G-COPSS: A Content Centric Communication Infrastructure for Gaming Applications

Abstract

Information-Centric Networking provides substantial flexibility for users to obtain information without knowing the source of information or its current location. With users increasingly focused on an online world, an emerging challenge for the network infrastructure is to support Massively Multiplayer Online Role Playing Game (MMORPG). Currently, MMORPG is built on IP infrastructure with the primary responsibility resting on servers for disseminating control messages and predicting/retrieving objects belonging to each player's view. Scale and timeliness are major challenges of such a server-oriented gaming architecture. Limited server resources significantly impair the user's interactive experience, requiring game implementations to limit the number of players in a single game instance. We propose Gaming over COPSS (G-COPSS), a distributed communication infrastructure using a Content-Oriented Pub/Sub System (COPSS) to enable efficient decentralized information dissemination in MMORPG, jointly exploiting the network and end-systems for player management and information dissemination. G-COPSS aims to scale well in the number of players in a single game, while still meeting users' response time requirements. We have implemented G-COPSS on top of the open-source CCNx implementation. We use a simple game with a hierarchical map to carefully micro benchmark the implementation and the processing involved in managing game dynamics. We have also micro benchmarked the game based on NDN and a server with an IP infrastructure. We emulate an application that is particularly emblematic of MMORPG -- Counter-Strike -- but one in which all players share a hierarchical structured map. Using trace-driven simulation, we demonstrate that G-COPSS can achieve high scalability and tight timeliness requirements of MMORPG. The simulator is parameterized based on micro benchmarks of our implementation. Our evaluations show that G-COPSS provides orders of magnitude improvement in update latency and a factor of two reduction in aggregate network load compared to a server-based implementation.