Overlay Network Management for Edge Data Processing
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Solution Overview
Problem
Existing solutions for managing application overlay networks face challenges in providing real-time data access and processing for IoT devices and edge applications, particularly due to bandwidth limitations, data sovereignty concerns, and the infeasibility of moving large volumes of data to centralized cloud networks.
Innovation Solution
Implementing a platform with heavy nodes equipped with low-power, large-memory devices to create and manage overlay networks that enable local data storage, processing, and analysis, allowing for dynamic and controlled information exchanges among devices and application components, with policies governing access and participation, and facilitating communication between edge devices and cloud networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is moved to centralized cloud networks for processing and storage, then data management and analysis capabilities are improved, but bandwidth consumption increases and latency increases making real-time processing infeasible
Solution Approach 1:
The patent segments the centralized cloud network into distributed overlay networks consisting of multiple edge nodes. Each node independently processes and stores data locally, eliminating the need to move all data to a central location. This segmentation enables real-time processing at the edge while maintaining data management capabilities through distributed coordination.
Solution Approach 2:
The patent introduces a new dimensional approach by creating virtual overlay networks that operate alongside the physical network infrastructure. These overlay networks provide an additional layer of abstraction that enables flexible data routing, local processing, and distributed storage without being constrained by the traditional centralized cloud architecture.
2Reliability
If large volumes of data are transmitted to centralized networks, then comprehensive data analysis is improved, but bandwidth limitations and transmission costs increase
Solution Approach 1:
The patent extracts data processing and storage functions from the centralized cloud network and places them at the edge nodes. This extraction allows data to be processed and analyzed locally where it is generated, eliminating the need to transmit large volumes of data across the network while maintaining comprehensive analysis capabilities through distributed processing.
Solution Approach 2:
The patent implements partial data transmission where only necessary data is sent to other nodes or the cloud, rather than transmitting all data. Each node performs local processing and filtering, sending only relevant information across the network, thereby reducing bandwidth consumption while maintaining data analysis capability.
3Speed
If overlay networks are implemented with multiple nodes for distributed processing, then real-time data access is improved, but network complexity and coordination overhead increase
Solution Approach 1:
The patent implements universal node designs where each overlay network node can perform multiple functions including data storage, processing, routing, and coordination. This multi-functionality reduces the need for specialized components and simplifies network management while enabling fast data access through distributed capabilities at each node.
Data Source
AI summary
Overlay networks of application components are managed. Applicant components may create overlay networks based on policies of the application components and an environment of the overlay network. The overlay network may be adjusted based on changes to the policies or the environment.