Distributed optimization of event dissemination exploiting interest clustering

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.