Dynamic Retransmission Timeout Bound Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current retransmission mechanisms in network communications, such as those used in TCP and SCTP, face challenges in setting optimal retransmission timers, leading to either unnecessary network congestion or delayed packet retransmission due to fixed and non-adaptive timeout values that do not account for varying network conditions.
Innovation Solution
Dynamic computation of a lower bound for retransmission timeouts based on statistical models of round-trip time sequences, using observed network parameters to adapt coefficients and optimize retransmission timing, thereby minimizing distortion and optimizing network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed retransmission timeout values are used, then network stability is maintained, but retransmission timing cannot adapt to varying network conditions leading to either unnecessary congestion or delayed retransmission
Solution Approach 1:
The patent applies dynamics by making the retransmission timeout value variable rather than fixed. The timeout is dynamically adjusted based on observed round-trip time measurements and statistical model parameters, allowing the system to adapt to changing network conditions while maintaining operational simplicity through automated adjustment.
Solution Approach 2:
The patent changes the parameter of retransmission timeout from a fixed value to a dynamically computed value based on statistical models. By monitoring round-trip times and updating model parameters, the system optimizes the timeout value to match current network conditions, resolving the contradiction between adaptability and complexity.
2Productivity
If retransmission timer is set too short, then lost packets are retransmitted quickly, but unnecessary retransmissions occur causing network congestion
Solution Approach 1:
The patent applies preliminary action by computing statistical model parameters from historical round-trip time data before determining the retransmission timeout. This preparatory modeling allows the system to predict appropriate timeout values that balance quick retransmission with avoidance of unnecessary congestion, rather than reacting to each timeout event independently.
Solution Approach 2:
The system uses feedback from observed round-trip times to continuously refine statistical model parameters and adjust the retransmission timeout accordingly. This closed-loop approach ensures that retransmission timing adapts to actual network conditions, preventing both premature retransmission and excessive delays.
3Stability of the object's composition
If retransmission timer is set too long, then network stability is maintained, but lost packets are not retransmitted timely delaying conversation flow
Solution Approach 1:
The patent makes the retransmission timeout dynamic rather than statically long, allowing it to shorten when network conditions improve. This enables timely retransmission of lost packets when the network can handle it, while maintaining stability through statistically-based adjustments rather than arbitrary changes.
Solution Approach 2:
The system changes the timeout parameter based on statistical analysis of round-trip times. By computing confidence intervals and model parameters from historical data, the system optimizes the timeout value to achieve both stability and timeliness, avoiding the need for excessively conservative fixed values.
4Productivity
If statistical modeling is used to compute retransmission timeout bounds, then retransmission timing is optimized, but computational complexity increases
Solution Approach 1:
The patent applies partial action by using simplified statistical models that capture the essential variability in round-trip times without requiring full-blown complex analysis. The system computes bounds using practical statistical methods that provide sufficient optimization without the overhead of exhaustive computational approaches.
Solution Approach 2:
The system performs self-service by automatically computing and updating statistical model parameters from its own observed round-trip time data. This eliminates the need for external configuration or complex manual tuning, allowing the system to optimize its own retransmission timing with minimal additional complexity.
Data Source
AI summary
A method includes estimating a parametric model for a round-trip time sequence for an electronic transmission over a network. Optimization calculations may be performed to dynamically determine a bound (for example, a lower bound) on re-transmission timeout for an electronic transmission to be conducted over the network.