Dynamic Resource Placement Control in Network Virtualization
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Solution Overview
Problem
Current network virtualization techniques lack the ability to dynamically adjust resource placement constraints for virtualized network functions (VNFs) at runtime, leading to inefficiencies and potential performance issues due to static constraint models that do not account for changing requirements.
Innovation Solution
A method where a first network entity determines constraints related to a virtualized network function and transmits this information to a second network entity managing resource capacity, allowing for dynamic resource allocation decisions based on these constraints, enhancing flexibility and adaptability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static placement constraints are used in VNF descriptor, then resource allocation is simple and deterministic, but the system cannot adapt to dynamic runtime conditions and changing workload requirements
Solution Approach 1:
The patent transforms static placement constraints into dynamic constraints that can be adjusted at runtime. The NFVO receives runtime information about actual workload conditions and modifies placement constraints accordingly, allowing the system to adapt to changing requirements while maintaining a manageable complexity through structured constraint updates rather than complete re-evaluation
Solution Approach 2:
The patent implements a feedback mechanism where the NFVO continuously monitors runtime conditions (workload, performance metrics, resource utilization) and uses this feedback to adjust placement constraints dynamically. This closed-loop approach enables adaptation to changing conditions while keeping constraint management systematic through automated feedback processing
2Productivity
If the NFVO has full responsibility for resource placement decisions, then global resource optimization is achieved, but the system lacks local expertise about specific VNF requirements and runtime conditions
Solution Approach 1:
The patent introduces the VNF manager as an intermediary between the NFVO and VNFs. The VNF manager provides local knowledge about VNF-specific requirements and runtime conditions to the NFVO through structured interfaces, enabling the NFVO to make globally optimized decisions while preserving access to local expertise through this mediating layer
3Ease of manufacture
If placement constraints are determined statically during VNF design, then constraint definition is straightforward, but constraints cannot reflect actual runtime conditions and workload variations
Solution Approach 1:
The patent uses preliminary static constraints defined during VNF design as initial placement guidelines, which are then refined at runtime based on actual conditions. This two-stage approach maintains the ease of initial constraint definition while improving accuracy through subsequent runtime adjustments that incorporate actual workload and system state information
Data Source
AI summary
There are provided measures for resource placement control in network virtualization scenarios. Such measures exemplarily comprise, in a network virtualization scenario, determining, by a first network entity managing a virtualized network function, constraints related to said virtualized network function, transmitting, by said first network entity, information indicative of said constraints to a second network entity managing resource capacity in said network virtualization scenario, and deciding, by said second network entity, resources or resource capacity to be allocated for said virtualized network function, based on said information indicative of said constraints.