Event Driven Simulation Architecture for Scalable Multiplayer Games
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Solution Overview
Problem
Current multiplayer game architectures face challenges in scalability, latency, and fault tolerance, particularly in handling large user bases and maintaining efficient interaction across multiple regions or 'shards' without allowing inter-shard user interaction.
Innovation Solution
A system comprising an object store layer, a communication layer, and a simulation layer that enables low-latency, high-bandwidth, and fault-tolerant event-driven simulations by using a stateless task processor, transactional context, and distributed object management, allowing for load balancing and preventing deadlocks through timestamp-based task prioritization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If regions limit the number of users simultaneously connected to maintain system performance, then latency is controlled and system stability is maintained, but the number of users that may be allowed to enter a particular region is restricted
Solution Approach 1:
The system segments users into different priority levels (low, normal, high) and processes them through different queues. This allows the region to maintain performance for normal users while accommodating priority users, effectively increasing the total number of users the system can handle without degrading overall performance.
Solution Approach 2:
The system dynamically changes the parameter of user capacity by introducing priority-based admission control. Instead of a fixed user limit, the system adjusts effective capacity based on user priority, allowing flexible scaling of user numbers while maintaining performance through selective prioritization.
2Productivity
If shards are implemented to increase the number of users in a region, then user capacity increases, but users within different shards cannot interact
Solution Approach 1:
The object store layer serves multiple functions: it stores objects for individual shards and also enables cross-shard object sharing. This universal storage mechanism allows users in different shards to interact through shared objects, eliminating the isolation problem while maintaining the scalability benefits of shards.
Solution Approach 2:
The object store layer acts as an intermediary between different shards. Instead of direct peer-to-peer interaction between shards, communication and interaction are mediated through the shared object store, enabling cross-shard functionality while preserving shard independence for scalability.
3Reliability
If periodic dumps to hard-drive back-up are performed for failure recovery, then fault tolerance is provided, but system performance and speed are reduced
Solution Approach 1:
The system implements periodic checkpointing at predetermined intervals rather than continuous backup. This periodic action provides fault tolerance by capturing state at regular intervals while minimizing performance impact by not requiring continuous I/O operations, thus balancing reliability and speed.
Solution Approach 2:
The system performs preliminary checkpointing before potential failure points by saving state at predetermined intervals. This preliminary action ensures that if a failure occurs, the system can recover to the most recent checkpoint, providing fault tolerance without requiring post-failure complex recovery operations that would slow down the system.
4Ease of manufacture
If a single process executes all active game states in memory, then implementation simplicity is maintained, but scalability and performance are limited
Solution Approach 1:
The system segments the monolithic single-process architecture into multiple independent processes, each handling specific game states or regions. This segmentation improves scalability by allowing parallel execution and independent resource allocation while maintaining implementation simplicity through standardized process templates and interfaces.
Solution Approach 2:
The system transitions from a single-dimensional single-process model to a multi-dimensional distributed process model. By adding the dimension of process distribution and introducing the object store layer as a new architectural dimension, the system achieves scalability while maintaining simplicity through standardized object interfaces that abstract away the complexity of distributed execution.
Data Source
AI summary
A system that includes an object store layer configured to store a plurality of objects, wherein each of the plurality of objects comprises a method, a communication layer configured to receive an event from a user and generate a task based on the event, and a simulation layer configured to retrieve one of the plurality of objects responsive to execution of the task and execute the method associated with the one of the plurality of objects.