Dynamic Programming for SDN Flow Table Mapping
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Solution Overview
Problem
Existing approaches for mapping virtual flow tables (VFTs) onto physical flow tables (PFTs) in software-defined networking (SDN) are not resource-efficient and unsuitable for real-time use, leading to time-consuming processes that hinder dynamic network adjustments and hitless updates.
Innovation Solution
A dynamic programming-based method is employed to generate a resource-efficient mapping of VFTs onto PFTs, considering the properties and capabilities of each table, which significantly improves mapping performance by several orders of magnitude compared to conventional methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional mapping methods are used for virtual flow tables onto physical flow tables, then the mapping process is simple to implement, but the resource efficiency is poor and the mapping time is excessive
Solution Approach 1:
The patent pre-calculates and stores the mapping relationships between virtual flow tables and physical flow tables in a mapping database before actual network operation. This preliminary action allows the system to quickly retrieve pre-computed mappings during runtime, dramatically reducing the mapping time from hours to seconds while maintaining resource efficiency through optimized mapping algorithms executed in advance.
Solution Approach 2:
The patent implements a dynamic mapping mechanism that can adaptively adjust the mapping relationships between virtual and physical flow tables based on real-time network conditions and resource availability. The system uses dynamic programming algorithms to optimize mapping configurations on-demand, enabling fast reconfiguration without manual intervention and improving both mapping speed and resource utilization.
2Productivity
If conventional mapping methods are used, then the implementation is straightforward, but the resource usage is not optimized
Solution Approach 1:
The patent executes complex dynamic programming algorithms and resource optimization calculations in advance, storing the results in a mapping database. This preliminary computation phase handles the algorithmic complexity offline, allowing the runtime system to simply retrieve pre-optimized mappings, thereby achieving high resource efficiency without adding complexity to the operational system.
Solution Approach 2:
The patent introduces a mapping database as an intermediary layer between virtual flow tables and physical flow tables. This database stores pre-computed optimal mappings generated by complex algorithms, acting as a mediator that translates high-level virtual table requirements into efficient physical table configurations without requiring the operational system to execute complex optimization algorithms in real-time.
3Adaptability or versatility
If real-time mapping adjustments are needed for dynamic network changes, then network adaptability improves, but the mapping process becomes time-consuming
Solution Approach 1:
The patent pre-computes multiple potential mapping configurations and stores them in the mapping database, ready for rapid retrieval. When network conditions change, the system can quickly switch between pre-computed mappings or generate new ones using the stored framework, enabling real-time adaptability without time-consuming optimization calculations during runtime.
Solution Approach 2:
The patent implements a dynamic mapping system that can rapidly reconfigure virtual-to-physical flow table mappings in response to network changes. The system uses lightweight dynamic programming algorithms that leverage pre-computed data structures to generate optimized mappings in seconds, maintaining high network adaptability while minimizing reconfiguration time through efficient incremental updates rather than complete recalculations.
Data Source
AI summary
Methods and apparatus for using dynamic programming to determine the most efficient mapping of a pipeline of virtual flow tables (VFTs) onto a pipeline of physical flow tables (PFTs) in the data plane of a software-defined networking (SDN) device are described. One example method of determining a configuration for an SDN device generally includes receiving a representation of a series of one or more VFTs, each of the VFTs having one or more properties; receiving a representation of a series of one or more PFTs for hardware of the SDN device, each of the PFTs having one or more capabilities; generating, using dynamic programming based on the properties of the VFTs and the capabilities of the PFTs, a mapping of the series of VFTs onto the series of PFTs; and outputting the generated mapping for implementation on the hardware of the SDN device.