Sampled Multicast Error Recovery for Congestion-Limited Networks
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Solution Overview
Problem
Multicast error recovery in communication systems faces challenges due to network congestion and latency caused by a high volume of retransmission requests when errors affect a large number of receiving devices, particularly in networks with shared transmission media, leading to unreliable delivery of video and other media content.
Innovation Solution
A method that sets a probability value in the multicast data stream, allowing only a selected subset of receivers to report errors, thereby reducing the number of retransmission requests through partial sampling, which avoids network congestion and enables effective recovery from errors affecting multiple receiving stations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all receiving devices report errors in the multicast data stream, then error detection coverage is improved, but network congestion and latency increase
Solution Approach 1:
The patent applies partial action by having only a subset of receiving devices report errors instead of all devices. Each receiver independently determines whether to report an error based on a probability value, creating a sampled feedback mechanism that provides sufficient error detection coverage while limiting the number of error reports to avoid network congestion.
2Reliability
If a high volume of retransmission requests are sent, then error recovery completeness is improved, but network latency increases
Solution Approach 1:
The system uses partial action by having only some receivers report errors through probabilistic sampling. This reduces the total number of retransmission requests sent over the network, thereby reducing latency while still maintaining adequate error recovery through the sampled feedback from representative receivers.
Solution Approach 2:
The patent implements a feedback mechanism where receiving devices send error reports back to the transmitter based on a probability value. This sampled feedback provides the transmitter with information about errors without overwhelming the network with feedback from every receiver, balancing error recovery effectiveness with network performance.
3Productivity
If error reports are limited to a subset of receivers, then network congestion is reduced, but error detection accuracy may decrease
Solution Approach 1:
The system uses probabilistic feedback where each receiver independently decides whether to report an error based on a probability value. This creates a statistically representative sample of error conditions across the network, providing sufficient detection accuracy while limiting the volume of feedback traffic to maintain network throughput.
Solution Approach 2:
The patent changes the parameter of error reporting from deterministic (all or none) to probabilistic. By introducing a probability value that controls the likelihood of each receiver reporting an error, the system can adjust the balance between detection accuracy and network load dynamically, achieving both goals under appropriate conditions.
Data Source
AI summary
A method is provided in one example and includes receiving a data stream that includes an error code probability; detecting an error in the data stream; and determining whether to generate an error signal for the error in the data stream based on the error code probability being compared to a threshold value. In more particular embodiments, the error code probability may be based on a total number of network elements that receive the data stream. In addition, more specific methodologies may include generating a number to be used as a basis for the threshold value; and generating the error signal if the error code probability is below the threshold value.