IoT Device Logical Networking via Partitioned Virtual Space
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Solution Overview
Problem
Current IoT technologies face scalability issues in forming high-quality connections between diverse IoT devices, as centralized matchmaking approaches require excessive computational resources, lack autonomy, and raise privacy concerns, while decentralized methods often miss suitable partner devices due to artificial constraints and limited scalability.
Innovation Solution
The implementation of a distributed system using software agents and a partitioned virtual space to determine pairwise affinities based on personality and behavioral attributes of IoT devices, allowing them to form logical connections autonomously and efficiently, with data privacy protection through decentralized storage and decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized matchmaking approaches are used to form connections between IoT devices, then connection quality can be improved, but computational resource requirements and system complexity increase excessively
Solution Approach 1:
The patent divides the centralized matchmaking system into distributed autonomous software agents deployed on individual IoT devices. Each agent independently performs affinity determination with other agents, eliminating the need for a central matchmaking server and reducing system complexity while maintaining connection quality through decentralized decision-making.
Solution Approach 2:
IoT device agents autonomously determine their own affinities with other devices without external intervention. The agents independently evaluate compatibility metrics, make connection decisions, and manage their own relationship portfolios, enabling self-service connection formation that reduces computational burden on central systems.
2Extent of automation
If decentralized matchmaking methods are used to reduce computational burden, then device autonomy is improved, but the ability to find suitable partner devices deteriorates due to artificial constraints
Solution Approach 1:
The patent introduces a multi-dimensional affinity determination framework that evaluates devices across multiple compatibility metrics simultaneously. This dimensional expansion allows autonomous agents to assess partner suitability comprehensively without artificial constraints, finding suitable matches by considering diverse attributes beyond simple proximity or device type.
Solution Approach 2:
The system dynamically adjusts affinity determination parameters and compatibility thresholds based on device characteristics, interaction history, and network conditions. This parameter adaptability enables autonomous agents to optimize partner selection for diverse device types and scenarios, maintaining versatility while preserving device autonomy.
3Productivity
If profile data is centralized for affinity determination, then matchmaking efficiency is improved, but data privacy and security concerns worsen
Solution Approach 1:
The patent extracts sensitive profile data from centralized repositories and distributes it to autonomous software agents residing on individual IoT devices. This extraction and distribution eliminates the single point of vulnerability, allowing efficient local affinity determination while protecting privacy through decentralized data storage and processing.
Solution Approach 2:
The autonomous software agent acts as an intermediary between profile data and affinity determination processes. The agent locally processes compatibility assessments using stored profile information, eliminating the need to transmit sensitive data over the network and reducing privacy risks while maintaining matchmaking efficiency through local computation.
Data Source
AI summary
A partitioned virtual space supports logical networking of IoT 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. Agents of devices having affinity are connected in a logical network. Some attributes can be based on a personality model and can reflect the personality of a user or other principal associated with a device. Such attributes can influence requests for affinity testing, calculation of similarity, and further behavioral effects incorporated in affinity determination. Evaluation of recommendations can lead to updating of similarity scores or changes in affinity determination. Disclosed embodiments provide scalable, distributed, autonomous, and unsupervised device-to-device connectivity, free of prior constraints. Embodiments can be implemented in the cloud, with privacy protection.