Presence Service Throttling for Mobile Network Load
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Solution Overview
Problem
Presence systems face challenges in balancing the need for up-to-date presence information with the strain it puts on bandwidth and battery resources, particularly in wireless mobile stations, due to frequent messaging required to maintain updated presence states.
Innovation Solution
A presence service system that monitors network traffic and throttles outgoing presence updates during high network load conditions, using minimum-delay throttling based on factors like the duration of presence sessions and the last incoming update, to reduce the frequency of updates and conserve resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If presence updates are sent frequently to maintain up-to-date presence information, then presence information accuracy is improved, but network bandwidth consumption and battery power usage increase
Solution Approach 1:
The system dynamically adjusts the presence update frequency based on network load conditions. During high network load, the update rate is reduced through throttling, while during low load periods, updates occur more frequently. This dynamic adaptation resolves the contradiction by making the update frequency flexible rather than fixed, allowing the system to maintain accuracy when possible while conserving energy when network conditions demand it.
Solution Approach 2:
The system changes the temporal parameter of presence updates by introducing variable delays between updates based on network load. A minimum delay threshold is enforced during high load conditions, effectively changing the update frequency parameter from a constant high value to a variable value that adapts to network conditions, thus reducing energy consumption while maintaining acceptable presence information accuracy.
2Measurement precision
If presence updates are sent frequently to maintain up-to-date presence information, then presence information accuracy is improved, but network bandwidth consumption increases
Solution Approach 1:
The system dynamically adjusts presence update frequency based on real-time network load monitoring. When network load is high, updates are throttled with enforced minimum delays, reducing bandwidth consumption. When load is low, updates occur more frequently, maintaining accuracy. This dynamic behavior resolves the contradiction by adapting the update rate to network conditions.
Solution Approach 2:
The system changes the temporal parameter of presence updates by introducing variable delays based on network load conditions. During high load, a minimum delay threshold is applied, effectively reducing the update frequency parameter to lower bandwidth consumption. This parameter adaptation allows the system to maintain accuracy when network capacity permits while reducing bandwidth usage when capacity is constrained.
3Quantity of substance
If presence updates are throttled during high network load, then bandwidth consumption is reduced, but presence information becomes less up-to-date
Solution Approach 1:
The system implements periodic presence updates with dynamically adjusted intervals. During high network load, updates occur at longer periodic intervals due to throttling, while during low load, intervals are shorter. This periodic action with variable periods resolves the contradiction by accepting reduced accuracy during high load periods while maintaining better accuracy during low load periods, balancing bandwidth consumption against information freshness.
Solution Approach 2:
The system changes the temporal parameter of presence updates by enforcing minimum delay thresholds during high network load conditions. This parameter change from frequent updates to spaced-out updates reduces bandwidth consumption, while the system accepts the trade-off of less up-to-date presence information during these periods. The parameter is restored to higher frequency when network load decreases.
4Productivity
If different throttling levels are applied based on session duration, then resource efficiency is improved, but device complexity increases
Solution Approach 1:
The system applies different throttling levels to different presence update scenarios based on session duration and update type. New session updates receive higher priority with less throttling, while established session updates receive more aggressive throttling. This local differentiation resolves the contradiction by optimizing resource efficiency for each scenario independently rather than applying a uniform throttling policy, thereby improving overall resource efficiency with manageable complexity.
Solution Approach 2:
The system changes the throttling parameter dynamically based on session duration and update characteristics. By monitoring session age and update type, the system adjusts the minimum delay threshold parameter to apply appropriate throttling levels. This parameter adaptation improves resource efficiency by being more lenient with important updates and more aggressive with routine updates, while the complexity remains manageable through rule-based decision logic.
Data Source
AI summary
Methods and systems are described for providing a presence service that is useful for mobile telecommunications devices. A plurality of outgoing presence updates are sent to a presence client. The system monitors the level of network traffic and determines whether the client is in a region of high network load, and if so, the system throttles the outgoing presence updates during the condition of high network load. The level of throttling may depend at least in part on the amount of time that has elapsed since the presence client began a presence session, and/or the amount of time that has elapsed since an incoming presence update was received from the presence client. In determining the latter amount of elapsed time, the system may consider only the amount of time elapsed since an incoming non-automatic presence update was received from the presence client.