Dynamic Flow Distribution Table for Packet Load Balancing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Distributed computing systems face challenges in efficiently managing packet flow load balancing across multiple interconnected processing nodes, particularly in maintaining service consistency and minimizing packet loss during node failures or changes in system capacity.
Innovation Solution
Implementing a dynamic flow distribution table (FDT) that allows traffic nodes to redistribute key ranges based on capacity and load considerations, enabling seamless migration of packet flow ownership between nodes without manual reconfiguration, and ensuring that active flows are not disrupted during node failures or changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static flow distribution table is used to assign key ranges to traffic nodes, then the system is simple to implement, but the system cannot adapt to changing capacity and load conditions
Solution Approach 1:
The patent implements a dynamic flow distribution table that automatically redistributes key ranges among traffic nodes based on real-time capacity and load conditions. The system can migrate key ranges from overloaded nodes to underloaded nodes without manual reconfiguration, enabling the system to adapt to changing conditions while maintaining load balancing.
Solution Approach 2:
The system performs self-adjustment by automatically detecting capacity and load conditions, making decisions about key range redistribution, and implementing changes without external intervention. This self-service mechanism reduces the need for manual management while maintaining adaptability.
2Reliability
If manual reconfiguration is used to redistribute key ranges, then the system can adapt to node failures, but the process is time-consuming and may disrupt active flows
Solution Approach 1:
The system prepares for node failures by continuously monitoring capacity and load conditions, enabling proactive redistribution before failures occur. When failures do happen, the pre-established automatic redistribution mechanism can quickly reallocate key ranges without manual intervention, minimizing service disruption.
Solution Approach 2:
The system continuously monitors capacity and load conditions of traffic nodes, using this feedback to automatically adjust key range assignments. This closed-loop control ensures that the system responds dynamically to changing conditions, including node failures, without requiring manual reconfiguration.
3Productivity
If key ranges are redistributed to balance load, then traffic node utilization is improved, but active flows may be disrupted
Solution Approach 1:
The patent segments the key space into manageable key ranges that can be independently redistributed. This segmentation allows the system to balance load by migrating individual key ranges without affecting the entire flow distribution, thereby maintaining service consistency for active flows while improving overall utilization.
Solution Approach 2:
The system applies different handling to different key ranges based on their current ownership and the status of associated flows. When redistributing key ranges, the system preserves bindings for active flows while allowing redistribution of inactive flows, ensuring that local quality of service is maintained while achieving global load balancing.
Data Source
AI summary
In general, techniques for implementing a flow distribution service using a plurality of traffic nodes that may operate as processing nodes of a distributed computing system are described. In some examples, the traffic nodes in the aggregate form a virtual appliance configured to apply a network service to packet flows.