Network Transmission Rate Optimization via Gambler Strategy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Data loss occurs in networks due to inherent lossy nature or congestion, where network utilization exceeds capacity, causing packets to be dropped, and existing methods are not responsive enough to adjust transmission rates effectively.
Innovation Solution
A system and method that differentiate between data loss caused by network characteristics and congestion by using loss probe packets and a gambler strategy, where multiple transmitters operate at different rates, and the one with the lowest loss rate is optimized, allowing for incremental adjustment of transmission rates to maximize throughput without causing congestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If transmission rate is increased to maximize throughput, then productivity is improved, but data loss increases due to network congestion
Solution Approach 1:
The system dynamically adjusts transmission rates based on real-time network conditions. Multiple transmitters operate at different transmission rates that are continuously adapted according to observed data loss patterns, allowing the system to maximize throughput while avoiding congestion-induced packet drops.
Solution Approach 2:
The invention changes the transmission rate parameter of data packets based on observed loss rates. By monitoring data loss at different transmission rates and identifying the inherent network loss rate, the system adjusts the transmission rate parameter to operate optimally below the congestion threshold.
2Reliability
If transmission rate is decreased to minimize data loss, then reliability is improved, but productivity decreases
Solution Approach 1:
Rather than using a static low transmission rate, the system dynamically determines the optimal transmission rate by testing multiple rates and observing data loss patterns. This allows the system to maintain high reliability while achieving maximum possible throughput for the given network conditions.
Solution Approach 2:
The system implements feedback mechanisms where data loss information is collected and used to adjust transmission rates. By monitoring whether data loss exceeds the inherent network loss rate, the system receives feedback that guides transmission rate adjustments to maintain reliability while maximizing productivity.
3Adaptability or versatility
If multiple transmitters operate at different rates, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system segments the transmission function into multiple independent transmitters, each operating at a different transmission rate. This segmentation allows the system to test and adapt to different network conditions simultaneously, improving adaptability while keeping individual transmitter complexity low.
Solution Approach 2:
Each transmitter independently determines its optimal transmission rate by observing data loss patterns specific to its transmission rate. The system self-adjusts without requiring complex centralized control, as each transmitter serves itself by monitoring its own performance and adapting accordingly.
Data Source
AI summary
Disclosed are systems and methods for an optimal transmission rate for large quantities of data over a network using gambler strategies. The gambler strategies can include initiating a gambler of a generation including a plurality of gamblers and transmitting one or more packets for the gambler over a network at a transmission rate specified by the gambler. In response to a determination the gambler is finished the network to discharge. In response to a determination the generation is finished, determining a gain-loss of the generation and the plurality of gamblers can be adjusted to be inline with an inherent network data loss rate.