Social Graph Construction from File Metadata for Distributed Problem Resolution
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Solution Overview
Problem
Modern computing systems face challenges in identifying and resolving problems due to their complexity, especially when users and system elements are geographically dispersed, making it difficult to determine the cause and implement solutions effectively.
Innovation Solution
A data analysis method using a commonality engine to determine the relative connection strength between users by analyzing shared data, which can help identify problems, their causes, and potential solutions, and facilitate preventive actions without requiring user cooperation or additional effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users are geographically dispersed across different locations, then the computing system can support global collaboration and accessibility, but it becomes difficult to identify problems, their causes, and potential solutions
Solution Approach 1:
The patent introduces a social graph as an intermediary data structure that mediates between geographically dispersed users and the central computing system. The social graph captures relationship information (colleagues, managers, teammates) that remains consistent across locations, enabling the system to identify relevant users for problem-solving regardless of geographical distribution. This intermediary structure allows the system to maintain collaboration capabilities while overcoming the difficulty of problem identification in distributed environments.
2Measurement precision
If a significant amount of time and effort is spent attempting to identify causes and solutions, then more thorough analysis can be performed, but productivity and response time are reduced
Solution Approach 1:
The patent performs preliminary action by pre-establishing the social graph structure that encodes user relationships and collaboration patterns before problems occur. This social graph is built in advance using metadata from collaboration platforms, so when a problem arises, the system can immediately query the pre-built structure to identify relevant users and potential solutions, eliminating the need for time-consuming analysis during incident response while maintaining thoroughness.
3Reliability
If the computing system includes geographically dispersed elements such as servers, then system availability and redundancy are improved, but it becomes difficult to identify and implement problem solutions
Solution Approach 1:
The patent applies universality by creating a unified social graph structure that serves multiple functions across geographically dispersed system elements. The same social graph data structure and query mechanisms are used whether the problem involves users, servers, or other system components, providing a universal approach to problem identification and solution implementation that simplifies the complexity of managing distributed system elements.
Data Source
AI summary
One example method includes identifying, in a computing system, an aggregate data set that includes both data used by a first user and data used by a second user, examining file metadata associated with the data in the aggregate data set and, based on the examination of the file metadata, determining whether or not any data in the aggregate data set is shared by the first and second users. When a determination is made that some data in the data set is shared by the first and second users, the method includes further determining how much of the data is shared, assigning a strength of connection between the first user and the second user based on the extent to which the first user and second user share data and, based on the strength of connection, taking an action to improve operation and/or configuration of the computing system.