Time-space consistency in large-scale distributed virtual environments
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Proceedings of 3rd ACM SIGCOMM workshop on Network and system support for games
Networking and Online Games
Analysis of factors affecting players' performance and perception in multiplayer games
NetGames '05 Proceedings of 4th ACM SIGCOMM workshop on Network and system support for games
Latency can kill: precision and deadline in online games
MMSys '10 Proceedings of the first annual ACM SIGMM conference on Multimedia systems
Proceedings of the 9th Annual Workshop on Network and Systems Support for Games
Peer-to-peer architectures for massively multiplayer online games: A Survey
ACM Computing Surveys (CSUR)
Assessing the impact of latency and jitter on the perceived quality of call of duty modern warfare 2
HCI'13 Proceedings of the 15th international conference on Human-Computer Interaction: users and contexts of use - Volume Part III
On Optimizing MMVEs in Network-Aware Clouds
Proceedings of International Workshop on Massively Multiuser Virtual Environments
Hi-index | 0.00 |
The ultimate goal of both game developers and network engineers is to provide a satisfactory quality of experience (QoE) for players. Most past works resort the subjective approaches to assess QoE which have serious limitations. But because of the interdependency of the quality metrics on game playability and the involvement of many players' subjective factors, defining an objective evaluation methodology for QoE faces some challenges. This paper presents an objective evaluation framework for QoE which based on our insights into the causal relationships between network delay, system consistency and QoE. First we breakdown QoE into three basic properties, then we propose to link a player's perception of quality to a novel definition of inconsistency that can then be matched with the three basic properties. Corresponding metrics are created to quantify the inconsistencies. Taking these objective inconsistencies as input, and the subjective QoE properties as output, a mapping function is derived. After aggregating the QoE properties that capture the quality of a single game scenario, we sum the weighted QoE of all the game scenarios to obtain a final overall objective playability evaluation of a game.