Edge Community Alignment for Low-Latency Collaborative Tasks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Edge devices in collaborative systems often face challenges due to mismatches between network-based and task-based communities, leading to inefficient task performance and communication bottlenecks, as they typically have limited computational resources and are remote from cloud data centers.
Innovation Solution
A method and system for aligning network-based and task-based communities by creating virtual private networks and virtual network functions to facilitate communication and resource allocation among edge devices, using active search and community detection algorithms to identify suitable devices for task collaboration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If edge devices rely on cloud data centers for computation-intensive tasks, then computational power is improved, but latency and communication overhead increase due to remote location
Solution Approach 1:
The patent segments the computing system into multiple levels: cloud data centers for heavy computation, edge data centers for intermediate processing, and local edge devices for lightweight tasks. This segmentation allows tasks to be distributed appropriately, reducing latency by keeping time-sensitive operations local while maintaining access to cloud computational power for intensive workloads.
Solution Approach 2:
The patent introduces edge data centers as intermediary components between cloud data centers and local edge devices. These intermediaries provide computational resources closer to the user, reducing communication latency while still leveraging cloud resources when needed, thus resolving the contradiction between computational power and latency.
2Device complexity
If edge devices have limited computational resources, then device complexity is reduced, but task performance deteriorates
Solution Approach 1:
The patent merges the capabilities of multiple edge devices through collaborative task execution. By combining computational resources, storage, and processing power across the network, the system achieves enhanced task performance while individual devices maintain their simplicity and low complexity.
Solution Approach 2:
The patent creates a universal edge computing platform where diverse edge devices with different capabilities can contribute to various tasks. The system dynamically allocates tasks based on device capabilities, allowing simple devices to perform lightweight operations while collectively achieving complex task performance through multi-functionality across the network.
3Adaptability or versatility
If edge devices collaborate without community alignment, then device versatility is improved, but communication efficiency deteriorates due to bottlenecks
Solution Approach 1:
The patent performs preliminary community detection and alignment before task execution. By pre-organizing devices into network-based and task-based communities and aligning them, the system establishes efficient communication pathways in advance, preventing communication bottlenecks during actual task execution while maintaining device versatility.
Solution Approach 2:
The patent implements feedback mechanisms that monitor communication patterns and task performance across the edge device network. This feedback enables dynamic adjustment of community alignments and task assignments, optimizing communication efficiency while preserving the versatility of individual devices to perform diverse functions.
Data Source
AI summary
Communication and task execution in a collaborative manner is disclosed. When a task is received, the task type is determined along with an archetypal device. Next, network-based communities are determined from a graph representing devices in a network. The graph is then searched to identify devices that are compatible with the task and the archetypal device. These devices represent a task-based network. The task-based network and the network-based communities are aligned. This may include establishing connections and network functions, such as virtual private networks and virtual network functions such that alignment is achieved. The task may be performed collaboratively by the devices in the task-based network after alignment.