Distributed physics in virtual networking multiplayer game
Virtual Distributed Physics Network is a Physics Engine Network Communication between multiple nodes together through cloud and performance in real time physics interaction between each node’s objects within a virtual environment. Many users of Virtual Distributed Physics Networking aims to achieve...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2017
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| Online Access: | http://hdl.handle.net/10356/70036 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Virtual Distributed Physics Network is a Physics Engine Network Communication between multiple nodes together through cloud and performance in real time physics interaction between each node’s objects within a virtual environment. Many users of Virtual Distributed Physics Networking aims to achieve the realistic Physics phenomena reaction on realtime games, however, network update is expensive when there are multiple nodes interacting between objects in the environment which can cause a degradation of physics performance.
Consistency is a key requirement of networked multiplayer computer games. Currently, these
methods update an entity’s states based on measures of its spatial and temporal inconsistencies. In general, considering the inconsistencies associated with the entity’s interactions with other environmental objects, it can potentially lead to significant differences between what users see and experience. This research paper proposes a simple technique that requires no highlevel understanding of networking, yet, to achieve the physics aware consistency with reasonable latency for the future of Virtual Distributed Physics Network Gaming.
In physics network, it will consist of TimeSpace Dead Reckoning technique, 3D optimization, Physics RigiBody and Network Architecture. The experiment showed that this technique will be able to improve consistency with realistic visual gameplay and reduced bandwidth usage. Thus, this technique is simple to understand, in comparison to other network optimizations that are available in current technology. Henceforth, the future of the work can be improved further with hybrid of algorithm techniques, with the TimeSpace Dead Reckoning, as part of it. |
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