Improving QoS and QoE for Mobile Communications – Journal of Computer Networks and Communications (JCNC)

Improving QoS and QoE for Mobile Communications – Journal of Computer Networks and Communications (JCNC)

Background and Scope:
The number of mobile Internet users and the volume of traffic generated by them keep increasing every year. In this context, the proliferation of smartphones, tablets, and cheap mobile data tariffs along with the emergence of new media services and the increasing use of 3G and upcoming 4G cellular networks as a substitute for traditional fixed-line connectivity, creates a host of new challenges when it comes to achieving good network performance and a satisfactory user experience. Beyond traditional multimedia applications such as IPTV and video conferencing which have a fairly very well-known set of performance requirements from the network perspective, the increasing uptake of web- and cloud-based services also introduces a new set of requirements for network performance. Furthermore, the evolution of mobile networks towards an all-IP paradigm (e.g. LTE) introduces new challenges for traditionally circuit-switched services such as voice telephony, where it is critical for operators to guarantee minimum levels of performance and improve them where possible.

For these reasons, operators need to understand, measure, and manage both quality and performance of the 3G and 4G services they offer. This has to be fulfilled on the technical quality of service (QoS) as well as on the quality of experience (QoE) level, since ultimately it is the human end-user who decides whether the quality of a given service is inacceptable, sufficient, or even exceeding expectations.

Topics of Interest:
This special issue aims at bringing together the state-of-the-art research on evaluating and improving QoS and QoE in wireless 3GPP networks. We encourage authors to submit recent unpublished work focused on the following topics. Potential topics include, but are not limited to:
. New mobile applications with special requirements in terms of network performance . Methods for objective and subjective QoS and QoE assessment . QoE evaluation methodologies for novel emerging mobile services . Subjective QoE testing of mobile services in the lab and in the field . Measurement, simulation, and evaluation techniques, tools, and testbeds . Combining user-, application-, and network-level measurements on different platforms . Modeling and mapping relationships between QoS and QoE . QoS and QoE monitoring in 3G and 4G networks . QoS- and QoE-driven resource control and service optimization in 4G networks, in particular regarding cross-layer approaches, extensions of current standards, and multitechnology connectivity . Trade-offs in contrast to QoS or QoE requirements (e.g., energy-efficient mechanisms coping with limited battery capacity, security, and reliability issues)

Before submission authors should carefully read over the journal’s Author Guidelines, which are located at Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at according to the following timetable:
Manuscript Due Friday, 7 Sept 2012
First Round of Reviews Friday, 30 Nov 2012
Publication Date Friday, 4 Jan 2013

Lead Guest Editor:
. Pedro Merino, University of Malaga, Teatinos Campus, 29071 Malaga, Spain

Guest Editors:
. Maria G. Martini, Faculty of Computing, Information Systems and Mathematics, Kingston University, Kingston Upon Thames, UK . Raimund Schatz, Telecommunications Research Center Vienna (FTW), Vienna, Austria . Lea Skorin-Kapov, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, Zagreb, Croatia . Martin Varela, VTT Technical Research Centre of Finland, P.O. 1100, 90571 Oulu, Finland

Online version of this CfP:

IEEE comm magazine – QoE management in emerging multimedia services

IEEE Communications Magazine

Feature topic on “QoE management in emerging multimedia services”


FINAL MANUSCRIPT: March 10, 2012


The realization of the paradigm of Internet anywhere, anytime and any-device and the diffusion of end-user multimedia devices with powerful and user-friendly capabilities such as smartphones, tablets pc, mobile gaming terminals and ebooks, are leading to the proliferation of a significant amount of emerging multimedia services: immersive environments, mobile online gaming, 3D virtual world, book/newspaper consumption, social networking, IPTV applications, just to cite a few. Some of these services have already reached a major market success, such as the case of newspaper/magazine mobile readers and smartphone multimedia apps. Their success could be achieved especially because a user-centered approach has been followed to design the whole process of content production, service activation, content consumption, service management and updating. Indeed, the quality of the user experience, the perceived simplicity of accessing and interacting with systems and services, and the effective and acceptable
hiding of the complexity of underlying technologies are determining factors for success or failure of these novel services, as well as graceful degradation. The management of the Quality of Experience (QoE) is then undoubtedly a crucial concept in the deployment of future successful services, and it is straightforward to be understood as well complex and stimulating to be implemented in real systems. The complexity is mainly due to the difficulty of its modeling, evaluation, and translation in what for more than a decade we have been mainly dealing with (partially in its substitution), that is the Quality of Services (QoS). Whereas QoS can be now easily measured, monitored and controlled at both the networking and application layers and
at the end-system and network sides, the quality of experience is something that is still quite intricate to be managed. The practice in evaluating the QoS can be exploited in evaluating the QoE, but it is just a starting point for a complete QoE management procedure, which should encompass at least the following activities: monitoring of the experience of the user when consuming the service, adapting the provisioning of the content on the basis of the varying context conditions (e.g. network status, user behavior, user
profile, environment), predicting potential experience level degradation, and masking quality degradation due to abrupt system changes. To have a complete control of the final user experience, all these tasks need to be performed in a coordinated way and their real effectiveness depends on the validity of the adopted user perception model.

