Mobile Data Proxy Scheduling for Energy Savings
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Solution Overview
Problem
Mobile devices face significant energy consumption challenges due to increasing power demands and data communication costs, leading to frequent battery recharges, with energy being consumed before and after data transfers, and background app activities contributing to these issues.
Innovation Solution
The system identifies data consumption patterns on mobile devices, determines sensitivity to delay, and aggregates network access for background services based on user tolerance, using a data proxy to intercept and bundle delay-tolerant data, reducing energy consumption by deferring low-priority data transfers to more power-efficient connections and pre-fetching associated data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If background services continuously access data in the background, then data availability and responsiveness are improved, but energy consumption increases
Solution Approach 1:
The patent implements periodic network access scheduling where background services are allowed to access data only during specific time windows rather than continuously. The system defines scheduled time periods when network access is permitted and blocks access outside these periods, creating a periodic pattern that reduces energy consumption while maintaining data availability during active periods.
Solution Approach 2:
The system performs preliminary classification of data traffic into delay-tolerant and delay-sensitive categories before scheduling network access. By pre-identifying which data can tolerate delays, the system can aggregate these requests and schedule them during off-peak energy consumption periods, thereby reducing overall energy usage while ensuring time-critical data receives immediate attention.
2Speed
If data transfers are performed immediately when needed, then user experience and responsiveness are improved, but energy consumption during transfer increases
Solution Approach 1:
The system performs preliminary classification of incoming data traffic to identify delay-tolerant data before it reaches the user. By pre-sorting data into categories based on urgency and tolerance for delay, the system can defer non-critical data transfers to periods when energy consumption is lower, while ensuring critical data is transferred immediately, thus optimizing the balance between transfer speed and energy cost.
Solution Approach 2:
The patent introduces a data proxy or intermediary component that sits between the network and the application, intercepting data requests and managing their scheduling. This intermediary classifies traffic, determines scheduling priorities, and buffers delay-tolerant data, allowing the system to control when transfers occur and choose more energy-efficient transmission opportunities without impacting user-perceived performance for critical data.
3Reliability
If the mobile device remains in high power state for data communication, then data transfer reliability is improved, but tail energy consumption increases
Solution Approach 1:
The system uses periodic scheduling to control when the device activates its communication radio for data transfers. By concentrating multiple data transfers into scheduled time windows and then entering low-power states between these windows, the device maintains reliability during active transfer periods while significantly reducing tail energy consumption that would otherwise be spent keeping the radio in high-power standby mode.
4Adaptability or versatility
If multiple background services access the network independently, then service functionality is maintained, but ramp energy costs increase
Solution Approach 1:
The patent merges multiple independent background service network requests into a unified scheduled access mechanism. Instead of allowing each service to independently activate the network radio (causing multiple ramp-up energy events), the system consolidates these requests and schedules them during common time windows, allowing the radio to remain active for extended periods serving multiple services simultaneously, thereby reducing the frequency of ramp-up events and associated energy costs.
Data Source
AI summary
Systems and methods of scheduling data in background services on mobile devices are disclosed. An example method includes identifying data consumption patterns on a mobile device. The method also includes determining sensitivity of data arriving at the mobile device based on the data consumption patterns. The method also includes aggregating network access by background services on the mobile device according to a schedule based on the sensitivity of the data arriving at the mobile device.


