Mobile Network Latency Estimation via Cell Site Aggregation
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Solution Overview
Problem
Existing systems for estimating network latency between computing devices are inaccurate due to missing or misplaced latitude-longitude values for IP addresses, poor correlation between geographic distance and latency, and dynamic network connections in mobile devices, leading to suboptimal user experiences in applications like video streaming and online gaming.
Innovation Solution
A latency estimation method that aggregates latency factors such as cell site identifiers, signal strength, and access proxies from multiple devices to calculate latency as a sum of three components: from the mobile device to a cell site, from the cell site to an access point, and from the access point to the destination device, providing a more accurate estimation for improving user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If geo-location databases are used to convert IP addresses to latitude-longitude values for latency estimation, then the estimation speed is improved, but the accuracy deteriorates due to missing or misplaced latitude-longitude values and poor correlation between geographic distance and latency
Solution Approach 1:
The patent changes the parameters used for latency estimation from geographic coordinates (latitude-longitude) to network-specific parameters (cell site identifiers, access proxies, signal strength). This parameter transformation resolves the contradiction by using parameters that directly correlate with network performance rather than geographic position, thereby improving accuracy while maintaining the speed of database lookups.
Solution Approach 2:
The patent introduces intermediary network elements (cell sites and access proxies) as mediators between the mobile device and the destination. Instead of directly estimating latency based on geographic distance, the system uses these intermediaries as reference points to break down the latency into measurable segments, improving estimation accuracy through indirect measurement.
2Measurement precision
If existing systems measure latencies for computing devices in fixed locations, then the measurement accuracy is improved, but the time cost and data traffic cost increase
Solution Approach 1:
The patent performs preliminary actions by pre-collecting and storing latency measurements from multiple computing devices in a database before they are needed. When a latency estimation is required, the system retrieves pre-computed data and combines it with current device parameters, avoiding the need for real-time measurements and thus reducing time cost while maintaining accuracy through aggregated historical data.
Solution Approach 2:
The patent uses latency measurements from multiple other computing devices as copies or proxies for estimating the latency of the target device. By aggregating measurements from devices in similar network conditions and using statistical methods, the system obtains accurate latency estimates without performing direct real-time measurements, thereby reducing time and data traffic costs.
3Speed
If geo-location databases are used for mobile devices, then the estimation speed is improved, but the accuracy deteriorates because there is often no correlation between IP addresses and latitude-longitude values for mobile devices
Solution Approach 1:
The patent changes the parameters for mobile device latency estimation from IP address-based geographic coordinates to mobile-specific parameters including cell site identifiers, signal strength, and access proxies. These parameters directly reflect the actual network connection state of mobile devices, resolving the correlation problem between IP addresses and physical location while maintaining fast estimation through database lookups.
Solution Approach 2:
The patent adopts dynamic parameters that change with the mobile device's network connection state rather than static geographic coordinates. By using cell site identifiers and signal strength that dynamically reflect the current network environment, the system maintains accurate latency estimation for mobile devices as they move and change networks, while preserving estimation speed through structured database queries.
Data Source
AI summary
Embodiments calculate an estimated latency between computing devices. A latency service aggregates latency records defining latency measurements and corresponding latency factors from a plurality of computing devices. From the aggregated latency records, the latency service defines relationships between the latency measurements and the corresponding latency factors. Responsive to a request for an estimated latency from a mobile computing device, the latency service applies the defined relationships to estimate the latency based on the latency factors associated with the received request. In some embodiments, the estimated latency includes three portions: a first latency value representing the latency from the mobile computing device to a cell site, a second latency value representing the latency from the cell site to an access point, and a third latency value representing the latency from the access point to a destination computing device.