Quality of Experience Provision in the Future Internet

Abstract

This work deals with the satisfaction of the quality of\ud experience (QoE) requirements in the perspective of the emerging\ud future Internet framework. The evolution of the Internet is pointing\ud out its limitations, which are likely to hinder its potential. In\ud this respect, this paper introduces an innovative approach to cope\ud with some key limitations of the present communication networks.\ud In particular, the need of efficiently utilizing the available network\ud resources and of guaranteeing the user expectations in terms of\ud QoE requires a full cognitive approach, which is realized by the\ud introduction of a novel architecture design, the so-called future\ud Internet core platform. The future Internet core platform aims\ud at bringing together the applications world with the network\ud world, hence introducing a further cognitive level while enabling a\ud new generation of applications: network-aware applications. This\ud paper is concerned with an important aspect of the intelligent\ud connectivity between applications and network: the service class\ud association, which, if performed with a cognitive approach, can\ud yield some important improvements and advantages in the emerging\ud information era. The key idea presented in this paper is a\ud real-time dynamic control procedure for the selection of the optimal\ud service class. The approach is based on theoretical considerations\ud validated by a proof-of-concept simulation

Multi-agent quality of experience control

“…1, both the Perceived and the Target QoE should be computed by a suitable QoE Evaluator based on suitable Feedback Parameters resulting from the real-time monitoring of the network, as well as from direct or indirect feedbacks coming from users and/or applications. For a more detailed description of the way the QoE functionalities are embedded in the Future Internet architecture, see [17], [18] and [19].…”

“…This means that, at each time instant tk, the QoE Controller has to decide, in real time, which is the most appropriate CoS to be associated with each in-progress application instance (e.g., if the Agents are embedded in mobile user terminals, the QoE Controller decisions can be implemented by inserting the selected CoS identifier in the header of the packets transmitted by the terminals). Up to the authors' knowledge, apart from [18], [19], [12] and [23], such a dynamic assignment approach has never been investigated so far.…”

Securing Cyber-Physical Systems: An Optimization Framework based on OSSTMM and Genetic Algorithms

“…In recent years, the study of Cyber-Physical Systems (CPSs) has become a topic of great interest for control system researchers, as CPSs bring together problems derived from classical control theory with concerns related to computer science and cyber-security [1]. In their most general definition, CPSs can be considered as interconnected systems that integrate both physical capabilities and computing power [2] and have found application in several fields, spacing from manufacturing [3], healthcare [4], telecommunication [5]- [7] and transportation [8] networks, power systems [9], [10] and aerospace [11].…”

A QoE-aware dynamic bandwidth allocation algorithm based on game theory

“…Although several algorithms converging to Wardrop equilibria have been proposed in the literature (e.g., for routing [26] and load balancing [27]), the algorithm proposed in this paper is the first one applied to QoE control. A first attempt to QoE control can be found in [28], where an optimal control approach was proposed for a simple homogeneous network scenario. The convergence to a Wardrop equilibrium can guarantee fairness among all the running applications (all the flows experience the same QoE value, in terms of Mean Opinion Score (MOS)).…”