M2M Resource Offloading to Edge Nodes for Latency Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In Machine-to-Machine (M2M) systems, existing technologies face challenges in managing resources efficiently, leading to delays and reliability issues due to high overhead on central servers, particularly in applications requiring low latency, such as vehicle collision avoidance systems, where resource processing needs to be distributed to edge or fog nodes for real-time processing.
Innovation Solution
Implementing a resource offloading method that allows M2M nodes to transfer resources from central servers to edge or fog nodes, enabling local processing and reducing latency by managing resources through a blocking, readable, or writable policy, and synchronizing data using periodic, update, or termination modes, thereby offloading resources from infrastructure nodes to middle or application nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If resources are processed on central servers, then system control is simplified, but processing delay increases and reliability decreases
Solution Approach 1:
The patent segments resource processing by dividing the system into infrastructure nodes (central servers) and middle/application nodes (edge devices). Resources are segmented and processed at different levels - critical real-time resources are processed at middle/application nodes while less time-sensitive resources remain at infrastructure nodes, enabling both low latency and simplified control.
Solution Approach 2:
The patent introduces a hierarchical dimension to resource processing by establishing multiple processing levels (infrastructure layer and middle/application layer). This dimensional change allows resources to be processed at the most appropriate level based on requirements, transforming a single-point processing model into a multi-level distributed architecture that simultaneously achieves speed and reliability.
2Speed
If resources are offloaded to edge nodes, then processing speed increases, but system complexity increases
Solution Approach 1:
The patent implements dynamic resource allocation where the system can flexibly assign resources to either infrastructure nodes or middle/application nodes based on real-time conditions. The blocking policy dynamically controls access to offloaded resources, allowing the system to adapt to varying computational demands and maintain simplicity through intelligent resource management rather than fixed complex architecture.
3Reliability
If access control is implemented for offloaded resources, then security is improved, but operation flexibility is reduced
Solution Approach 1:
The patent applies local quality by implementing different access control characteristics for different resource types and locations. The blocking policy provides selective access control - blocking operations for certain resources while allowing others, thereby maintaining security for critical resources while preserving operational flexibility for non-critical resources.
Data Source
AI summary
The present invention relates to a method of performing group management in a machine-to-machine (M2M) system. Herein, the group management method may include controlling a group member included in a group based on a group resource.