Dynamic Edge Computing Deployment Using Idle Network Devices
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Solution Overview
Problem
Cloud computing systems face issues with increased load due to the growing number of IoT devices, security and privacy concerns, and service disruptions from errors or lack of internet connectivity, while conventional edge computing services are limited to fixed devices and may not be available based on the state of edge devices.
Innovation Solution
An edge computing system and method that utilizes devices with idle computing power in a network, dynamically configuring them as edge devices to perform edge computing services by installing modules based on device registration and connection testing, enabling flexible deployment and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cloud computing is used to process data from IoT devices, then computing service is provided, but system load increases and security/privacy issues occur
Solution Approach 1:
The patent segments the centralized cloud computing architecture into distributed edge computing nodes. Each edge device (electronic device 301) processes data locally or near the data source, dividing the computing workload across multiple distributed units rather than concentrating it in a single cloud system. This segmentation reduces system load on centralized servers and improves security by keeping sensitive data processing localized.
Solution Approach 2:
The patent introduces a new dimensional approach by enabling any device in the network to become an edge computing device dynamically. Instead of fixed hierarchical layers, the system allows devices to participate in edge computing based on their available resources and network position, creating a multi-dimensional computing architecture that flexibly utilizes available computing power across the network.
2Adaptability or versatility
If conventional edge computing service is provided via fixed module to fixed edge device, then edge computing is implemented, but service availability is limited based on edge device state
Solution Approach 1:
The patent implements dynamic edge computing where devices can transition between different roles (leaf device, edge device) based on their current state and available resources. The system continuously evaluates device availability, computing power, and network conditions to dynamically allocate edge computing services, ensuring service continuity even when individual devices become unavailable or their state changes.
Solution Approach 2:
The patent makes edge computing services universal by enabling any device in the network to potentially serve as an edge device. The system doesn't rely on fixed dedicated edge devices but allows multiple devices to perform edge computing functions based on their capabilities and current state, increasing service availability through redundant capable devices.
3Reliability
If resources for edge computing are required to be secured, then edge computing service is provided, but device complexity increases
Solution Approach 1:
The patent implements self-service resource management where devices automatically declare their computing capabilities and resource availability to the network. Edge devices autonomously manage their own computing resources, memory, and processing power without requiring complex centralized resource allocation. The system allows devices to self-register and self-manage their edge computing participation based on their current state.
Solution Approach 2:
The patent employs feedback mechanisms where devices continuously report their computing resource status, availability, and performance metrics to the network. This feedback enables dynamic resource allocation and service routing, allowing the system to adapt to changing device states without complex manual resource management. The feedback loop ensures reliable service provision by routing tasks to devices that currently have available resources.
Data Source
AI summary
An electronic device includes: a communication module; a memory; and a processor configured to: receive a connection test command for a leaf device positioned in a network from an external server by using the communication module; based on receiving the connection test command, identify whether a connection to the leaf device is possible, by using the communication module, and transmit a result of the identification to the external server; based on identifying that the connection to the leaf device is possible, receive at least one module configured to perform an edge computing service from the external server, and store and install the at least one module in the memory; and execute the installed at least one module to perform the edge computing service, based on data received from the leaf device.