Network Resiliency Testbed Emulator Using Virtual Machine Clusters
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Solution Overview
Problem
Existing network resiliency testing methods struggle to effectively simulate and evaluate the resiliency of large, complex communication networks, making it difficult to assess the impact of operational optimizations and potential failures.
Innovation Solution
A communication network resiliency testbed emulator is developed using a cluster of virtual machines that execute a distributed network processing model, leveraging swarm theory to analyze least cost paths and simulate communications across emulated networks, allowing for the evaluation of resiliency algorithms on very large networks up to 20,000 nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a cluster of virtual machines executes a distributed network processing model to simulate large networks, then the network size and complexity that can be simulated is improved, but the computational resources and system complexity required increase
Solution Approach 1:
The network simulation system is divided into multiple virtual machines, each handling specific portions of the network topology and traffic. This segmentation allows the system to simulate large networks by distributing the computational load across multiple independent processing units, where each VM manages a manageable subset of the overall network complexity.
Solution Approach 2:
The patent transitions from simulating networks in a single computational environment to a multi-dimensional distributed architecture across multiple virtual machines. This dimensional shift enables the system to handle larger network scales by adding the dimension of distributed parallel processing, where network simulation occurs across spatially separated computational nodes.
2Measurement precision
If swarm theory techniques are used to flood the topology with propagated data structures to analyze least cost paths, then the path analysis capability is improved, but the computational overhead and time required increase
Solution Approach 1:
The swarm theory implementation uses periodic flooding cycles where data structures are propagated through the network topology in controlled waves. Instead of continuous computation, the system performs discrete periodic sweeps across the network, allowing path analysis to converge over multiple cycles while managing computational overhead through rhythmic, structured processing intervals.
Solution Approach 2:
The patent creates multiple copies of data structures representing network paths and propagates them simultaneously through the topology. By replicating path analysis data across multiple virtual machines and processing copies in parallel, the system achieves comprehensive path coverage and accuracy while reducing the time required compared to sequential analysis methods.
3Adaptability or versatility
If the emulator is configured to emulate very large networks with 20,000 nodes, then the resiliency evaluation capability is improved, but the memory and processing requirements increase
Solution Approach 1:
The large-scale network emulation is segmented across multiple virtual machines, with each VM responsible for emulating a specific portion of the 20,000-node network. This segmentation distributes memory and processing requirements across the cluster, allowing the system to emulate very large networks that would be impossible to handle on a single machine while maintaining adaptability to different network configurations.
Solution Approach 2:
The virtual machine cluster is designed with universal functionality to emulate diverse network topologies and configurations. Each VM can adapt to different network roles and requirements, allowing the same infrastructure to handle various emulation scenarios from small to very large networks, thereby improving versatility without proportionally increasing resource consumption for each specific use case.
Data Source
AI summary
A method for network resiliency testing comprising: executing a resiliency testbed application at a plurality of virtual machines; accessing, by the plurality of virtual machines, network configuration data stored in a configuration database, the configuration data corresponding to a topology of a network to be emulated; configuring at least a portion of the virtual machines, according to the network configuration data, to emulate a plurality of nodes of the network to be emulated; automatically determining least cost paths between the plurality of nodes; simulating communications between the plurality of nodes based on the determined least cost paths; and determining one or more metrics of the network to be emulated based on the simulation.