Federated Compute Job Assignment via Node Metrics
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Solution Overview
Problem
Existing technologies face challenges in efficiently utilizing distributed computing resources for complex tasks like blockchain verification, due to technical complexity, high costs, and the need for specialized skills and hardware.
Innovation Solution
A system that facilitates the creation of ad-hoc computing node clusters by federating individually controlled computing resources, using a node management system to transmit tokens, receive metrics, and assign compute jobs, thereby optimizing distributed computing environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If distributed computing systems are used to solve complex computational problems, then computational capability is improved, but system complexity increases
Solution Approach 1:
The patent introduces a job manager as an intermediary component that mediates between compute job sources and federated computing nodes. The job manager receives compute jobs, determines appropriate federations, and routes jobs to suitable nodes, thereby simplifying the overall system complexity while maintaining high computational capability through distributed processing.
Solution Approach 2:
The system segments the distributed computing environment into independent federations of computing nodes, each with specific characteristics. This segmentation allows the job manager to route jobs to appropriate federations based on job requirements, reducing the complexity of managing the entire distributed system as a monolithic entity.
2Power
If specialized hardware and advanced skills are required for distributed computing, then computational performance is improved, but ease of operation deteriorates
Solution Approach 1:
The system enables computing nodes to self-register and self-describe their capabilities to the job manager. Nodes automatically provide information about their hardware specifications, available resources, and suitable workloads, eliminating the need for manual configuration and reducing the operational burden on users while maintaining high computational performance.
Solution Approach 2:
The job manager acts as an intermediary that abstracts the complexity of distributed system management from end users. It handles job distribution, node selection, and resource allocation automatically, allowing users to submit compute jobs without needing specialized knowledge of distributed computing architectures.
3Power
If computing resources are consolidated into large-scale systems, then computational power is improved, but cost increases
Solution Approach 1:
The patent creates a universal job management system that can handle multiple types of compute jobs across diverse federations of computing nodes. This multi-functional approach allows the system to efficiently utilize existing computing resources for various workloads, maximizing resource utilization and reducing the need for dedicated specialized hardware, thereby lowering costs while maintaining high computational power.
Solution Approach 2:
The system merges multiple independent computing nodes into federations that can be dynamically allocated to different job types. By combining resources from multiple sources and allowing flexible allocation, the system achieves high computational power comparable to large-scale consolidated systems while distributing costs across multiple participants.
Data Source
AI summary
Systems and methods are provided for improving compute job distribution using federated computing nodes. Metrics and user preferences associated with particular nodes in the federation of computing nodes are received. Compute jobs are assigned, based on the metrics and user preferences, to the particular nodes by assembling a compute job data packet comprising the one or more compute jobs. Assigned compute jobs and unrelated compute tasks can also be dynamically modified in order to optimize compute job completion based on the received metrics.