Call for Papers -- Feature Topic, Vol.15, No.10, 2018

The multimedia services have been on the rise during the last decade, and video service has been gaining importance in wireless networks. However, currently, there is still no way to guarantee the video quality of experience (QoE) due to the differences of service characteristics and the human perception limits. In addition to the quality of experience, future wireless networks also need to take care of the video service continuity for special cases such as high-speed moving and surge in traffic. However, existing evaluation of the multimedia services only considers several simple factors such as packet loss rate or bandwidth delay. Considering the deficiency in existing wireless networks nowadays, an excellent QoE model, which directly reflects the user’s perspective of the overall performance of the network services, is the key to ensuring user’s service experience in future multimedia communications.

With the data-driven QoE model established, QoE-based network management is promising for improving the quality of multimedia services from users’ perspective. The QoE-driven optimization may centralize on network resource allocation or multimedia application operation, both of which aim to maximize the QoE scores over the resource constraint transmission conditions. Due to the different characteristics of different wireless network scenarios, the optimization scheme should trade off among the QoS metrics in order to achieve the best QoE and improve the efficiency of the network resource. Besides, the fairness of the heterogeneous users should also be taken into account to perform fair multimedia service delivery while optimizing the overall QoE scores.

QoE-based applications are far more than network optimization. While the original goal of proposing QoE is to better evaluate the multimedia services and to provide guidance for network management, it can also apply to the field of analysis and processing of multimedia data. Multimedia analysis from QoE big data, for instance, presents a good potential in the era of mobile Internet, big data and cloud computing. Moreover, QoE-driven media processing and transmission over the cloud is poised to cater to the needs and preferences of users, and thus obtains high gain in terms of QoE.

For this reason, this special issue calls for papers on the topic of “Quality of Experience for Multimedia Communications” to explore the key technologies and possible applications in future QoE-based multimedia communication networks.

Submission Deadline: May 15, 2018

Acceptance Notification (1st round): June 5, 2018

Minor Revision Due: July 5, 2018

Final Decision Due: July 25, 2018

Final Manuscript Due: August 20, 2018

Publication Date: October 15, 2018

 

 

Xiaoming Tao, Tsinghua University, China

Jiajia Liu, XiDian University, China

Shiwen Mao, Auburn University, USA

Mérouane Debbah, CentraleSupélec and Huawei, France

Chunxiao Jiang, Tsinghua University, China

 

l TRACK 1:QOE MODELS AND EVALUATION METHODS

n QoE evaluation methodologies and metrics

n QoE models, their applications and use cases

n Datasets for QoE validation and benchmarking

n KPI and KQI definition for QoE optimization in emerging environments (5G, IoT, M2M, Cloud)

 

l TRACK 2: QOE-BASED NETWORK OPTIMIZATION

n QoE-based network management

n QoE-based cooperative computing networks

n QoE-based routing schemes

n Cognitive networks with QoE

n QoE-based network and service monitoring and troubleshooting

 

l TRACK 3: QOE-BASED APPLICATIONS

n QoE management in Smart Cities applications

n Media analytics from QoE Big Data

n Multimedia processing with QoE

n QoE-driven media processing and transmission over the cloud

n QoE-based adaptive media services