Consolidated Service Indicators for Distributed Data Communication
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Solution Overview
Problem
In large distributed computer systems, client terminals often struggle to efficiently communicate with multiple data sources, leading to suboptimal utilization of resources due to mismatched availability and demand for services.
Innovation Solution
A method and device that compute a consolidated indicator by aggregating key-value pairs from multiple data sources across a wide-area network, allowing client terminals to adjust their data communications based on the overall availability or demand for services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If client terminals communicate with multiple data sources independently, then each terminal can access data from various sources, but the system experiences suboptimal resource utilization due to mismatched availability and demand
Solution Approach 1:
The patent introduces an intermediary component that consolidates availability information from multiple data sources and communicates demand information back to client terminals. This intermediary acts as a mediator that matches supply and demand across the distributed system, resolving the contradiction between independent access and coordinated resource utilization.
Solution Approach 2:
The system implements feedback loops where availability data from data sources is collected, consolidated, and used to generate demand recommendations that are fed back to client terminals. This feedback mechanism enables dynamic adjustment of communication patterns to optimize resource utilization while maintaining service availability matching.
2Ease of operation
If client terminals continuously monitor all data sources for availability, then they can make informed communication decisions, but the system complexity and communication overhead increase significantly
Solution Approach 1:
The patent merges the monitoring and consolidation functions into a centralized or semi-centralized component that aggregates availability information from multiple data sources. This consolidation approach simplifies the architecture by eliminating the need for each client terminal to independently monitor all data sources, reducing system complexity while maintaining informed decision-making capabilities.
Solution Approach 2:
The intermediary component serves multiple functions: it consolidates availability data from various data sources, processes this information, generates demand recommendations, and communicates with client terminals. This multi-functional design reduces overall system complexity by consolidating multiple specialized components into a single universal intermediary.
Data Source
AI summary
Data includes key-value pairs that include numerical keys and numerical values. Each key represents a level of service associated with a data source and client terminals. The respective value represents availability or demand for the level of service. Data from different data sources is consolidated into consolidated data by summing values for each key. A consolidated indicator is determined for the consolidated data by computing an average key and an aggregate duration of keys of the consolidated data. The consolidated indicator is outputted for access to the client terminals via a wide-area computer network to allow the client terminals to use the consolidated indicator to configure respective data communications with different data sources.