security through innovative technology-independent metrics. The results presented in this paper moves from the solutions identified in the pSHIELD project and enrich them with the innovative advances achieved through the nSHIELD research, still ongoing. Both projects have been funded by ARTEMIS-JU