Dynamic Data Cluster Routing via Bidding Counters
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In multiple data cluster systems, existing methods are inefficient in dynamically routing requests to available data clusters, leading to suboptimal use of computing resources and potential data unavailability due to the lack of a systematic approach to identify and utilize clusters with the most available resources.
Innovation Solution
A method and system that utilize cluster bidding counters (CBCs) and data access gateway (DAG) metadata to dynamically identify and route requests to data clusters with the most available resources, ensuring efficient resource utilization and request servicing even if initial clusters become unavailable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a systematic approach using cluster bidding counters and DAG metadata is implemented to dynamically route requests, then request servicing efficiency and resource utilization are improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing cluster bidding counters and DAG metadata structures before request processing. These pre-computed resource availability metrics and access gateway information enable rapid request routing decisions without real-time complex calculations, thus improving productivity while managing complexity through advance preparation.
Solution Approach 2:
The patent introduces intermediary components including cluster bidding counters as mediators between requestors and data clusters. These intermediaries simplify the routing decision process by providing standardized resource availability metrics, reducing the complexity of direct request-cluster matching while improving overall system efficiency.
2Reliability
If dynamic routing to alternative data clusters is implemented, then system reliability is improved, but the complexity of identifying and redirecting requests increases
Solution Approach 1:
The system implements feedback mechanisms through cluster bidding counters that continuously reflect current resource availability status of data clusters. This feedback information is used to dynamically adjust request routing decisions, ensuring reliable data availability while simplifying the complexity through automated, feedback-driven routing rather than manual intervention.
Solution Approach 2:
The patent employs dynamic routing mechanisms that adaptively select data clusters based on real-time resource availability indicated by bidding counters. This dynamic approach improves reliability by automatically switching to available clusters when needed, while the systematic use of pre-defined routing algorithms manages the complexity of dynamic decision-making.
3Productivity
If cluster bidding counters and DAG metadata are used for request routing, then resource utilization efficiency is improved, but computational overhead for obtaining and processing routing information increases
Solution Approach 1:
The system performs preliminary computation of resource availability metrics and stores them in cluster bidding counters and DAG metadata structures. By pre-computing and caching this routing information, the system reduces the computational overhead during actual request processing, improving resource utilization efficiency while minimizing the energy cost of repeated real-time calculations.
Data Source
AI summary
This application includes a method that is performed store data. The method includes obtaining, by a data processor, a first request from a host; and in response to the first request: obtaining first cluster bidding counters (CBCs) from data clusters; identifying a first data cluster of the data clusters to service the request based on the first CBCs and data access gateway (DAG) metadata; sending the first request to the first data cluster; making a first determination that the first data cluster is unable to service the request; and in response to the first determination: identifying a second data cluster of the data clusters to service the request based on the first CBCs and the DAG metadata; and sending the first request to the second data cluster.