Service Function Chain Similarity Matching for Faster NFV Deployment
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Solution Overview
Problem
Existing methods for Service Function Chain (SFC) placement and mapping in Network Function Virtualization (NFV) do not effectively utilize similarity between incoming SFC requests and existing SFCs, leading to inefficiencies in mapping and placement time, as well as increased policy redundancy and conflict detection.
Innovation Solution
A similarity manager framework is integrated into the NFV Orchestrator (NFVO) to detect similarities between new SFC requests and deployed SFCs through graph decomposition, translation, and similarity checking, using techniques like frequent sub-graph mining and graph embedding, allowing for faster mapping and reduced policy redundancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional embedding approaches are used for SFC placement and mapping, then comprehensive node and link requirements can be specified, but mapping and placement time is excessive and policy redundancy increases
Solution Approach 1:
The patent applies preliminary action by pre-processing SFC requests into graph representations and storing them in a database before actual placement operations. When a new SFC arrives, the system retrieves and compares pre-processed graphs instead of processing from scratch, significantly reducing mapping time while maintaining placement precision through systematic graph matching algorithms
Solution Approach 2:
The patent segments the SFC placement problem into distinct components: graph representation of SFC requests, graph database storage, graph matching algorithms, and policy constraint verification. This segmentation allows each component to be optimized independently, reducing overall processing time while maintaining comprehensive requirement specification through structured graph models
2Reliability
If traditional SFC placement methods are used, then all policy constraints can be enforced, but policy conflict detection becomes redundant and inefficient
Solution Approach 1:
The patent uses copying by creating graph representations that replicate the structural and constraint information of original SFC requests. These graph copies are stored in the database and can be rapidly retrieved and compared against new requests, ensuring policy compliance through structural matching while dramatically improving deployment efficiency through avoided re-processing
Solution Approach 2:
The patent transforms SFC placement parameters into graph-theoretical parameters (nodes, edges, attributes, constraints) that enable efficient computational matching. This parameter transformation allows the system to enforce comprehensive policy constraints through graph isomorphism testing and subgraph matching, which are computationally more efficient than traditional constraint satisfaction approaches
Data Source
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AI summary
The disclosure relates to a method and system for deploying a new service function chain (SFC) based on similarities with previously deployed SFCs. A service similarity manager framework is proposed to find the exact or partial matching between incoming SFC requests and previously deployed services to accelerate network service provisioning by skipping one or more service provisioning steps while satisfying different constraints. The method comprises receiving a request for the new SFC. The method comprises generating a vector representation for the requested new SFC. The method comprises comparing the vector representation of the requested new SFC with vector representations of previously deployed SFCs. The method comprises identifying a previously deployed SFC similar to the requested new SFC. The method comprises mapping and instantiating a copy of the previously deployed SFC on one or more physical server.