Video Streaming Service Solutions

Dear Colleagues,

Currently, video generates more than 80% of internet traffic and is an information medium on which many services are based. One of the main ways of delivering content on IP networks is video streaming, whose condition has a significant impact on the quality of the services offered.

Parameters such as network throughput, delays, and jitter are the basic factors that should be controlled because they have a direct impact on the quality of the streaming service.

They become particularly important when talking about the implementation of real-time services.

Moreover, various unfavorable phenomena that occur in wired and, in particular, wireless packet networks affect packet loss, which reduces the quality of the service provided.

Therefore, there is a need to counteract the unfavorable consequences of the abovementioned phenomena, including by building networks with high bandwidth which are safe and resistant to external interference. On the other hand, there is a need to develop more efficient coding methods, implement new codecs, design new communication protocols, and implement dynamic and adaptive streaming methods. Once all this has been achieved, the next step is to measure and determine the resulting service quality. This can be achieved by using existing or implementing new methods, e.g., methods based on machine learning, for assessing the quality of services.

This Special Issue is devoted to the current and future challenges faced by content and service providers, as well as network operators, to ensure the highest level of quality of services provided to users.

In particular, this Special Issue will be devoted to, but is not limited to, topics such as the following:

• Video streaming.
• Development of new streaming techniques.
• Resource-efficient streaming algorithms.
• Adaptive dynamic streaming on IP networks.
• Video codecs and compression.
• Mobile video streaming applications.
• Multimedia applications.
• Streaming protocols.
• Network performance.
• Critical network challenges.
• Using neural networks to improve video streaming performance.
• Cloud-based video streaming services.
• Cloud video processing.
• Video streaming solutions for scalability and cost-effectiveness.
• Future communication systems.
• Quality of Service.
• Quality of Experience.
• Security issues in wired and wireless networks.
• Subjective video quality assessments.
• Objective video quality evaluations.
• Classical and machine learning-based quality assessment methods.

Dr. Janusz Klink
Dr. Stefan P. Brachmański
Prof. Dr. Tadeus Uhl
Guest Editors

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