Temporary IoT Device Grouping Using Function Usage Thresholds
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Solution Overview
Problem
Current technologies face challenges in efficiently organizing temporary device groups for collaborative computing in IoT environments, where devices struggle to dynamically form and manage groups based on functional needs and resource utilization, leading to inefficiencies and suboptimal performance.
Innovation Solution
A computer-implemented method and system that calculates individual function usage scores for devices, allowing them to form temporary device groups when the score exceeds a threshold, enabling the sharing of functions and data, and dynamically reconfigure groups based on changing efficiency gains and losses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If devices form temporary groups for collaborative computing, then resource utilization and performance are improved, but device complexity and management overhead increase
Solution Approach 1:
Devices autonomously calculate their own function usage scores and make independent decisions about joining or leaving device groups based on whether the score exceeds a threshold. Each device self-manages its participation in collaborative groups without requiring centralized coordination, thereby improving resource utilization while avoiding complex group management overhead.
2Adaptability or versatility
If devices dynamically form and reconfigure groups, then adaptability and efficiency are improved, but stability and reliability decrease
Solution Approach 1:
The system implements dynamic device group formation where devices can join or leave groups based on changing conditions. The function usage score is continuously calculated and compared against a threshold, allowing groups to form and reconfigure adaptively when beneficial while maintaining stability when conditions are favorable, thus balancing adaptability with reliability.
3Productivity
If devices calculate function usage scores and form groups when exceeding threshold, then collaboration efficiency is improved, but energy consumption and computational overhead increase
Solution Approach 1:
The system uses a threshold-based parameter change approach where devices only perform computationally intensive collaboration operations when the function usage score exceeds a predefined threshold. This conditional activation reduces unnecessary computational overhead and energy consumption while maintaining high collaboration efficiency when conditions warrant group formation.
Data Source
AI summary
Provided are techniques for organizing a temporary device group for collaborative computing. A list of functions for each of a plurality of devices are stored. A determination is made to form a device group including a receiver device from the plurality of devices, where the receiver device will perform one of the functions. An individual function usage score is generated. In response to the individual function usage score exceeding a device threshold, a request to form a device group is sent to the receiver device. In response to receiving an indication of acceptance to form the device group from the receiving device, the device group is formed for a temporary period, where functions and data are shared in the device group.