Location-Based Service Discovery Filtering by Proximity Rules
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Solution Overview
Problem
Existing service discovery mechanisms, such as DNS-SD and mDNS, often provide large lists of service providers that include irrelevant options due to lack of effective filtering by proximity and service type, leading to user devices being presented with numerous, often distant, service providers that are not suitable for the desired service.
Innovation Solution
Implementing a discovery orchestrator that associates service providers with location indicators and service types, applying proximity rules to filter service providers based on their proximity to the user device, ensuring only relevant services are listed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If DNS-SD or mDNS mechanisms are used to discover service providers, then service discovery capability is provided, but the list of service providers becomes large and includes irrelevant distant providers
Solution Approach 1:
The system performs preliminary actions by collecting location information of service providers in advance and storing it in a location database. When a service discovery request is received, the system uses the pre-stored location data to quickly filter providers based on proximity to the user device, avoiding the need to process all service providers from scratch and reducing the size of the returned list.
Solution Approach 2:
The system applies local quality by associating each service provider with location metadata (such as geographic coordinates or proximity indicators). This allows the discovery response to be tailored to the local area around the user device, presenting only service providers that are geographically relevant rather than a universal list of all providers.
2Loss of information
If all service providers are listed without filtering, then complete service provider information is provided, but user devices are presented with numerous irrelevant options reducing efficiency
Solution Approach 1:
The system changes parameters by introducing location-based filtering criteria (such as maximum distance thresholds or proximity thresholds) to the service discovery process. By applying these parameter-based filters, the system transforms the complete but inefficient full list into a optimized subset that maintains sufficient information for users while dramatically improving discovery efficiency by eliminating obviously irrelevant distant providers.
3Ease of operation
If proximity filtering is applied to service providers, then relevant local services are identified, but additional processing complexity is introduced
Solution Approach 1:
The system reduces processing complexity by performing preliminary actions - storing location metadata for all service providers in advance in a centralized database. This pre-processing allows the discovery orchestrator to perform simple database lookups and filtering operations rather than calculating distances and assessing proximity for each service provider in real-time, thus maintaining ease of operation without excessive complexity.
Data Source
AI summary
Databases may include records that: associate service providers with location indicators and with service types. A proximity rule may be associated with one of the service types. A discovery request may include location metadata and a service identifier associated with the service type associated with the proximity rule. In response to receiving the discovery request, the proximity rule may be applied to the location metadata and the location indicators to identify a service provider that satisfies the proximity rule and that provides the service indicated by the service identifier. A discovery response that is responsive to the discovery request and that indicates the service provider may be sent in response to the discovery request.