Event-Based View Synchronization for Lower Simulation Latency
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Solution Overview
Problem
Existing virtual simulation systems face inefficiencies in resource consumption and data latency due to the reliance on multiple distributed clusters of machines managed by a single server, which can lead to suboptimal data throughput and complexity in complex simulations.
Innovation Solution
A simulation system utilizing a single machine architecture with modules for state synchronization, authority assignment, interest management, subscription matching, and view synchronization to manage and synchronize views efficiently, reducing resource consumption and improving data throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a distributed cluster of machines is used for simulation, then the simulation can handle complex scenarios, but resource consumption increases and data latency worsens
Solution Approach 1:
The simulation system is segmented into multiple worker modules, each responsible for specific simulation scenarios. Each worker module independently manages its own simulation context and data, allowing parallel processing without requiring a fully distributed cluster. This segmentation enables complex simulations to be handled through coordinated modular workers rather than requiring extensive distributed infrastructure.
2Quantity of substance
If multiple distributed clusters are used, then more simulation capacity is available, but data throughput decreases due to latency
Solution Approach 1:
Multiple worker modules are merged into a unified simulation system that shares common data structures and synchronization mechanisms. The workers communicate through standardized interfaces and share access to simulation state data, eliminating the need for complex inter-cluster data transfer. This merging maintains high simulation capacity while improving data throughput by reducing network latency associated with distributed clusters.
3Device complexity
If a single server manages distributed clusters, then coordination is simplified, but the system becomes a bottleneck for data synchronization
Solution Approach 1:
The central coordination function is extracted from a single server and distributed among worker modules that autonomously manage their own state synchronization. Each worker module maintains local simulation state and only synchronizes specific data elements with others when necessary. This extraction eliminates the single-server bottleneck while maintaining coordination through peer-to-peer communication and event-driven synchronization.
4Adaptability or versatility
If distributed clusters are used, then simulation scalability is improved, but view synchronization complexity increases
Solution Approach 1:
Each worker module maintains local simulation state and view data specific to its assigned scenarios. View synchronization is performed locally within each worker rather than being coordinated centrally across the entire distributed system. This local quality approach allows the system to scale by adding workers while keeping view synchronization complexity contained within individual modules rather than increasing system-wide complexity.
Data Source
AI summary
Methods, systems, computer-readable media, and apparatuses for performing, providing, managing, executing, and/or running a simulation are presented. In one or more embodiments, a computing device may receive one or more changes associated with one of a plurality of entities being simulated. The computing device may determine, based on the one or more changes, one or more component updates associated with the one of the plurality of entities, and determine one or more authority change events occurred on one or more components of the one of the plurality of entities. The computing device may further determine that one or more interest query change events occurred and that one or more interest view change events occurred. The computing device may further determine one or more worker protocol operations, and synchronize, based on the one or more worker protocol operations, view changes with one or more interested workers.


