Dynamic Data Burst Assembly via Traffic Monitoring
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Solution Overview
Problem
Conventional data burst assembly mechanisms, such as PHTT and BSML, fail to maximize data burst usability due to inefficiencies in data transfer, leading to increased collisions and reduced efficiency, especially when data traffic conditions are dynamic.
Innovation Solution
A data burst assembly apparatus and method that dynamically generates and processes data bursts by monitoring network traffic conditions, adjusting generation parameters such as period and size based on real-time data traffic, and using a mapping table to optimize parameter settings for improved data burst utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If PHTT mechanism is used to generate data bursts after a fixed period, then the structure is simplified and operation time is constant, but data burst usability is drastically degraded due to transfer of dummy data and successive collisions
Solution Approach 1:
The patent applies dynamics by making the data burst generation parameters (period and size) variable rather than fixed. The data burst generator dynamically adjusts the generation period and size based on monitored network traffic conditions, allowing the system to adapt to changing data traffic patterns while maintaining a relatively simple overall structure.
Solution Approach 2:
The patent changes the parameters of data burst generation by introducing a mapping table that stores multiple generation parameter sets corresponding to different network traffic conditions. The system selects appropriate parameters (period and size) based on current traffic conditions, thereby improving data burst usability without significantly increasing structural complexity.
2Productivity
If BSML mechanism is used to generate data bursts when received data reaches a certain size, then data burst efficiency is increased, but packets below threshold are continuously stored and not output
Solution Approach 1:
The patent makes the data burst generation size dynamic by allowing it to vary based on network traffic conditions. Instead of using a fixed threshold size, the system adjusts the generation size parameter according to current traffic patterns, enabling timely output of data bursts even when packet sizes are below the traditional threshold.
Solution Approach 2:
The patent changes the generation size parameter by storing multiple size values in a mapping table corresponding to different network traffic conditions. This allows the system to select appropriate generation sizes dynamically, preventing continuous storage of packets below a fixed threshold while maintaining efficient data burst generation.
3Adaptability or versatility
If hybrid mechanism of PHTT and BSML is used, then both mechanisms are combined, but data burst utilization decreases and successive collisions increase when data amount is insignificant or high
Solution Approach 1:
The patent improves upon the hybrid mechanism by introducing a mapping table that stores optimized generation parameter sets for different network traffic conditions. Instead of simply combining PHTT and BSML mechanisms, the system dynamically selects and adjusts parameters (period and size) based on monitored traffic conditions, thereby improving data burst utilization and reducing successive collisions.
Solution Approach 2:
The patent implements feedback by continuously monitoring network traffic conditions and using this information to dynamically adjust data burst generation parameters. The monitor component tracks traffic patterns and feeds this information back to the data burst generator, which then selects appropriate parameters from the mapping table, creating a closed-loop system that adapts to changing conditions.
Data Source
AI summary
A data burst assembly apparatus includes a receiver to receive a packet from at least one source; a monitor to monitor a data traffic condition of a network; and a data burst generator to dynamically determine a value of a generation parameter for generating a data burst with respect to the packet received at the receiver according to the data traffic condition of the network, and to generate the data burst using the generation parameter value. A storage unit may be further included to store a mapping table defining generation parameter values mapped based on data traffic conditions. A data burst generator can read a generation parameter value mapped to a monitoring result from a mapping table and generate a corresponding data burst.