Client-Side Filesystem for Distributed Computation Orchestration
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Solution Overview
Problem
Current computer network systems face challenges in efficiently managing and orchestrating computations across multiple hosts, particularly in terms of scalability, network bandwidth usage, and data immutability, while ensuring reproducibility and auditing capabilities.
Innovation Solution
A client-side filesystem and computation orchestrator system that utilizes a repository manager to store and manage data and program code, allowing clients to access and update data locally, cache credentials for efficient network usage, and orchestrate computations across hosts based on capabilities, ensuring immutability and reproducibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a centralized repository manager is used to manage computations across multiple hosts, then scalability and centralized control are improved, but network bandwidth usage increases and system complexity increases
Solution Approach 1:
The system performs preliminary actions by caching credentials and computing parameters on client-side before they are needed for computation execution. The repository manager pre-manages parameter variations and computes what parameters to vary based on past computations, reducing real-time network communication requirements.
Solution Approach 2:
The client-side filesystem acts as an intermediary between the centralized repository manager and the computation hosts. It caches credentials and manages local parameter variations, reducing the frequency and amount of network traffic required for computation orchestration while maintaining scalability.
2Extent of automation
If a centralized repository manager is used to manage computations across multiple hosts, then centralized control and coordination are improved, but device complexity increases
Solution Approach 1:
The system segments complexity by implementing a client-side filesystem that handles local computation coordination and parameter management independently. This segmentation allows the centralized repository manager to focus on high-level orchestration while client-side components handle detailed execution, reducing overall system complexity.
Solution Approach 2:
The client-side filesystem performs self-service by autonomously managing credential caching, local parameter variations, and computation execution without requiring constant centralized control. This reduces the complexity burden on the centralized system while maintaining automation.
3Reliability
If data is stored and managed in a remote repository, then data immutability and auditing capabilities are improved, but network bandwidth usage and access speed decrease
Solution Approach 1:
The system performs preliminary actions by caching credentials and pre-computing parameter variations on the client-side. This reduces the need for frequent network requests to the remote repository, maintaining data immutability while minimizing bandwidth consumption during computation execution.
Solution Approach 2:
The client-side filesystem creates local copies of credentials and parameter data needed for computation execution. This copying reduces the frequency of network requests to the remote repository, maintaining data immutability and audit capabilities while reducing network bandwidth usage.
4Adaptability or versatility
If computations are orchestrated across multiple hosts with different capabilities, then adaptability and resource utilization are improved, but coordination complexity and network communication increase
Solution Approach 1:
The system applies local quality by allowing each host to have customized computation parameters and capabilities managed locally on the client-side filesystem. This enables adaptability to different host capabilities while reducing coordination complexity through decentralized parameter management.
Solution Approach 2:
The repository manager performs preliminary action by pre-determining which parameters to vary based on past computation outcomes. This reduces real-time coordination complexity while maintaining adaptability to different host capabilities through pre-computed parameter strategies.
Data Source
AI summary
Methods, systems, and computer-readable media for parameter variations for computations using a remote repository are disclosed. A first computation is assigned to a first set of one or more hosts. The first computation is associated with first parameters including one or more inputs and program code. A second computation is assigned to a second set of one or more hosts and is associated with a second set of parameters. Execution of the first computation is initiated using the first set of hosts and the first set of parameters. Local copies of the input(s) and program code are obtained from a storage service using a TO credential supplied by a repository manager. Execution of the second computation is initiated using the second set of hosts and the second set of parameters as obtained using a credential supplied by the repository manager.