1. Multiparty Call Control at the Network Edge
- Author
-
Ivaylo Asenov, Denitsa Velkova, Ivaylo Atanasov, and Evelina Pencheva
- Subjects
Emulation ,Edge device ,Application programming interface ,business.industry ,Computer science ,05 social sciences ,Mission critical ,050801 communication & media studies ,020206 networking & telecommunications ,02 engineering and technology ,Call control ,multi-access edge computing ,application programming interfaces ,0508 media and communications ,Next-generation network ,0202 electrical engineering, electronic engineering, information engineering ,next generation networking ,network function virtualization ,Session (computer science) ,lcsh:Electrical engineering. Electronics. Nuclear engineering ,Electrical and Electronic Engineering ,business ,lcsh:TK1-9971 ,Edge computing ,Computer network - Abstract
Network programmability is a key feature of fifth generation (5G) system which, in combination with cloud-based services, can support many use cases, including mission critical and healthcare communications. Programmability enables flexibility in customization of service connectivity. Multi-access Edge Computing (MEC) services and applications are enablers for network programmability. In this paper, MEC capabilities for programmability of multiparty multimedia call control at the network edge are studied. Multiparty video calls are one of the key applications of 5G, and are efficient way to exchange ideas, knowledge, expertise, information, and so on. The paper presents an approach to design MEC Application Programming Interfaces (APIs) which enable third party applications to create multiparty multimedia sessions and dynamically manage session participations. The API functionality is described by required information and message flows. The paper specifies the proposed MEC API with data model. Feasibility study includes modelling and formal validation of multiparty session state models supported by the network and mobile edge application. The latency injected by the API is evaluated by emulation.
- Published
- 2020