Execution File Assignment for Distributed Processing Overhead
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Solution Overview
Problem
Conventional data processing systems experience overhead during distributed processing, leading to reduced processing speed and difficulty in real-time device operation and information display in device cooperation systems, especially when the number of connected devices is small or when low-performance CPUs are used.
Innovation Solution
Assigning execution responsibilities for execution files in an application to specific information processing devices before execution, allowing each device to execute only its assigned files, thereby reducing overhead and ensuring efficient distributed processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed processing is executed by a plurality of CPUs under unified management by a main CPU, then processing can be divided and assigned to respective CPUs, but processing becomes concentrated in the main CPU and delay of processing generates overhead
Solution Approach 1:
The invention segments the processing system by allowing each CPU to independently manage its assigned processing tasks without requiring centralized coordination for every operation. The main CPU divides processing into independent units and assigns them to slave CPUs, which then execute autonomously, eliminating the bottleneck of centralized management and reducing processing delays.
Solution Approach 2:
The invention applies preliminary action by pre-dividing processing tasks into independent units before execution and pre-assigning them to specific CPUs. This preparation eliminates the need for real-time coordination during task execution, reducing overhead and processing delays while maintaining high productivity through parallel processing.
2Productivity
If script codes are sequentially interpreted to distribute processing during application execution, then processing can be separated into units and assigned to devices, but overhead of interpretation and distribution processing reduces system processing speed
Solution Approach 1:
The invention eliminates sequential interpretation overhead by pre-compiling script codes into executable files before application execution. The processing distribution structure is also predetermined and prepared in advance. This preliminary preparation allows CPUs to directly execute compiled code without interpretation overhead during runtime, significantly improving processing speed while maintaining the ability to distribute processing across multiple devices.
3Device complexity
If the number of connected devices is small, then the system is simpler to manage, but the amount of processing to be executed by each device becomes larger and a heavy load is applied to the CPU
Solution Approach 1:
The invention applies segmentation by automatically dividing processing tasks into smaller units and distributing them across available devices, regardless of the total number of devices. Each device executes only its assigned segment, reducing the processing burden on individual CPUs while maintaining simple system management through automated task distribution rather than requiring complex manual configuration.
Data Source
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AI summary
An information processing device provided with: an application division setting part (132) for assigning execution responsibility for each of a plurality of execution files included in an application to one of a plurality of information processing devices, and for generating execution responsibility assignment information indicating each of the execution files and an information processing device to which the execution responsibility for the execution file is assigned; a communication part (140) for transmitting the execution responsibility assignment information to a network; and an application division execution part (133) for referring to the execution responsibility assignment information to execute an execution file whose execution responsibility is assigned to its own device out of the plurality of execution files.