Adaptive Event Dissemination for Peer-to-Peer Multiplayer Online Games
Gabriele D'Angelo, Stefano Ferretti, Moreno Marzolla

TL;DR
This paper proposes adaptive gossip algorithms for efficient event dissemination in P2P multiplayer online games, tuning message spread based on player behavior to improve performance.
Contribution
It introduces three adaptive gossip protocols that adjust dissemination probabilities based on reception rates, enhancing event distribution in P2P MOGs.
Findings
Adaptive schemes improve dissemination efficiency
Protocols outperform static dissemination methods
Simulation results validate effectiveness of proposed algorithms
Abstract
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…
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Taxonomy
TopicsEvolutionary Game Theory and Cooperation · Complex Network Analysis Techniques · Mathematical and Theoretical Epidemiology and Ecology Models
