Multi-Layer Edge Simulation Using Segmented Workload Simulators
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Solution Overview
Problem
Current network simulation tools are ineffective for performing high-scale simulations, particularly in multi-layer edge architectures, failing to efficiently simulate large numbers of workloads and status collections.
Innovation Solution
A system is developed that composes multiple simulators to simulate different parts of the network system, enabling efficient simulation of millions to hundreds-of-millions of workloads by configuring endpoint, workload placement, and workload status simulators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current network simulation tools are used for multi-layer edge architecture, then basic simulation functionality is provided, but high-scale simulation capability is insufficient
Solution Approach 1:
The simulation system is divided into multiple independent simulator components, each handling specific aspects of network simulation. This segmentation enables the system to scale to millions of workloads by distributing simulation tasks across multiple specialized simulators rather than using a single monolithic tool.
Solution Approach 2:
The simulation framework is designed to be universally applicable across different network architectures and scales. It can simulate various network configurations, workload types, and edge architecture patterns through a unified interface, making it adaptable to high-scale multi-layer edge scenarios without requiring architecture-specific tools.
2Quantity of substance
If network simulation tools attempt to simulate large numbers of workloads, then simulation comprehensiveness improves, but simulation efficiency deteriorates
Solution Approach 1:
The workload simulation is segmented into parallel processing streams where multiple simulators can simultaneously handle different portions of the workload population. This allows the system to simulate millions of workloads while maintaining efficiency through concurrent execution rather than sequential processing.
Solution Approach 2:
The system dynamically adjusts simulation parameters such as workload generation rates, status collection frequencies, and simulation time steps to optimize performance. By changing these parameters based on the scale of simulation required, the system can efficiently handle varying quantities of workloads without proportional increases in processing time.
3Measurement precision
If detailed workload status collection is implemented, then simulation accuracy improves, but computational overhead increases
Solution Approach 1:
The system implements selective status collection where only relevant workload attributes are tracked at high detail levels, while less critical metrics are collected at lower granularity. This partial action approach maintains measurement precision for key performance indicators while reducing overall computational overhead by avoiding exhaustive collection of all possible status parameters.
Solution Approach 2:
The simulation dynamically adjusts the level of detail in status collection based on workload characteristics and simulation phase. During certain phases, more detailed monitoring is applied to critical workloads, while less intensive monitoring is used for stable or less important workloads, optimizing the balance between accuracy and resource consumption.
Data Source
AI summary
An embodiment establishes a virtual representation of a network configuration, wherein the virtual representation of the network configuration comprises a plurality of layers corresponding to the network configuration. The embodiment generates a plurality of workloads to simulate with the virtual representation. The embodiment generates a plurality of workload statuses to simulate with the virtual representation. The embodiment simulates the plurality of workloads. The embodiment simulates the plurality of workloads statuses. The embodiment receives simulation results responsive to simulating the plurality of workloads and from simulating the plurality of workload statuses.