Hash-Based Data Distribution for Channel Load Balancing

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Solution Overview

Problem

In computer systems with multiple components, high volumes of data transmission lead to performance bottlenecks due to uneven resource usage across communication channels, particularly in industries like financial services where certain data types dominate, causing CPU resource imbalances.

Innovation Solution

A method using a predictable hash function, such as the Symbol Randomization utility, to consistently route data of specific types over the same communication channels, ensuring even distribution and efficient resource utilization by converting symbol names into hash numbers and applying a modulo operation to determine channel assignment.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If data is transmitted over multiple communication channels without distribution, then data transmission capacity is increased, but resource usage becomes uneven causing performance bottlenecks

Engineering Contradiction:

Improvedata transmission capacityVSAvoidperformance consistency

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent segments data transmission by dividing data into different types (e.g., market data, order data, execution data) and routing each type through dedicated communication channels. This segmentation ensures that high-volume data types do not monopolize channel resources, distributing the load evenly across multiple channels while maintaining overall transmission capacity.

Inventive Principle:

Principle #1Segmentation

2Adaptability or versatility

If certain data types dominate communication channels, then specific data transmission requirements are met, but CPU resources become imbalanced across channels

Engineering Contradiction:

Improvedata type handlingVSAvoidCPU resource usage

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The patent applies local quality by assigning different communication channel characteristics to different data types. Each channel is optimized for specific data types based on their transmission requirements, ensuring that dominant data types do not overload single channels. This local optimization balances CPU resource usage across channels while maintaining adaptability to various data type requirements.

Inventive Principle:

Principle #3Local quality

3Productivity

If data routing is dynamic to balance load, then resource utilization improves, but routing predictability decreases

Engineering Contradiction:

Improveresource utilizationVSAvoidrouting consistency

Core Design Contradiction:

ProductivityVSStability of the object's composition

Solution Approach 1:

The patent implements preliminary action by pre-establishing routing rules that map data types to specific communication channels based on historical analysis of data patterns. This pre-planned routing configuration ensures predictable resource utilization without requiring dynamic load balancing decisions during data transmission, maintaining both productivity and routing stability.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS7725622B2Data distribution system and method

Publication Date: 2010.05.25 EZE CASTLE SOFTWARE LLC

AI summary

The transmission of data is distributed evenly and predictably over a given number of communication channels using a hash function.