Proactive Bandwidth Probing for Network Path Reliability
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Solution Overview
Problem
Existing network optimization techniques rely on reactive approaches, leading to periods of reduced performance before corrective measures are taken, making it difficult to distinguish and optimize traffic flows for specific applications in enterprise networks with varying service level agreements (SLAs) and bandwidth demands.
Innovation Solution
A predictive performance architecture that uses machine learning and proactive bandwidth probing to identify optimal times for sending probe packets, dynamically adjust probing rates based on network conditions, and collect data to determine available bandwidth limits, ensuring SLAs are met without impacting user traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reactive techniques are used to enforce network performance criteria, then network performance can be monitored and adjusted, but the network experiences periods of reduced performance before corrective measures are taken
Solution Approach 1:
The system performs preliminary actions by proactively probing network paths before congestion occurs. Bandwidth probing is initiated in advance to predict available capacity and identify potential bottlenecks, allowing the network to take corrective measures before performance degradation happens, thus eliminating periods of reduced performance
Solution Approach 2:
The system implements continuous feedback loops where bandwidth probing results are constantly monitored and fed back to adjust network routing and resource allocation. This real-time feedback mechanism enables dynamic adaptation to changing network conditions, maintaining reliable performance by continuously optimizing based on current bandwidth availability
2Measurement precision
If traditional bandwidth probing is performed continuously, then available bandwidth can be determined, but user traffic is impacted during probing
Solution Approach 1:
Instead of continuous probing, the system employs periodic bandwidth probing at strategically selected intervals. Probe packets are sent at specific times when user traffic patterns indicate optimal conditions, allowing accurate bandwidth measurement while minimizing disruption to user traffic. The periodic nature ensures measurements are taken frequently enough to maintain accuracy without continuously impacting user experience
Solution Approach 2:
The system dynamically adjusts probing parameters based on current network conditions and user traffic patterns. When user traffic is heavy, probing intensity is reduced or paused. When conditions are favorable, probing is intensified to gather more data. This dynamic adaptation allows the system to maintain measurement precision while protecting user traffic quality under varying load conditions
3Productivity
If multiple applications with different SLAs share the same network, then network resource utilization is maximized, but it becomes difficult to distinguish and optimize traffic flows for specific applications
Solution Approach 1:
The system applies local quality by customizing bandwidth probing and optimization parameters for each application's specific SLA requirements. Different applications receive tailored probing strategies, measurement thresholds, and optimization rules based on their individual performance needs. This allows the network to maintain high overall utilization while simultaneously optimizing each application's traffic flow according to its specific characteristics and service level agreements
Data Source
AI summary
In one embodiment, a time period is identified in which probe packets are to be sent along a path in a network based on predicted user traffic along the path. The probe packets are then sent during the identified time period along the path. Conditions of the network path are monitored during the time period. The rate at which the packets are sent during the time period is dynamically adjusted based on the monitored conditions. Results of the monitored conditions are collected, to determine an available bandwidth limit along the path.