Centralized Proximity Discovery Server for Ad Hoc Networks
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Solution Overview
Problem
Current proximity-based systems for mobile devices face issues with privacy, scalability, interoperability, and user experience, often requiring resource-intensive applications and relying on peer-to-peer data exchange, which can lead to data synchronization problems and unnecessary disclosure of private information.
Innovation Solution
A system and method utilizing a network of clients with recognition equipment and a server to identify other devices matching predetermined criteria, where clients can be in active or passive states, and the server manages user profiles and coordinates device interactions to reduce redundant discoveries and ensure authorized data sharing, using a centralized approach to handle multiple profiles and geographical awareness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If peer-to-peer proximity-based systems are used, then device discovery capability is improved, but device resource consumption (CPU, memory, storage) increases significantly
Solution Approach 1:
The patent introduces a server as an intermediary component that handles the complexity of proximity-based matching. Instead of requiring devices to perform resource-intensive peer-to-peer discovery and matching algorithms, the server receives location information from devices, performs the matching against stored profiles, and returns results. This mediator approach transfers computational burden from resource-constrained mobile devices to a more powerful server infrastructure.
2Productivity
If peer-to-peer data exchange is implemented, then direct device communication is improved, but data synchronization reliability deteriorates
Solution Approach 1:
The server acts as a central intermediary that receives data from devices, maintains authoritative copies of user profiles and location information, and distributes relevant data to appropriate devices. This centralized coordination ensures that all devices work with synchronized, consistent data, eliminating the synchronization problems inherent in distributed peer-to-peer systems where each device maintains its own local copy.
3Measurement precision
If proximity-based applications continuously monitor location, then discovery accuracy is improved, but privacy protection deteriorates
Solution Approach 1:
The system performs preliminary actions by having users pre-register their profiles, interests, and preferences in advance on the server. When location-based matching is needed, the system queries this pre-prepared information rather than requiring continuous monitoring or real-time disclosure of sensitive personal data. This allows accurate matching based on user characteristics without continuously exposing private information.
Solution Approach 2:
The server mediates the privacy concern by receiving location information from devices, performing matching against stored profiles, and returning only relevant match results. Individual devices do not need to continuously broadcast or monitor detailed location data, reducing privacy exposure while maintaining discovery accuracy through the server's coordinated processing.
4Difficulty of detecting and measuring
If specialized proximity applications are deployed on each device, then discovery functionality is improved, but scalability deteriorates
Solution Approach 1:
The server intermediary handles the complexity of discovery functionality, allowing devices to use simpler clients that communicate with the server. This architecture improves scalability because adding new devices or users only requires server-side processing, not deployment of complex specialized applications on each device. The server can dynamically adapt to new devices and profiles without requiring updates to individual device software.
Data Source
AI summary
A network has clients and a server. The clients can discover and be discovered by each other. Discovery includes emitting requests to and acquiring identifying information from clients within a certain geographical range. A discovering client sends all identifying information to the server. The server includes client information database and topological map, comprised of nodes representing clients and edges indicating the discovery of one client by another. When the server receives identifying information from the discovering client, the server updates the topological map and determines which neighboring clients of the discovering client matches the match criteria of the discovering client. The server may determine a discovery schedule detailing which client should discover next. The server may send the match information and discovery schedule to the discovering client, discovered clients, or a third party. The server may also store this information.