Message Filter Module for Enterprise Messaging Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Enterprise messaging systems face inefficiencies due to the need to manually restart messages when receiver systems are offline and the consumption of resources in processing asynchronous messages, especially during peak workloads and when messages are dependent on other messages' processing states.
Innovation Solution
A messaging system with a filter module that selectively stops and resumes message processing based on predefined criteria, such as message content, sender and receiver properties, and queue order, allowing messages to be stored and processed only when the receiver system is online, reducing resource consumption and ensuring ordered delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If messages are continuously processed and sent to receiver systems, then message delivery speed is improved, but resource consumption increases during peak workloads and offline receiver scenarios
Solution Approach 1:
The system performs preliminary actions by filtering messages before they reach the receiver system. The filter module pre-processes messages to identify those that should be stopped based on predefined criteria, and the queue module pre-organizes stopped messages for later resumption. This preliminary processing reduces resource consumption during peak workloads while maintaining delivery speed for critical messages.
Solution Approach 2:
The messaging system dynamically adjusts its behavior based on receiver system status and workload conditions. The filter module dynamically applies different filtering criteria based on message content, sender/receiver properties, and queue order. The queue module dynamically manages message resumption based on predefined time or event conditions, allowing the system to adapt resource allocation in real-time.
2Reliability
If all messages are processed manually after errors occur, then message delivery reliability is improved, but processing time and resource consumption increase significantly
Solution Approach 1:
The system performs self-service by automatically managing message errors and resumption. When messages are stopped due to receiver offline status or other conditions, the queue module automatically stores them and the filter module automatically resumes processing when predefined conditions are met. This eliminates the need for manual intervention while maintaining delivery reliability and reducing processing time.
Solution Approach 2:
The system implements feedback mechanisms where the filter module monitors message processing status and receiver system availability. When messages are stopped, the system tracks their status and automatically resumes processing when conditions change. This feedback loop ensures reliable message delivery without requiring manual checking or intervention.
3Use of energy by moving object
If messages are filtered and stopped based on predefined criteria, then resource consumption is reduced, but message processing complexity increases
Solution Approach 1:
The system segments the message processing function into distinct modules: a filter module that handles message filtering based on predefined criteria, and a queue module that manages stopped and resuming messages. This segmentation reduces overall processing complexity by dividing the complex task into manageable, independent functions that can be optimized separately.
Solution Approach 2:
The filter module uses parameter changes in predefined criteria to control message filtering. By adjusting filter parameters such as message content patterns, sender/receiver properties, queue order, and message type/size, the system can dynamically change filtering behavior without increasing structural complexity. This allows resource optimization through parameter tuning rather than system redesign.
4Reliability
If messages are processed in queue order to ensure delivery guarantees, then message delivery reliability is improved, but processing speed decreases during peak workloads
Solution Approach 1:
The system performs preliminary filtering actions before queue processing to identify and stop messages that don't meet delivery criteria. This preliminary action reduces the number of messages that need to be processed in queue order, maintaining delivery reliability for critical messages while improving overall processing speed during peak workloads by filtering out non-essential messages early.
Data Source
AI summary
A system and method for filtering messages in a messaging system is described. The system includes a user interface configured to receive user input for defining one or more message filters. Each message filter specifies predefined criteria by which a message is to be stopped. The system further includes a filter module comprising the one or more filters, and a queue connected with the filter module for queuing messages stopped according to one of the one or more filters. In a method, messages in the messaging system are stopped according to predefined criteria. Stopped messages are restarted according to a job executed by the messaging system.