In distributed real-time applications, such as online games or interactive conferencing systems, timeliness of update event dissemination is a prevailing requirement. Direct connections are often the best solution. However, participants’ connection bandwidths, especially uplink capacities of asymmetric end user Internet connections, impose a limit to this. We present and evaluate a lightweight local algorithm that optimizes many-to-many event dissemination in highly dynamic scenarios. The algorithm exploits the high clustering of interest networks, as observed in virtual environments based on local vision, but also in social networks of many kinds. Our approach allows reducing traffic by aggregating messages as well as balancing traffic among participants based on their capabilities.

Abstract—The rising number of mobile devices and their increasing computational capabilities enable new interactive context-sensitive applications. Popular examples are augmented reality games such as Google’s Ingress, where users interact with each other in the real world while being part of the game at the same time. This local interaction pattern in the real world as well as in the game is not reflected in the underlying communication pattern. Every locally generated game event is first transferred to a backend server via a cellular connection, from where it is then further disseminated to all players within the given area of interest. This communiation pattern introduces significant delays and limits the interactivity of the game. In this work, we propose an event dissemination system that exploits the locality characteristics of mobile augmented reality games to (i) enable and configure local peer-to-peer dissemination of events when appropriate and (ii) reconfigure or replace the utilized peer-to-peer protocol to adapt to a wide range of requirements. Through extensive evaluation we show that the proposed system decreases the delivery delay by a factor of eight compared to the existing communication pattern, leading to significantly increased information accuracy. I.