Fitting the Puzzle: Towards Source Traffic Modeling For Mobile Instant Messaging

Mobile instant messaging (MIM) via applications such as WhatsApp transformed human communication by enabling the exchange of various different message types, such as text, image, video, or voice, globally at every time of day. Network providers are confronted with a substantial user base and network load which is especially high in group chats where each message needs to be distributed to each member. Since end-to-end encryption restricts insights into user traffic, it becomes essential for network operators to obtain knowledge about the communication and the resulting load on the network through MIM by other means, which makes it necessary to model the network traffic of MIM. In this work, we therefore present a theoretical approach to source traffic modeling for MIM. Therefore, we identify the building blocks of a source traffic model (STM) for MIM and determine missing pieces. We fill the gaps through studies on MIM communication networks, user proximity, media compression and payload size, as well as media file size distribution. Combining existing literature and our work, we present a theoretical modular STM approach which can be used for developing STMs for MIM. With this, we provide a comprehensive description of MIM in the network researching context and enable consideration MIM in future network design.