Adaptive Polling Interval Optimization for Mobile Network Efficiency
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Solution Overview
Problem
Existing mobile networks are not optimized for frequent, low-throughput data requests from mobile applications, leading to inefficient data transfer and sub-optimal utilization of shared connections, as they do not account for different types of mobile traffic, content, or application behaviors.
Innovation Solution
A distributed proxy and cache system that categorizes mobile traffic and implements delivery policies based on application behavior, content priority, user activity, and user expectations to align data transfer and optimize connections, using a local proxy on the mobile device and a remote proxy server to manage polling intervals and cache content effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mobile networks use high-throughput data transfer designed for large amounts of data, then network bandwidth utilization is improved, but mobile applications requiring frequent low-throughput requests experience inefficient data transfer and sub-optimal connection utilization
Solution Approach 1:
The system dynamically adjusts polling intervals based on observed application behavior patterns, transitioning from static to adaptive timing. The proxy server learns when applications typically request data and optimizes polling frequency accordingly, reducing unnecessary wake-ups and radio activations while maintaining data freshness requirements.
Solution Approach 2:
The invention changes the temporal parameter of polling intervals from fixed values to adaptive values based on application behavior. By analyzing patterns in application data requests and adjusting polling frequency accordingly, the system optimizes the balance between connection utilization and energy consumption for different application types.
2Reliability
If the system polls resources frequently to ensure data freshness, then data availability is improved, but network bandwidth usage and battery consumption increase
Solution Approach 1:
The proxy server implements feedback mechanisms by monitoring application behavior patterns and using this information to adjust polling intervals. The system observes when applications actually request data and uses this feedback to optimize polling frequency, ensuring data is available when needed while avoiding unnecessary network transactions.
Solution Approach 2:
The system performs preliminary analysis of application behavior patterns to predict when data requests will occur. By pre-configuring optimal polling intervals based on historical behavior, the system prepares in advance to poll at the right moments, ensuring data availability without excessive networking.
3Adaptability or versatility
If multiple services trigger client connections at different times independently, then service independence is maintained, but connection alignment and shared connection utilization become sub-optimal
Solution Approach 1:
The proxy server merges multiple independent service polling operations into a coordinated approach. By consolidating polling requests and aligning them based on observed behavior patterns, the system maintains service independence at the application level while achieving optimized connection utilization at the network level through the proxy.
Solution Approach 2:
The proxy server acts as an intermediary between multiple services and the client, coordinating their connection requests. Instead of services directly triggering independent connections, the proxy mediates by aligning polling operations and batching requests, thereby improving shared connection utilization while preserving service autonomy.
Data Source
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AI summary
Systems and methods for optimizing a polling interval to capture new or changed content at an application server in a wireless network are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, for polling the application server using a first polling interval, monitoring responses received from the polling of the application server, adjusting the first polling interval to a second polling interval for polling the application server and/or using the second polling interval for polling another resource delivering same or similar content as the application server.