Christos Tselios

A model of network related QoE for 3D video

Three Dimensional video quality comprises a variety of perceptual attributes, including overall image quality, naturalness, presence, perceived depth, comfort, immersiveness, etc. This paper proposes a novel objective QoE model for 3D video streaming that takes into account network parameters (i.e. packet losses)and is based on the relationship between objective and subjective video quality measures. The investigation is concerned with stereoscopic video (left-and-right views). The analysis of the results indicate that the proposed QoE model has a strong correlation with MOS scores, hence can be effectively used in predicting the overall image quality of 3D videos transmitted over lossy networks.

Peer selection and scheduling of H.264 SVC video over wireless networks

Scalable video enables flexible video delivery over IP networks. The adaptation of the video content to the network configuration and the networking conditions is the great advantage of scalable video. In this research work, on-demand H.264 SVC video delivery over wireless multi-hop single-frequency networks is studied. The main objective is to achieve the highest levels of video quality possible while ensuring fairness among competing video flows over a wireless network. With the main barrier being interference, each video receiver has to decide from which peer it will receive a specific layer. The problem of peer selection and layer allocation is formed as a Mixed Integer Linear Program (MILP). A relaxation as a Non-Linear Program (NLP) is also provided. Simulation results based on real input video sequences verify the validity of the theoretical approach.

Cloud for multimedia applications and services over heterogeneous networks ensuring QoE

This paper aims to identify open challenges and propose the future steps towards establishing QoE driven media aware clouds. Cloud computing emerges as technology that allows access to resources over the Internet, transparently and independently of the underlying infrastructure. This study identifies the research challenges that future media-aware cloud computing will need to address. This is important in order to support multimedia services and applications exchange with efficiency, seamlessness and with guaranteed perceived quality across heterogeneous networking technologies, user devices and preferences.

End-to-end quality aware optimization for multimedia clouds

This article presents a novel, end-to-end, quality-aware optimization framework for multimedia clouds, where path selection mechanisms are exploited in conjunction with media optimization in order to support multimedia delivery in a quality-aware manner. As wireless data traffic worldwide is characterized by exponential growth, with the most prominent part being multimedia services, consumers get in the challenging position to compete for the limited wireless network resources. Cloud technologies and especially Software-Defined Networking is the perfect candidate technology in order to provide an elastic, dynamic provisioning of network resources that adapt to a highly changing environment, where application requirements and data volumes vary over time. This work combines the selection of the optimum path in the core network with quality-aware media adaptation based on the current conditions of the wireless access network. Thus the proposed framework achieves efficient network resources utilization in an end-to-end fashion.

Service continuity over intertechnology RATs

This paper proposes a novel architecture that integrates Media Independent Handover (MIH) 802.21 framework and IP Multimedia Subsystem (IMS) functionalities in order to support multimedia services across intertechnology Radio Access Networks (RANs) in a secure and seamless manner. MIH framework is responsible for deciding and triggering a handoff based on physical, network and application layer statistics so that an ongoing multimedia session can be transferred seamlessly and securely (using context transfer) across inter-technology Radio Access Networks. In parallel, IMS provides the functionalities for providing uninterrupted service continuity across different network domains during vertical handoffs. The paper proposes a novel integration between MIH and IMS that results in minimizing handoff latency and improving perceived video quality in terms of PSNR. Real testbed experiments indicate that during a inter IMS domain, MIH vertical handoff with security enhancements, the handoff delay is reduced by 12sec during a 3G-WiFi handover as opposed to a non-integrated MIH/IMS architecture.

On optimizing scalable video delivery over media aware mobile clouds

The sovereignty of cloud-deployed media applications and services is improbable to be disrupted in the foreseeable future. This paper aims to provide an overview of the most essential technologies utilized by this constantly evolving cloud ecosystem, identify the design principles of a media-aware cloud and present an architectural position based on the research conclusions. An end-to-end quality-aware optimization framework is evaluated, where path selection mechanisms are exploited in conjunction with media optimization in order to support cloud based multimedia delivery in a quality-aware manner. This position intends to be simplistic yet outright enough to be employed for mobile cloud deployment in the upcoming fifth generation network era.

