IoT Device Affinity Determination via Distributed Virtual Space
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Solution Overview
Problem
Current IoT technologies face scalability issues in forming connections between diverse IoT devices, as centralized matchmaking approaches are resource-intensive and fail to identify suitable partners outside pre-existing networks, leading to inefficiencies in device-to-device communication.
Innovation Solution
The implementation of a distributed system that uses personality and behavioral attributes to determine affinity between IoT devices, forming logical networks based on similarity scores, allowing devices to autonomously seek connections within a virtual space organized by interests, reducing computational burden and enhancing connection quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If centralized matchmaking approaches are used to form connections between IoT devices, then connection formation is achieved, but scalability is poor and resource consumption is high
Solution Approach 1:
The patent divides the centralized matchmaking system into distributed device agents that operate autonomously. Each device agent independently manages its own profile and performs affinity calculations with other devices, eliminating the need for a central matchmaking server. This segmentation resolves the scalability issue by distributing computational load across multiple devices rather than concentrating it in a single central system.
Solution Approach 2:
Device agents autonomously determine affinity with other devices using similarity scores based on device profiles, without requiring central coordination. Each device independently evaluates potential connections by comparing attributes such as device type, functionality, and operational characteristics. This self-service approach eliminates the resource-intensive centralized matchmaking process while maintaining effective connection formation.
2Productivity
If centralized matchmaking approaches are used, then device connections are established, but the system fails to identify suitable partners outside pre-existing networks
Solution Approach 1:
The patent implements a universal affinity determination mechanism that works across all device types and network configurations. The similarity score calculation uses standardized device profiles that can represent any IoT device, enabling devices to find suitable partners regardless of whether they exist in pre-existing networks. This universal approach allows the system to adapt to diverse device types and identify suitable partners in any network context.
Solution Approach 2:
The system uses adjustable similarity score thresholds and weighted attributes to adapt affinity determination to different device types and connection scenarios. By modifying the parameters in the similarity calculation (such as weighting different device attributes differently), the system can optimize partner identification for various device categories and network conditions, enhancing versatility without requiring device-specific matchmaking logic.
3Reliability
If affinity determination uses multiple device attributes including personality and behavioral attributes, then connection quality improves, but computational complexity increases
Solution Approach 1:
The patent implements a tiered affinity determination process where devices first calculate similarity scores using essential device attributes (device type, functionality), then optionally incorporate personality and behavioral attributes only when needed for final connection decisions. This partial action approach maintains connection quality by using comprehensive attributes when necessary, while reducing computational burden by using simplified attribute sets for initial filtering and routine connections.
Data Source
AI summary
Attributes are applied to Internet-of-Things (IoT) devices to establish high quality connections between the devices. Agents of the devices are assigned to interest-based cells in a virtual space, and can travel among the cells. Within the cells, pairs of devices are tested for similarity, based on device profiles, and for detected affinity. Devices having affinity are connected and form a logical network of IoT devices. Some attributes can be based on a personality model and can reflect the personality of a user or other principal associated with a device. The user or principal attributes can influence requests for affinity testing, calculation of similarity, and further behavioral effects incorporated in affinity determination. Disclosed embodiments provide scalable, distributed, autonomous, and unsupervised device-to-device connectivity, free of prior constraints. Associated infrastructure, simulations, performance metrics, and variations are disclosed.