Distributed Network Infrastructure Nodes for Real-Time Data Processing
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Solution Overview
Problem
Conventional cloud computing systems face latency and data overload issues due to centralized data processing, limiting real-time data sharing and processing across industries, which hampers the delivery of ultra-intelligence and ultra-realistic services like self-driving and augmented/virtual reality.
Innovation Solution
A network infrastructure system with multiple nodes providing data transfer, distribution, processing, and sharing functions, allowing dynamic data processing and software execution at optimized locations within the network, enabling real-time data sharing and processing across domains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If data is processed in a centralized cloud computing system, then data processing capability is improved, but data transmission latency increases
Solution Approach 1:
The patent segments the centralized cloud computing system into multiple distributed network infrastructure nodes. Each node independently processes data locally, eliminating the need for long-distance data transmission to a central cloud. This segmentation maintains processing capability while reducing transmission latency by enabling parallel processing across multiple nodes.
Solution Approach 2:
The patent transitions from a single-dimensional centralized processing model to a multi-dimensional distributed network architecture. Data can be processed at multiple levels (edge devices, local nodes, regional nodes, central cloud), adding spatial and hierarchical dimensions to the processing architecture, thereby reducing latency while maintaining capability.
2Power
If data is processed in a centralized cloud computing system, then data processing capability is improved, but data overload occurs
Solution Approach 1:
The patent divides the data processing load across multiple distributed nodes instead of concentrating all data in a single centralized cloud. Each node handles a portion of the data locally, preventing data overload at any single point while maintaining aggregate processing capability through parallel processing across the network.
Solution Approach 2:
The patent introduces network infrastructure nodes as intermediaries between edge devices and the central cloud. These intermediary nodes filter, process, and aggregate data locally before transmitting to the cloud, reducing the volume of data that reaches the central system and preventing data overload.
3Measurement precision
If data is processed in a centralized cloud computing system, then data analysis capability is improved, but real-time data sharing across industries becomes difficult
Solution Approach 1:
The patent creates a universal network infrastructure that can serve multiple industries and applications simultaneously. The distributed nodes provide multi-functional capabilities, handling data processing, storage, sharing, and analysis across different industrial domains in real-time, replacing the single-purpose centralized cloud model.
Solution Approach 2:
The patent implements real-time feedback mechanisms where distributed nodes continuously exchange data and processing results across the network. This enables real-time data sharing and collaborative analysis across industries, with each node receiving feedback from others to improve local processing decisions while maintaining overall system analysis capability.
4Loss of time
If fog computing is used to reduce data transmission latency, then latency is reduced, but network efficiency and resource management become limited
Solution Approach 1:
The patent implements dynamic resource allocation and management across the distributed network nodes. Unlike static fog computing architectures, the system dynamically adjusts processing loads, data routing, and resource distribution based on real-time network conditions, application requirements, and node availability, thereby improving network efficiency while maintaining low latency.
Solution Approach 2:
The patent enables distributed nodes to autonomously manage their own resources and processing loads without requiring centralized control. Each node independently optimizes its operations, manages local data caching, and makes real-time decisions about data processing and sharing, improving overall network efficiency through decentralized self-service capabilities.
Data Source
AI summary
A network infrastructure system implements data sharing and processing by using a network infrastructure to which an application terminal or application server constituting an application domain is connected in a shared manner, includes a plurality of network infrastructure nodes storing, processing, sharing data, wherein each of the plurality of network infrastructure nodes includes a data processing module including a data transfer function, a data distribution function, a data processing function, and a data sharing function which are provided to at least one of the application terminal and the application server.