SDN Metrics Aggregation Granularity and Storage
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for monitoring the health of edge gateways in software-defined networks (SDNs) lack an efficient framework for collecting and aggregating operational data, leading to inadequate network performance monitoring and potential overloading issues.
Innovation Solution
A framework is deployed that collects operational data from network elements in SDNs, allowing for customizable data collection, aggregation, and storage criteria through an interface, using data collectors and a parser/translator system to configure and aggregate data based on client application requirements, and stores aggregated data in a time-series database for efficient monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If operational data is collected and stored for all network elements with high granularity and long retention periods, then monitoring precision and reliability are improved, but storage requirements and system complexity increase significantly
Solution Approach 1:
The patent segments operational data into multiple granularity levels (fine-grained and coarse-grained) and implements separate storage strategies for each level. Fine-grained data is stored for short periods while coarse-grained aggregated data is stored long-term, allowing the system to maintain high monitoring reliability for recent events while reducing overall storage complexity and costs.
Solution Approach 2:
The system implements periodic aggregation of operational data at scheduled intervals, transforming detailed fine-grained metrics into summarized coarse-grained metrics. This periodic processing reduces the volume of data requiring long-term storage while preserving essential monitoring capabilities across different time scales.
2Adaptability or versatility
If different client applications require different aggregation criteria and time periods for operational data, then adaptability to specific monitoring needs is improved, but system complexity in managing diverse requirements increases
Solution Approach 1:
The patent creates a universal data storage and retrieval system that handles multiple client applications with diverse monitoring requirements through a common architecture. The system provides unified interfaces for configuring aggregation criteria, storage parameters, and data retrieval, allowing different applications to access operational data according to their specific needs without requiring separate specialized systems.
Solution Approach 2:
The system implements dynamic configuration capabilities that allow aggregation criteria, time periods, and storage parameters to be adjusted based on specific client application requirements. The framework enables flexible modification of monitoring parameters without requiring system redesign, adapting to changing monitoring needs of different applications.
3Loss of information
If fine-grained operational data is retained for long periods, then historical analysis capability is improved, but storage costs and data retrieval complexity increase
Solution Approach 1:
The patent segments historical data into fine-grained and coarse-grained representations stored for different durations. Recent fine-grained data is retained for detailed analysis, while older data is aggregated into coarse-grained summaries for long-term historical analysis. This segmentation preserves essential historical information while dramatically reducing total storage requirements.
Solution Approach 2:
The system performs periodic aggregation of fine-grained operational data into coarse-grained summaries at scheduled intervals. This periodic transformation enables the system to maintain long-term historical data availability in an efficient format, reducing storage volume while preserving the ability to perform historical analysis at appropriate levels of detail.
Data Source
AI summary
Some embodiments provide a novel method of presenting operational data from several network elements in a software-defined network (SDN). An operational data aggregator of the SDN receives a first request to view metric data for a first time period prior to a current time. The operational data aggregator presents the a first group of sets of aggregated metrics created for the first time period. The operational data aggregator also receives a second request to view metric data for a second time period prior to the current time. The operational data aggregator presents a second group of sets of aggregated metrics created for the second time period. The first group of sets of aggregated metrics has at least one aggregated metric set that is at a different aggregation granularity than all other sets of aggregated metrics in the second group of sets of aggregated metrics.