P2P Live Stream Data Frame Relationship Sequence
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Solution Overview
Problem
Current P2P-based live stream pull methods are complex and have poor disaster recovery capabilities, relying on a central node for sequence marking and lacking efficient multi-path data restoration.
Innovation Solution
A data transmission method that generates a current relationship sequence for each data frame based on its frame identifier and historical frame identifiers, allowing frame data to be transmitted without relying on a central node for sequence marking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a central node is used for sequence marking in P2P-based live stream pull, then data transmission control is achieved, but system complexity increases and disaster recovery capability deteriorates
Solution Approach 1:
The patent extracts the sequence marking function from the central node and embeds it directly into each data frame through relationship sequences. Each frame carries its own positioning information (relationship sequence) that indicates its position in the data stream, eliminating the need for centralized sequence management and enabling independent disaster recovery at each node.
Solution Approach 2:
Each data frame becomes self-sufficient by carrying its own relationship sequence information that enables it to be positioned and reconstructed without external assistance. The frame includes identifiers and sequence information that allow receiving nodes to independently reconstruct the data stream even when disconnected from the central node.
2Adaptability or versatility
If uniform slicing through a central node is performed, then data stream management is simplified, but multi-path data restoration capability is reduced
Solution Approach 1:
The data stream is divided into multiple independent data frames, each containing complete relationship sequence information. This segmentation allows any subset of frames to be independently received, transmitted through different paths, and reconstructed at the destination, enabling multi-path restoration without requiring centralized management.
Solution Approach 2:
The patent adds a new dimension of information (relationship sequence) to each data frame that encodes positional and contextual information. This transforms the data structure from a simple sequential stream into a multi-dimensional framework where frames can be reordered and reconstructed from any path, enhancing adaptability without increasing management complexity.
Data Source
AI summary
Embodiments of the present disclosure provide a data transmission method, a data processing method, apparatuses, a device, and a storage medium. The data transmission method includes: acquiring a current frame identifier of a current data frame in a target data stream, where the current data frame is a data frame that is currently to be sent; generating a current relationship sequence of the current data frame according to the current frame identifier and a historical frame identifier of at least one historical data frame, where the current data frame and the at least one historical data frame are data frames continuously arranged in the target data stream, and the current relationship sequence is used to indicate a current arrangement sequence of the current data frame in the target data stream; and transmitting frame data of the current data frame and the current relationship sequence to a receiving end.