Programmable networks, Human factors and Machine learning.
The non-cooperative competition of network resources between a growing number of adaptive media applications has a significant detrimental impact on user experience and network efficiency. This can lead to knock-on effects on the digital economy and digital public services, which are increasingly dependent on high quality and reliable media streaming. Future network management must leverage application and user-level cognitive factors in order to allocate scarce network resources effectively and intelligently.
SDCN aims at developing software-defined cognitive networking to ensure the user experience, user-level fairness and network efficiency of online adaptive media using SDN-assisted and QoE-aware resource management. SDCN will lay the groundwork for a great leap from the conventional resource provisioning and traffic engineering schemes to context-aware network management especially in the context of future online video streaming, 5G and big data.
The project is partnered with Hewlett Packard Enterprise Aruba and Lancaster University.
Research outcomes, blog posts and social media content related to SDCN do not necessarily represent the views of any company, institution, or individual associated with SDCN.