Tour Guiding Resource Scheduling via Edge Caching
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Solution Overview
Problem
Existing mobile network technologies face delays and freezing issues when providing tour guiding resources to users in different locations, as they struggle to accurately predict user movements and pre-determine resource scheduling strategies due to the dynamic nature of user traffic in scenic areas.
Innovation Solution
A method that acquires historical routes of user movements, determines predicted future locations based on current positions and historical data, selects popular locations by user frequency, and schedules tour guiding resources at the core and edge computing layers to pre-load relevant data, reducing delays and enhancing user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If tour guiding resources are provided in real-time from a server, then resource availability is ensured, but service delays and freezing occur due to network transmission latency
Solution Approach 1:
The patent pre-loads tour guiding resources to edge computing nodes before users actually need them, based on historical route data and predicted future locations. This preliminary action stores resources in advance at locations where users are likely to go, eliminating network transmission delays when users request resources during their tours.
Solution Approach 2:
The patent introduces edge computing nodes as intermediaries between the central server and mobile terminals. These edge nodes cache and deliver tour guiding resources locally, reducing dependency on real-time server communication and minimizing network latency while maintaining resource availability.
2Loss of time
If all tour guiding resources are pre-loaded across the network, then service delays are reduced, but network complexity and resource management difficulty increase
Solution Approach 1:
The patent implements localized resource caching at edge computing nodes specific to different geographic locations and tourist attractions. Instead of uniformly distributing all resources network-wide, each edge node stores only the resources relevant to its local area, reducing overall network complexity while maintaining fast local service delivery.
Solution Approach 2:
The patent divides the network into multiple edge computing segments distributed across different locations, each independently managing its own resource cache. This segmentation allows parallel resource management without centralized coordination complexity, reducing overall system complexity while enabling localized fast resource delivery.
3Measurement precision
If historical route data is analyzed to predict user movements, then resource scheduling accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent analyzes only the most relevant historical route data patterns rather than processing complete historical records. By focusing on key movement patterns and frequently visited locations, the system achieves sufficient prediction accuracy while minimizing data processing complexity through selective analysis of essential data elements.
Data Source
AI summary
A method includes: acquiring a plurality of historical routes of movement of a plurality of historical users in a geographic area, wherein each historical route includes at least a portion of a plurality of locations; determining, based on the plurality of historical routes and a plurality of current positions of a plurality of users in the geographic area, a set of predicted locations among the plurality of locations that the plurality of users will visit in the future, respectively, wherein the plurality of users use a tour guiding service associated with the plurality of locations that is provided by a mobile network; selecting a set of popular locations from the set of predicted locations based on the number of users among the plurality of users who will visit each predicted location in the set of predicted locations; and scheduling tour guiding resources associated with the set of popular locations.