Intelligent Resource Allocator for Computing Load Synchronization
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Solution Overview
Problem
Current computing networks face inefficiencies in synchronizing users and timing data across complex systems, particularly in wireless, satellite, and wire-based networks, leading to delays and inefficiencies in data exchange.
Innovation Solution
The implementation of an intelligent synchronization method that utilizes a network system with a processor, memory, and communication center to manage and allocate computing resources dynamically based on user interactions and geolocation, enabling efficient data exchange across diverse computing devices and networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional synchronization methods are used in complex computing networks, then system compatibility is maintained, but synchronization speed and efficiency deteriorate
Solution Approach 1:
The system segments the complex computing network into multiple computing environments (first computing environment and second computing environment) with separate processors (first processor and second processor). Each processor independently manages synchronization for its respective environment, dividing the complex synchronization task into manageable segments that can operate in parallel, thereby improving synchronization speed without requiring the entire complex network to coordinate simultaneously.
2Productivity
If dynamic resource allocation based on computing load is implemented, then resource utilization efficiency is improved, but system complexity increases
Solution Approach 1:
The system dynamically allocates computing resources between the first and second computing environments based on real-time computing load conditions. The processors monitor resource utilization metrics and automatically adjust resource distribution, enabling the system to adapt to changing workloads. This dynamic approach improves resource utilization efficiency by directing resources to the environment with higher demand while the resource management complexity is handled through automated algorithms rather than manual configuration.
Data Source
AI summary
This disclosure is directed to intelligent synchronization of computing users, and associated timing data, based on parameters or data received from computing systems connected via wireless, satellite, wire-based, optical-fiber based, etc., computing networks.