Cloud Network Manager Simulates Live Traffic for Software Testing
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Solution Overview
Problem
Existing network testing methods for e-commerce systems are inadequate as they do not account for changes in network traffic and resource duplication is costly, leading to potential failures in live production environments.
Innovation Solution
A cloud-based network manager simulates a live customer network to test software upgrades by monitoring and replicating its topology, traffic patterns, and behavior, allowing for automated network testing without the need for a traditional system testing environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a traditional system testing environment is built to mirror the live production environment, then network stability and reliability during software updates can be tested, but the cost of duplicating resources becomes prohibitively expensive
Solution Approach 1:
The patent creates a simulated network environment that replicates the topology, traffic patterns, and behavior of the live production network without physically duplicating expensive hardware resources. The simulation uses virtualized network functions and software-defined networking to model the production environment, allowing comprehensive testing at a fraction of the cost of building a traditional parallel testing infrastructure.
Solution Approach 2:
The patent replaces the mechanical/physical system of duplicating hardware network equipment with a software-based simulation system. Instead of physically copying routers, switches, and servers, the invention uses software models that replicate network behavior, traffic flows, and topological relationships, thereby eliminating the need for expensive hardware duplication while maintaining testing fidelity.
2Measurement precision
If network testing is performed manually by experts to evaluate network capability, then detailed assessment can be achieved, but the process is costly and susceptible to human error
Solution Approach 1:
The simulated network environment performs self-testing and self-validation through automated software agents that monitor network behavior, detect anomalies, and assess software update impacts without requiring manual expert intervention. The system automatically generates test scenarios, executes them, and analyzes results, making the testing process both more accurate and fully automated.
Solution Approach 2:
The patent implements automated feedback loops where the simulation continuously monitors network performance metrics, compares expected vs. actual behavior, and adjusts testing parameters dynamically. This automated feedback mechanism provides precise measurement of network capabilities and identifies issues that would be difficult for manual testers to detect consistently.
3Productivity
If software updates are deployed directly to the live production environment, then deployment speed is maximized, but the risk of network failure and revenue loss increases
Solution Approach 1:
The patent performs comprehensive network testing and validation in the simulated environment before software updates are deployed to production. The simulation pre-identifies potential failures, validates configuration changes, and verifies network stability under various traffic conditions, ensuring that only thoroughly tested updates reach the live environment. This preliminary validation eliminates the need for costly post-deployment fixes and rollback procedures.
Solution Approach 2:
The simulated network environment proactively identifies and mitigates potential failure modes before they can affect the live production system. By testing software updates against simulated traffic patterns and failure scenarios, the system pre-counters potential problems, preventing them from manifesting in the actual network and thereby protecting against revenue loss and service disruptions.
Data Source
AI summary
A method for network testing simulation includes generating a simulated network configuration comprising a plurality of simulation nodes based on a topology of an existing network. The method also includes determining a peak traffic for the existing network based on a volume of traffic processed by the existing network, and a plurality of protocols of the traffic. The method further includes generating a simulated traffic based on the peak traffic, the protocols, and the simulated network configuration. Additionally, the method includes processing the simulated traffic using the simulated network configuration to generate a plurality of simulation states of the nodes. Also, the method includes determining whether the software upgrade is tested successfully based on the generated states of the nodes.