Computing Clusters for Network Connectivity Trust Ratings
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Solution Overview
Problem
Quantifying and utilizing network connectivity within and between communities to determine trustworthiness or competence of individuals or entities is challenging due to varying credibility and scale of information, duplicate entries, and rapid connection changes, complicating real-world decision-making.
Innovation Solution
Systems and methods using graph traversal and normalization techniques, including path counting and weighted links, to determine connectivity ratings, with parallel computational frameworks for distributed processing, and decision-making algorithms for trust-based transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If network connectivity information is collected from multiple community members to determine trustworthiness, then the quantity and diversity of information increases, but the complexity of processing and comparing varying credibility and scale information increases
Solution Approach 1:
The patent transforms qualitative connectivity information into quantitative metrics by assigning numerical weights to different types of connections and credibility levels. This parameter transformation enables mathematical comparison and aggregation of diverse information sources, resolving the complexity of processing varying credibility and scale information.
Solution Approach 2:
The system introduces intermediary computational layers including graph traversal algorithms, normalization processes, and aggregation functions that mediate between raw connectivity data and final trust scores. These intermediaries standardize and harmonize diverse information sources before comparison.
2Measurement precision
If graph traversal and normalization techniques are used to determine connectivity ratings, then the precision of trust measurement improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent segments the computational process into distinct phases: graph traversal to identify connections, normalization to standardize metrics, aggregation to combine results, and ranking to produce final scores. This segmentation allows each phase to be optimized independently and facilitates parallel processing.
Solution Approach 2:
The system implements configurable depth limits and sampling strategies in graph traversal to achieve sufficient measurement precision without exhaustive computation. By performing partial exploration of the network graph, the system obtains adequate trust measurements while reducing computational complexity.
3Ease of operation
If duplicate entries and outdated information are not addressed, then the ease of data collection is maintained, but the accuracy of connectivity representation deteriorates
Solution Approach 1:
The system implements feedback mechanisms that continuously monitor and update connectivity information. By comparing new data against existing records and detecting duplicates through consistency checks, the system automatically identifies and corrects outdated or redundant information while maintaining ease of data collection.
Solution Approach 2:
The patent applies preliminary filtering and deduplication processes during data ingestion before full processing occurs. This preliminary action removes obvious duplicates and validates data format early in the pipeline, preventing accumulation of erroneous information while maintaining operational simplicity.
4Reliability
If connectivity information is updated in real-time to reflect rapid connection changes, then the currency of information improves, but the processing speed and system responsiveness may deteriorate
Solution Approach 1:
The system implements periodic updates at strategically determined intervals rather than continuous real-time processing. By updating connectivity information periodically based on change detection thresholds and priority levels, the system maintains adequate currency of information while preserving processing speed and system responsiveness.
Solution Approach 2:
The patent employs dynamic update strategies that adjust processing frequency based on network activity levels, user priorities, and resource availability. High-priority connections receive more frequent updates while low-priority connections are updated less frequently, optimizing the balance between information currency and processing speed.
Data Source
AI summary
A system is provided wherein a processor in a distributed network system determines a network connectivity value associated with a computer in a network. The connectivity value is determined as a function of an aggregation of path scores of paths between the computer and a mobile device and also as a function of at least one of the path scores. Determining the connectivity value may be accomplished by distributing the tasks to distributed processors within one or more of a plurality of clusters of processors. The processors perform their respective computing task before reporting results. A virtual marker system for use within the network may be provided. Markers in the marker system may be provided based on network connectivity value.