Push Notification Throttling via Workload Modeling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Cloud-based computing systems face increased latency and service outages due to excessive push notifications overwhelming service providers, as the existing systems do not effectively manage the resource utilization and transmission rate of push notifications.
Innovation Solution
A method to dynamically adjust the frequency of generating and transmitting push notifications based on resource utilization and available computing resources at service providers, using a workload analyzer to determine the optimal transmission rate and prevent system overload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If push notifications are transmitted at a high frequency to endpoint systems, then the productivity of the push notification system is improved, but the service provider experiences increased latency and may become unavailable due to resource overload
Solution Approach 1:
The system dynamically adjusts the push notification transmission rate based on real-time resource utilization monitoring at the service provider. The workload analyzer continuously evaluates current workload conditions and modifies the transmission rate accordingly, transitioning from a static high-frequency approach to a dynamic adaptive approach that maintains productivity while preventing service overload
Solution Approach 2:
The system implements a feedback mechanism where the service provider's resource utilization is monitored and fed back to the push notification system. The workload analyzer uses this feedback information to adjust the transmission rate, creating a closed-loop control system that balances notification delivery with service provider capacity, thereby maintaining reliability while achieving productivity goals
2Speed
If push notifications are transmitted at a high frequency, then the speed of data delivery to endpoint systems is improved, but the service provider experiences resource overload and increased latency
Solution Approach 1:
The transmission rate is dynamically adjusted based on service provider workload conditions. When resource utilization is low, the system increases transmission speed to deliver data quickly. When workload increases and latency risks emerge, the system automatically reduces the transmission rate, creating a dynamic balance between delivery speed and processing time
Solution Approach 2:
The workload analyzer performs preliminary assessment of service provider capacity before initiating push notification transmissions. By evaluating resource availability in advance, the system can plan transmission schedules that optimize delivery speed while preventing latency caused by resource contention, essentially preparing the transmission strategy before execution
Data Source
AI summary
The present disclosure relates to managing a rate of generating data requests to be processed at a service provider. An example method generally includes detecting an instance of a push notification event directed to a group of endpoint systems. The push notification event generally indicates that push notifications are to be transmitted to the group of endpoint systems to generate the data requests. A computing system determines a resource utilization associated with at least one of the data requests generated based on the push notification event and determines a push notification transmission rate based on the determined resource utilization and computing resources available at the service provider. The rate generally indicates a number of push notifications to generate and transmit over a period of time. The computing system transmits the push notifications to the group of endpoint systems based on the calculated push notification transmission rate.