Patterns for the design of secure and dependable software defined networks

In an interconnected world, cyber and physical networks face a number of challenges that need to be resolved. These challenges are mainly due to the nature and complexity of interconnected systems and networks and their ability to support heterogeneous physical and cyber components simultaneously. The construction of complex networks preserving Security and Dependability (S&D) properties is necessary to avoid system vulnerabilities, which may occur in all the different layers of Software Defined Networking (SDN) architectures. In this paper, we present a model based approach to support the design of secure and dependable SDN. This approach is based on executable patterns for designing networks able to guarantee S&D properties and can be used in SDN networks. The design patterns express conditions that can guarantee specific S&D properties and can be used to design networks that have these properties and manage them during their deployment. To evaluate our pattern approach, we have implemented executable pattern instances, in a rule-based reasoning system, and used them to design and verify wireless SDN networks with respect to availability and confidentiality. To complete this work, we propose and evaluate an implementation framework in which S&D patterns can be applied for the design and verification of SDN networks

Quality of experience management in mobile cellular networks: Key issues and design challenges

Telecom operators have recently faced the need for a radical shift from technical quality requirements to customer experience guarantees. This trend has emerged due to the constantly increasing amount of mobile devices and applications and the explosion of overall traffic demand, forming a new era: the rise of the consumer. New terms have been coined in order to quantify, manage, and improve the experienced user quality, with QoE being the most dominant one. However, QoE has always been an afterthought for network providers, and thus numerous research questions need to be answered prior to a shift from conventional network- centric paradigms to more user-centric approaches. To this end, the scope of this article is to provide insights on the issue of networklevel QoE management, identifying the open issues and prerequisites toward acquiring QoE awareness and enabling QoE support in mobile cellular networks. A conceptual framework for achieving end-to-end QoE provisioning is proposed and described in detail in terms of its design, its constituents and their interactions, as well as the key implementation challenges. An evaluation study serves as a proof of concept for this framework, and demonstrates the potential benefits of implementing such a quality management scheme on top of current or future generations of mobile cellular networks. © 1979-2012 IEEE

A survey on parametric QoE estimation for popular services

As we are moving forward to the 5G era, we are witnessing a transformation in the way networks are designed and behave, with the end-user placed at the epicenter of any decision. One of the most promising contributors towards this direction is the shift from Quality of Service (QoS) to Quality of Experience (QoE) service provisioning paradigms. QoE, i.e., the degree of delight or annoyance of a service as this is perceived by the end-user, paves the way for flexible service management and personalized quality monitoring. This is enabled by exploiting parametric QoE assessment models, namely specific formula-based QoE estimation methods. In this paper, recognizing a gap in the literature between the lack of a proper manual regarding the objective QoE estimation and the ever increasing interest from network stakeholders for QoE intelligence, we provide a comprehensive guide to standardized and state-of-the-art quality assessment models. More specifically, we identify and describe parametric QoE formulas for the most popular service types (i.e., VoIP, online video, video streaming, web browsing, Skype, IPTV and file download services), indicating the key performance indicators (KPIs) and major configuration parameters (MCPs) per type. Throughout the paper, it is revealed that KPIs and MCPs are highly variant per service type, and that, even for the same service, different factors contribute with a different weight on the perceived QoE. This finding can strongly enable a more meaningful resource provisioning across different applications compared to QoE-agnostic schemes. Overall, this paper is a stand-alone, self-contained repository of QoE assessment models for the most common applications, becoming a handy tutorial to parties interested in delving more into QoE network management topics. © 2016 Elsevier Lt

The need for QoE-driven interference management in femtocell-overlaid cellular networks

Under the current requirements for mobile, ubiquitous and highly reliable communications, internet and mobile communication technologies have converged to an all-Internet Protocol (IP) packet network. This technological evolution is followed by a major change in the cellular networks’ architecture, where the traditional wide-range cells (macrocells) coexist with indoor smallsized cells (femtocells). A key challenge for the evolved heterogeneous cellular networks is the mitigation of the generated interferences. In the literature, this problem has been thoroughly studied from the Quality of Service (QoS) point of view, while a study from the user’s satisfaction perspective, described under the term “Quality of Experience (QoE)”, has not received enough attention yet. In this paper, we study the QoE performance of VoIP calls in a femto-overlaid Long Term Evolution Advanced (LTE-A) network and we examine how QoE can drive a power controlled interference management scheme. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014

TCP video streaming and mobile networks: Not a love story, but better with context

