Distributed Simulation System Dynamic Resource Allocation
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Solution Overview
Problem
Conventional simulation systems struggle to scale and handle large numbers of objects in real-time, leading to overloading, data loss, and difficulties in fault tolerance and stateful migration, especially when simulating complex scenarios like cities with numerous entities.
Innovation Solution
A distributed simulation system that assigns multiple workers to simulate entities, with each worker connected through bridges to entity databases, allowing for dynamic interest component management and data propagation, enabling efficient data communication and load balancing across multiple machines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If computing resources are statically assigned to a portion of the simulated world, then resource allocation is simple, but the system cannot handle dynamic object movement and congestion effectively
Solution Approach 1:
The patent implements dynamic resource allocation by allowing workers to dynamically acquire and release computing resources based on real-time simulation needs. Workers can request resources from a resource manager when needed and release them when complete, enabling the system to adapt to changing object distributions and congestion patterns throughout the simulation runtime.
Solution Approach 2:
A resource manager acts as an intermediary between workers and computing resources. This mediator coordinates resource requests and releases, manages the pool of available resources, and ensures fair and efficient allocation. The resource manager enables workers to access resources dynamically without direct conflict, resolving the contradiction between simple allocation and dynamic adaptability.
2Device complexity
If computing resources are concentrated on a single computing resource, then resource management is simple, but fault tolerance and stateful migration become difficult
Solution Approach 1:
The patent segments computing resources into multiple independent workers distributed across different computing nodes. Each worker manages a portion of the simulated world independently, allowing the system to tolerate failures of individual workers. This segmentation enables fault tolerance while maintaining manageable complexity through standardized worker protocols.
Solution Approach 2:
The system changes the parameter of resource distribution from centralized to distributed across multiple workers. This parameter change enables stateful migration by allowing workers to be dynamically assigned to different computing nodes. When a worker fails or needs migration, its state can be transferred to another node without disrupting the overall simulation, improving reliability while managing complexity through state persistence mechanisms.
3Device complexity
If a single simulation engine is used to simulate the entire world, then system architecture is simple, but scalability to large numbers of objects is limited
Solution Approach 1:
The patent segments the simulation workload into multiple workers, each responsible for simulating a specific portion of the simulated world. This segmentation allows the system to scale by adding more workers to handle larger numbers of objects. Each worker operates independently with its own simulation engine instance, enabling parallel processing and linear scalability.
Solution Approach 2:
The system transitions from a single-point simulation architecture to a distributed architecture across multiple computing nodes. This dimensional change from one to many enables the system to handle larger quantities of objects by utilizing additional computational dimensions. The resource manager coordinates these distributed workers, maintaining architectural manageability while achieving scalability.
4Device complexity
If simulation data is concentrated on a single computing resource, then data management is simple, but stateful migration and data sharing are restricted
Solution Approach 1:
The patent segments simulation data across multiple workers and computing nodes rather than concentrating it on a single resource. Each worker maintains its own local state, enabling independent data management. This segmentation facilitates stateful migration by allowing worker states to be transferred between nodes without requiring centralized data management, improving adaptability while keeping data management complexity manageable through distributed protocols.
Data Source
AI summary
Methods, systems, computer-readable media, and apparatuses for query-based interest in a simulation are presented. An entity comprising one or more components may be simulated. The entity may be modified to include an interest component indicating, for each component in the one or more components of the entity, a query subscription to an entity database. The query subscription may comprise one or more queries. Each query of the one or more queries may comprise a component value that qualifies another entity for inclusion in a query result, and a frequency for receiving, from the entity database, updates on the query result.