Edge Device Transmission Frequency Management via Utility Optimization
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Solution Overview
Problem
In interconnected distributed networks, the performance of edge devices is restricted by the limited maximum writing frequency, which can hinder data flow and storage efficiency, especially when managing a large number of edge devices.
Innovation Solution
A computer-implemented method using a decentralized optimization algorithm to determine optimal data flow writing frequencies for edge devices, based on their associated utility functions, ensuring convergence and maintaining privacy by local definition and processing within the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the maximum writing frequency MWF is increased to improve data flow writing capability, then the productivity of the network is improved, but the device complexity and privacy protection requirements increase
Solution Approach 1:
Each edge device autonomously determines its own optimal writing frequency by evaluating its utility function and the current system state, without requiring centralized control or complex coordination mechanisms. This self-service approach allows devices to adapt to changing conditions while maintaining overall system efficiency
Solution Approach 2:
The system dynamically adjusts the writing frequency parameter based on utility function evaluations and convergence detection, allowing the frequency to adapt to changing network conditions and device priorities rather than using fixed frequency allocations
2Productivity
If centralized control is used to manage transmission frequency, then the productivity is improved, but the loss of information and privacy protection capability deteriorate
Solution Approach 1:
The frequency management problem is segmented into independent sub-problems at each edge device, where each device locally evaluates its utility function and determines its optimal frequency contribution. This segmentation eliminates the need to share sensitive utility information while still achieving globally optimal frequency allocation
Solution Approach 2:
The system uses an intermediary convergence mechanism where devices iteratively adjust their frequencies based on shared state information without directly sharing their private utility functions. This intermediary approach allows coordination while preserving the privacy of sensitive device-specific information
Data Source
AI summary
In an approach to managing transmission frequency for a plurality of edge devices of an interconnected distributed network, one or more computer processors determine a maximum writing frequency, MWF, for the interconnected distributed network; iteratively process values of data flow writing frequency, DFWF, for a plurality of edge devices of an interconnected distributed network in accordance with an optimization algorithm based on the MWF to identify a convergence in the values of DFWF, wherein each iteration of processing values comprises, at each edge device in the plurality of edge devices, determine a value of DFWF based on an associated utility function of the respective edge device, wherein the utility function is a measure of utility of the device as a function of DFWF; responsive to identifying convergence, determine the converged values of DFWF to be optimal values of DFWF for the plurality of edge devices.