Dynamic Swarm Segmentation for Peer Matching
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Solution Overview
Problem
In peer-to-peer computing systems, the inefficiency arises from peers having non-overlapping byte ranges for software updates, leading to ineffective content sharing due to lack of overlapping data, which hampers the effectiveness of the network in distributing updates efficiently.
Innovation Solution
A system utilizing a graph representation of datasets to identify and match clients based on their required byte ranges, allowing for efficient peer matching by grouping clients with similar update needs and traversing the graph to find suitable peers, even if ideal matches are not available within the same group.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If peers are matched based on having any content overlap, then peer-to-peer content sharing can occur, but the matching efficiency is low and many peers become ineffective when byte ranges do not overlap
Solution Approach 1:
The patent segments the content into distinct byte ranges and organizes them in a hierarchical graph structure. Each node in the graph represents a specific byte range, allowing the system to break down the complex peer matching problem into smaller, manageable segments. This enables efficient identification of overlapping byte ranges between peers without requiring complex global analysis.
Solution Approach 2:
The patent introduces a hierarchical dimension to the peer matching process by organizing byte ranges in a graph structure with multiple levels. Instead of performing flat, two-dimensional peer comparisons, the system traverses the hierarchical graph to find matches, adding a dimensional aspect that simplifies the matching logic and improves efficiency.
2Reliability
If the entire dataset is distributed to all peers, then all peers can have complete content, but the data transfer volume and network load increase significantly
Solution Approach 1:
The patent extracts and identifies only the specific byte ranges that each peer needs, rather than distributing the entire dataset. By using the hierarchical graph to determine exact content requirements, the system extracts only the necessary portions of data for transfer, significantly reducing network bandwidth consumption while ensuring each peer receives complete content.
Solution Approach 2:
The patent applies local quality by tailoring the data distribution to each peer's specific needs. Instead of uniform distribution of all data to all peers, the system determines the local requirements of each peer and provides only those specific byte ranges, optimizing network efficiency while maintaining content completeness for each individual peer.
3Productivity
If peers trade all their content with each other, then content sharing is maximized, but the time required for content exchange increases due to unnecessary data transfer
Solution Approach 1:
The patent performs preliminary action by pre-organizing the content structure into a hierarchical graph of byte ranges before peer matching occurs. This pre-structured organization allows the system to quickly identify which byte ranges need to be exchanged, eliminating the need for time-consuming trial-and-error content sharing and enabling peers to exchange only the necessary data immediately.
Solution Approach 2:
The patent introduces dynamics by enabling flexible, adaptive peer matching based on real-time content requirements. The hierarchical graph structure allows the system to dynamically determine the optimal peer pairs and byte range exchanges, adapting to different peer configurations and content needs rather than following a fixed, static distribution pattern.
Data Source
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AI summary
Identifying peers to a client for the client to obtain data. A method includes receiving from the client an identification of a dataset and a specification of one or more byte ranges of the dataset. As a result, the method further includes identifying one or more other clients associated with the one or more byte ranges of the dataset to acts as peers to the client. The method further includes providing an indication of the one or more of the other identified clients as peers to the client.