The rise in popularity of TCP-based video streaming in recent years is unbroken. These streaming services not just operate on wired access lines but more and more specifically target users of mobile networks as well. Yet it still remains difficult to evaluate the performance of such streaming approaches in mobile networks. This is especially critical as mobile networks exhibit much more potential for undesirable interactions between the network protocol layers and control plane properties on one side and the protocols and strategies of the application layer on the other side, ultimately resulting in scenarios with bad QoE for video streaming. This paper aims to rectify this lack of knowledge and understanding in a multi-pronged approach as follows: The first contribution provides an easy means to investigate such interactions with a streaming simulation framework built on ns-3. In a second contribution three exemplary scenarios within this framework are investigated in order to uncover the nature of such interactions. The final undertaking attempts to unravel the issues of the mobility scenario using context information. Such information can be collected through crowdsensing and collaboratively processed in a Big Data approach. This results in a tailor-made analytical solution through the formulation of a Mixed Integer Linear Program (MILP) that can prevent video stalling in this particular scenario. © 2016 Elsevier B.V

QoE-SD N APP: A Rate-guided QoE-aware SDN-APP for HTTP Adaptive Video Streaming

While video streaming has dominated the Internet traffic, video service providers (VSPs) compete on how to assure the best quality of experience (QoE) to their customers. HTTP Adaptive Streaming (HAS) has become the de facto way that helps VSPs work-around potential network bottlenecks that inevitably cause stallings. However, HAS-alone cannot guarantee a seamless viewing experience, since this highly relies on the mobile network operators' (MNOs) infrastructure and evolving network conditions. Software-defined networking (SDN) has brought new perspectives to this traditional paradigm where VSPs and MNOs are isolated, allowing the latter to open their network for more flexible, service-oriented programmability. This paper takes advantage of recent standardization trends in SDN and proposes a programmable QoE-SDN App, enabling network exposure feedback from MNOs to VSPs towards network-aware video segment selection and caching, in the context of HAS. The video selection problem is formulated using Knapsack optimization and relaxed to partial sub-problems that provide segment encodings that can mitigate stallings. Furthermore, a mobility prediction mechanism based on the Self-similar Least-Action Walk model is introduced, toward proactive segment caching. A number of use cases, enabled by the QoE-SDN App, are designed to evaluate the proposed scheme, revealing QoE benefits for VSPs and bandwidth savings for MNOs. © 2018 IEEE

The CASPER user-centric approach for advanced service provisioning in mobile networks

This paper presents an overview of the project CASPER,1 a 4-year Marie Curie Research and Innovation Staff Exchange (RISE) project running between 2016 and 2020, describing its objectives, approach, architecture, tools and key achievements. CASPER combines academic and industrial forces towards leveraging the expected benefits of Quality of Experience (QoE) exploitation in future networks. In order to achieve that, a QoE orchestrator has been proposed which implements the basic functionalities of QoE monitoring, estimation and management. With means of simulation and testbed emulation, CASPER has managed to develop a proprietary SDN Controller, which implements QoE-based traffic rerouting for the challenging scenario of HTTP adaptive video streaming, leading to more stable and higher QoE scores compared to a state-of-the-art SDN Controller implementation. © 202

No-reference video quality measurement: Added value of machine learning

Video quality measurement is an important component in the end-to-end video delivery chain. Video quality is, however, subjective, and thus, there will always be interobserver differences in the subjective opinion about the visual quality of the same video. Despite this, most existing works on objective quality measurement typically focus only on predicting a single score and evaluate their prediction accuracies based on how close it is to the mean opinion scores (or similar average based ratings). Clearly, such an approach ignores the underlying diversities in the subjective scoring process and, as a result, does not allow further analysis on how reliable the objective prediction is in terms of subjective variability. Consequently, the aim of this paper is to analyze this issue and present a machine-learning based solution to address it. We demonstrate the utility of our ideas by considering the practical scenario of video broadcast transmissions with focus on digital terrestrial television (DTT) and proposing a no-reference objective video quality estimator for such application. We conducted meaningful verification studies on different video content (including video clips recorded from real DTT broadcast transmissions) in order to verify the performance of the proposed solution. © 2015 SPIE and ISandT

The value of context-awareness in bandwidth-challenging HTTP adaptive streaming scenarios

Video streaming has become an indispensable technology in people’s lives, while its usage keeps constantly increasing. The variability, instability and unpredictability of network conditions pose one of the biggest challenges to video streaming. In this chapter, we analyze HTTP Adaptive Streaming, a technology that relieves these issues by adapting the video reproduction to the current network conditions. Particularly, we study how context awareness can be combined with the adaptive streaming logic to design a proactive client-based video streaming strategy. Our results show that such a context-aware strategy manages to successfully mitigate stallings in light of network connectivity problems, such as an outage. Moreover, we analyze the performance of this strategy by comparing it to the optimal case, as well as by considering situations where the awareness of the context lacks reliability. © The Author(s) 2018