Geolocation-Based Load Balancing for Mobile Cloud Services
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Solution Overview
Problem
The increasing network traffic from high-end mobile devices poses a communication bottleneck in cloud computing environments, particularly when handling large volumes of map image or distribution data, as existing infrastructures are not optimized for mobile computing applications.
Innovation Solution
A load balancer is configured to provide geolocation-based load balancing between database servers and application servers, dynamically managing data caches based on user device movement, calculating the probability of movement, and adjusting the amount of cached data to be copied between cache servers to optimize data access and reduce bottlenecks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing infrastructure is used for mobile computing applications, then business applications can run on personal computers, but communication between database server and Web application server becomes a bottleneck due to large volume of data retrieval
Solution Approach 1:
The patent segments the monolithic data retrieval process into multiple cache servers distributed across different locations. Each cache server stores a portion of the geographical data, allowing parallel access and reducing the communication burden on any single database server. This segmentation transforms the single-point bottleneck into a distributed system where multiple servers can handle requests simultaneously.
Solution Approach 2:
The patent introduces cache servers as intermediary components between the database server and Web application servers. These cache servers act as mediators that pre-store frequently accessed geographical data, intercepting requests before they reach the database server and returning cached data directly. This intermediary layer reduces the frequency and volume of communications between database servers and application servers.
2Speed
If data is cached statically, then data access speed improves, but cache memory is wasted when user devices do not move to expected cells
Solution Approach 1:
The patent implements dynamic cache configuration where the amount of data copied to each cache server is not fixed but adjusted based on real-time or near-real-time user movement patterns. The system calculates movement probabilities and dynamically determines copy factors, allowing cache memory allocation to adapt to changing user behavior. This dynamic approach ensures cache memory is utilized efficiently without being wasted on stagnant data.
Solution Approach 2:
The patent incorporates feedback mechanisms where user movement data is continuously collected and analyzed to update movement probabilities. These updated probabilities feed back into the cache configuration process, creating a closed-loop system that optimizes cache memory usage based on actual user behavior patterns. The feedback ensures that cache memory is allocated to locations where users are actually moving to, rather than based on static predictions.
3Productivity
If more cache servers are deployed, then service capacity increases, but system complexity and data management overhead increase
Solution Approach 1:
The patent designs cache servers with multi-functional capabilities, where each cache server not only stores geographical data but also participates in movement probability calculations and dynamic configuration adjustments. This universal design allows the system to scale by adding identical multi-functional units rather than requiring specialized components for each function, thereby increasing service capacity while maintaining manageable system complexity through standardized, versatile server units.
Data Source
AI summary
Technologies are generally described for geolocation-based load balancing in a cloud computing environment hosting a mobile service. In some examples, a method may include calculating a probability of movement of a user device from a first cell to a second cell, and calculating an amount of cached data to copy from a second cache server corresponding to the second cell to a first cache server corresponding to the first cell based at least in part on the calculated probability.