Network Probe Aggregation via Geographic Proximity
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Solution Overview
Problem
Current methods for collecting network performance data in cloud networks often result in excessive probe traffic, overloading the network and wasting resources, as they require injecting synthetic probe packets into every network path, leading to inefficient data collection and storage due to the abundance of data and lack of processing capabilities.
Innovation Solution
A method that determines the geo-location of target nodes and selects one representative node within a specified proximity radius to collect network performance data, minimizing probe packets and using stored data when available, thereby reducing network bandwidth usage and resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If synthetic probe packets are injected into every network path to every network node, then network performance data can be collected from all nodes, but excessive probe traffic is generated that overloads the network and wastes bandwidth
Solution Approach 1:
The patent merges multiple probe requests into a single probe packet by identifying target nodes within a geographic proximity radius. Instead of sending separate probes to each node, one probe is sent to a representative node, and its performance data is applied to all nodes within the radius, combining multiple measurement tasks into one action.
Solution Approach 2:
The patent makes a single probe packet serve multiple functions by having it collect performance data that represents multiple target nodes simultaneously. The probe packet not only measures the representative node but also provides data for all nodes within the proximity radius, making one probe packet universally applicable to multiple measurement targets.
2Loss of information
If probe packets are sent to every target node, then complete network performance data is obtained, but the quantity of probes injected into the network increases significantly
Solution Approach 1:
The patent combines multiple probe operations into a single probe packet by grouping target nodes within a geographic proximity radius. One probe packet replaces multiple individual probes, reducing the quantity of probe packets while maintaining data completeness for all nodes in the group through the use of representative data.
Solution Approach 2:
The patent creates a copy of performance data from a representative node and applies it to multiple target nodes within the proximity radius. Instead of obtaining original data from each node, the system copies the representative node's data and uses it to represent all nodes in the group, significantly reducing probe traffic.
3Measurement precision
If network performance data is collected from each individual node, then accurate node-specific data is obtained, but storage facilities and processing resources are excessively consumed
Solution Approach 1:
The patent merges the storage requirements for multiple nodes into a single data record by collecting performance data from one representative node and applying it to all nodes within the proximity radius. This approach maintains node-specific accuracy while reducing storage capacity requirements by combining what would otherwise be separate storage entries.
Data Source
AI summary
In an embodiment, a method comprises receiving a request to obtain network performance data for a plurality of target nodes; determining geo-locations of the plurality of target nodes; based on the geo-locations, determining a set of the plurality of target nodes that are within a specified proximity radius; selecting one particular target node in the set; sending a probe packet, requesting network performance data, to the one particular target node in the set and not to all other target nodes in the set; applying, to all the target nodes in the set, network performance data that is received in response to the probe packet; wherein the method is performed by one or more processors.