Hybrid Data Control Processing Architecture for Latency
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Solution Overview
Problem
Existing data processing systems for video distribution, particularly in wireless environments, face challenges in optimizing resource usage and controlling latency while handling diverse data processing tasks with varying performance constraints and transmission protocols, lacking a versatile architecture to support both application and transmission requirements effectively.
Innovation Solution
A data processing system with a configurable architecture comprising multiple data processing hardware units, each with predetermined latency capabilities, and a controller that determines the type of task and selects the appropriate unit based on latency constraints, source, and destination, enabling flexible task execution and resource optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a data-flow based computational model is used, then intensive data processing requirements are met, but control requirements and dynamic task scheduling are insufficient
Solution Approach 1:
The patent merges data-flow processing and control-flow processing into a single hybrid architecture. Data-flow processing elements handle intensive data processing tasks while control-flow processing elements manage dynamic task scheduling and control requirements, allowing both paradigms to coexist and coordinate within the same system.
Solution Approach 2:
The hybrid processing platform is designed to be universal, supporting both data-flow and control-flow computational models. The system can dynamically allocate resources to handle different types of processing requirements, making it adaptable to various application scenarios including video distribution, wireless communication, and real-time data processing.
2Adaptability or versatility
If a control-flow based computational model is used, then dynamic task scheduling is achieved, but intensive data processing capability is reduced
Solution Approach 1:
The processing platform is segmented into distinct data-flow processing elements and control-flow processing elements. This segmentation allows each type of element to specialize in its respective strength while the overall system benefits from the combination. Data-flow elements focus on high-speed data processing while control-flow elements handle scheduling and control logic.
3Reliability
If multiple specific implementations are created for different contexts, then performance constraints are optimized, but device complexity and resource optimization are worsened
Solution Approach 1:
Instead of creating multiple specific implementations, the patent creates a single universal hybrid processing platform that can adapt to different performance constraints through dynamic resource allocation and configuration. The platform maintains reliability across different contexts by intelligently selecting and coordinating appropriate processing elements based on the specific requirements of each task.
Data Source
AI summary
A data processing system comprising a plurality of data inputs and of data outputs for processing input data and providing processed data to a data output. The system comprises a plurality of data processing hardware units, each being configured to process data within a predetermined latency and according to a data processing task of a predetermined type. The system further comprises a memory for storing a predetermined latency for each of the data processing hardware units and a controller configured to determine a type of a data processing task to be executed as a function of a source of data to be processed or of a destination of processed data and further configured to select one data processing hardware unit as a function of the determined type of the task to be executed and of latency constraints associated with the task to be executed.