On the Deployment of Healthcare Applications over Fog Computing Infrastructure

Fog computing is considered as the most promising enhancement of the traditional cloud computing paradigm in order to handle potential issues introduced by the emerging Interned of Things (IoT) framework at the network edge. The heterogeneous nature, the extensive distribution and the hefty number of deployed IoT nodes will disrupt existing functional models, creating confusion. However, IoT will facilitate the rise of new applications, with automated healthcare monitoring platforms being amongst them. This paper presents the pillars of design for such applications, along with the evaluation of a working prototype that collects ECG traces from a tailor-made device and utilizes the patients smartphone as a Fog gateway for securely sharing them to other authorized entities. This prototype will allow patients to share information to their physicians, monitor their health status independently and notify the authorities rapidly in emergency situations. Historical data will also be available for further analysis, towards identifying patterns that may improve medical diagnoses in the foreseeable future.

Valuing quality of experience: A brave new era of user satisfaction and revenue possibilities

Telecommunication market today is defined by a plethora of innovative products and technologies that constantly raising the bar of technical feasibility in both hardware and software. Meanwhile users constantly demand better quality and improved attributes for all applications, becoming less and less tolerant in errors or inconsistencies. Evaluation methods that were dominant for several years in the field seem to have limited effect on assess end-user satisfaction, leading to unhappy customers and lower revenue for key market players. Ensuring Quality of Service (QoS) proved no longer capable to increase market share therefore a novel evaluation method is necessary. The aim of the present paper is to present a new framework of user-oriented quality assessment that tries to measure the overall experience derived from a telecommunication product. Provided that modern services are based over the principal of sharing an overall experience with others, it seems certain that the new method of estimating Quality of Experience (QoE) will produce much better results, needed by both providers and customers.

Enhancing SDN security for IoT-related deployments through blockchain

The majority of business activity of our integrated and connected world takes place in networks based on cloud computing infrastructure that cross national, geographic and jurisdictional boundaries. Such an efficient entity interconnection is made possible through an emerging networking paradigm, Software Defined Networking (SDN) that intends to vastly simplify policy enforcement and network reconfiguration in a dynamic manner. However, despite the obvious advantages this novel networking paradigm introduces, its increased attack surface compared to traditional networking deployments proved to be a thorny issue that creates skepticism when safety-critical applications are considered. Especially when SDN is used to support Internet-of-Things (IoT)-related networking elements, additional security concerns rise, due to the elevated vulnerability of such deployments to specific types of attacks and the necessity of inter-cloud communication any IoT application would require. The overall number of connected nodes makes the efficient monitoring of all entities a real challenge, that must be tackled to prevent system degradation and service outage. This position paper provides an overview of common security issues of SDN when linked to IoT clouds, describes the design principals of the recently introduced Blockchain paradigm and advocates the reasons that render Blockchain as a significant security factor for solutions where SDN and IoT are involved.

Automated profiling of virtualized media processing functions using telemetry and machine learning

Most media streaming services are composed by different virtualized processing functions such as encoding, packaging, encryption, content stitching etc. Deployment of these functions in the cloud is attractive as it enables flexibility in deployment options and resource allocation for the different functions. Yet, most of the time overprovisioning of cloud resources is necessary in order to meet demand variability. This can be costly, especially for large scale deployments. Prior art proposes resource allocation based on analytical models that minimize the costs of cloud deployments under a quality of service (QoS) constraint. However, these models do not sufficiently capture the underlying complexity of services composed of multiple processing functions. Instead, we introduce a novel methodology based on full-stack telemetry and machine learning to profile virtualized or cloud native media processing functions individually. The basis of the approach consists of investigating 4 categories of performance metrics: throughput, anomaly, latency and entropy (TALE) in offline (stress tests) and online setups using cloud telemetry. Machine learning is then used to profile the media processing function in the targeted cloud/NFV environment and to extract the most relevant cloud level Key Performance Indicators (KPIs) that relate to the final perceived quality and known client side performance indicators. The results enable more efficient monitoring, as only KPI related metrics need to be collected, stored and analyzed, reducing the storage and communication footprints by over 85%. In addition a detailed overview of the functions behavior was obtained, enabling optimized initial configuration and deployment, and more fine-grained dynamic online resource allocation reducing overprovisioning and avoiding function collapse. We further highlight the next steps towards cloud native carrier grade virtualized processing functions relevant for future network architectures such as in emerging 5G architectures.