5GMEDE - 5G Mobile Edge Computing with Enriched Radio Network Information Services

• Main Authors: Akman, A., Monteiro, V., Marques, P., Rodriguez, J., Vieira, P., Marques, H., Abdalla, A.
• Format: Conference Proceeding
• Language: English
• Subjects: 5G mobile communication; Base stations; Complexity theory; Edge computing; Energy consumption; Energy Efficiency; MEC; Mobile applications; Radio access networks; RAN
• ISSN: 2378-4873
• DOI: 10.1109/CAMAD50429.2020.9209310

5G has a number of challenges to solve. Higher data usage and processing power necessities have emerged from the increasing number of mobile users as well as mobile applications becoming more and more demanding. There is a significant need to reduce the latency of the mobile network while cutting down on energy consumption. Backhaul traffic needs to be optimized to avoid setting up costly backhaul connections. Many IoT scenarios have conflicting requirements; the need for cheap and low complexity devices vs the need for processing power. Operators need to come up with value added services to avoid being dumb-pipe operators. The answer to these challenges and more require cloud-computing capabilities within the Radio Access Network (RAN) as well as a platform for mobile operators and third-party application providers to utilize these computing capabilities. This is where Mobile Edge Computing (MEC), one of the key emerging technologies for 5G, comes into play. The 5GMEDE project proposes to not only develop and demonstrate a complete MEC solution, including the MEC framework, Base Station services and applications to run on top, but also offers innovative features like constraint based mobile edge selection, using data analytics to enrich and refine real-time radio network information and utilizing Software Defined Wireless Networks (SDWN) concepts to improve mobility and resource allocation services to enable operators.