Objectives The purpose of this special issue is to present to the magazine’s audience a concise, tutorial oriented reference of the state-of-the-art, current and future research challenges and trends on the management of QoE in emerging multimedia services. To achieve this goal the special issue seeks original research and review papers that survey and present new ideas, leading-edge research prototype development, trials and early deployment, and performance evaluations in the following areas: * Definition of QoE (Quality of Experience) for emerging services * Relationship between QoE and QoS
* Architectures for the management of the QoE in emerging multimedia services
* Offline and online prediction and evaluation of QoE * QoE-oriented multimedia traffic management * QoE-oriented multimedia source and channel coding * Testbeds for performance evaluation of QoE-oriented systems
* Middleware solutions for QoE management * Adaptive and self-configuring solutions for QoE management * Advanced, scalable service-aware QoE-oriented traffic control and management
* QoE management in heterogeneous networks

Prospective authors should follow the IEEE Communications Magazine manuscript format described in the Authors Guidelines
( All articles to be considered for publication must be submitted through the IEEE Manuscript Central ( Guest Editors:
* Luigi Atzori, Dept. of Electrical and Electronic Engineering, University of Cagliari, Italy
* Chang Wen Chen, Dept. of Computer Science and Engineering, University at Buffalo, NJ, USA
* Tasos Dagiuklas, Technological Educational Institute of Mesolonghi, Greece * Hong Ren Wu, Royal Melbourne Institute of Technology, Australia

TCSVT Special Issue Video Analysis on Resource-Limited Systems

IEEE Transactions Circuits and Systems for Video Technology

Special Issue on
Video Analysis on Resource-Limited Systems

Guest Editors
Rama Chellappa, University of Maryland, USA
Andrea Cavallaro, Queen Mary, University of London, UK
Ying Wu, Northwestern University, USA
Caifeng Shan, Philips Research, The Netherlands
Yun (Raymond) Fu, University at Buffalo (SUNY), USA
Kari Pulli, Nokia Research Center (NRC) Palo Alto, USA

Submission deadline: Dec. 15, 2010
Notification of acceptance: Jun. 15, 2011
Final manuscript due: Jun. 30, 2011
Tentative publication date: Oct. 2011

In many real-world video analytics systems, the available resource is limited. This could mean low-quality data (e.g., limited imaging resolution/sensor size/frame rate), such as video footage from surveillance cameras and videos captured by consumers via mobile or wearable cameras. Another dimension comes from limited amount of processing power, for example, on mobile camera phones. There is a huge demand for video analysis and computer vision techniques on resource-limited systems. However, although there are some existing studies, video analysis on low-quality video data or with limited computing power is still an under-explored field. The existing video analysis research mainly focuses on high-performance systems, that is, high-quality video data or powerful computing platforms. There aremany challenges when addressing video analysis on resource-limited systems. For example, how to effectively extract representative visual features from low-quality data? How to fuse mult
iple low-resolution frames for reliable recognition? How to accelerate vision algorithms for use on mobile platforms? How to mitigate degrading factors caused by the low quality data? We have to adapt the existing approaches developed for high-performance systems or find new techniques suitable for resource-limited systems.

This special issue seeks to present and highlight the latest developmentson video analysis and computer vision on resource-limited systems. Submissions that address real-world applications are especially encouraged.

Topics of interest include, but are not limited to,
– Feature extraction from low-quality data
– Super-resolution
– Video stabilization
– Object detection in low-quality data
– Visual tracking on resource-limited systems
– Image recognition on mobile devices
– Face image analysis on resource-limited systems
– (Soft-)biometrics (face, body, gait, … ) in low-quality data – Gesture recognition in low-quality data
– Human activity analysis in low-quality data
– Video analysis on resource-limited platforms (UAVs, toy robots, capsuleendoscopy, …) – Energy optimization for video coding on resource-limited devices – Multiple-view analysis of low-quality data
– Low-cost smart camera networks with embedded computing
– Video analysis on low-cost non-classical cameras (e.g., omni-directional cameras)
– Real-world applications on resource-limited systems (smart environments, safety and surveillance, entertainment …) – Evaluation of video analysis algorithms on resource-limited systems

New paper accepted for publication

The manuscript entitled as QoE-driven dynamic management proposals for 3G VoIP services authored by Jose-Oscar Fajardoa, Fidel Liberal, Is-Haka Mkwawa, Lingfen Sun and Harilaos Koumaras has been accepted for publication by the Journal of Computer Communications, Elsevier.

In this paper the authors propose a combined approach where service level adaptation is considered first and, provided that no suitable parameter combination is capable of providing enough QoE, a change of network state will be suggested. In order to do so we analyse the performance of the end-to-end (e2e) performance metrics in thisĀ  convergent scenario, the root causes of possible degradations and, finally, the combined effects of the different network segments and their impact on the user perceived QoE. We show the the map of best performing VoIP configurations for every state of the network segments. Furthermore, considering each of these configurations, we analyse the acceptability of the service or the convenience of trying to modify the network state. Finally, a lightweight implementation based on simple network state estimation and decision heurisitics is proposed and validated in terms of accuracy and responsiveness.