Adaptive Event Dissemination for Peer-to-Peer Multiplayer Online Games
  In this paper we show that gossip algorithms may be effectively used to disseminate game events in Peer-to-Peer (P2P) Multiplayer Online Games (MOGs). Game events are disseminated through an overlay network. The proposed scheme exploits the typical behavior of players to tune the data dissemination. In fact, it is well known that users playing a MOG typically generate game events at a rate that can be approximated using some (game dependent) probability distribution. Hence, as soon as a given node experiences a reception rate, for messages coming from a given peer, which is lower than expected, it can send a stimulus to the neighbor that usually forwards these messages, asking it to increase its dissemination probability. Three variants of this approach will be studied. According to the first one, upon reception of a stimulus from a neighbor, a peer increases its dissemination probability towards that node irrespectively from the sender. In the second protocol a peer increases only the dissemination probability for a given sender towards all its neighbors. Finally, the third protocol takes into consideration both the sender and the neighbor in order to decide how to increase the dissemination probability. We performed extensive simulations to assess the efficacy of the proposed scheme, and based on the simulation results we compare the different dissemination protocols. The results confirm that adaptive gossip schemes are indeed effective and deserve further investigation. 
Gabriele D'Angelo, Stefano Ferretti, Moreno Marzolla
cs.NI cs.DC