Rapid Testing of IaaS Resource Management Algorithms via Cloud Middleware Simulation

TL;DR

This paper introduces a simulation approach for testing IaaS resource management algorithms that uses runtime monitoring data to automatically create models, reducing implementation effort and accurately reflecting real hardware behavior.

Contribution

The authors present a novel simulation method that automatically constructs models from runtime data, enabling efficient testing of resource management algorithms without reimplementation.

Findings

Simulation results match real hardware behavior

Reduces effort in algorithm testing

Automates model creation from runtime data

Abstract

Infrastructure as a Service (IaaS) Cloud services allow users to deploy distributed applications in a virtualized environment without having to customize their applications to a specific Platform as a Service (PaaS) stack. It is common practice to host multiple Virtual Machines (VMs) on the same server to save resources. Traditionally, IaaS data center management required manual effort for optimization, e.g. by consolidating VM placement based on changes in usage patterns. Many resource management algorithms and frameworks have been developed to automate this process. Resource management algorithms are typically tested via experimentation or using simulation. The main drawback of both approaches is the high effort required to conduct the testing. Existing Cloud or IaaS simulators require the algorithm engineer to reimplement their algorithm against the simulator's API. Furthermore, the engineer manually needs to define the workload model used for algorithm testing. We propose an approach for the simulative analysis of IaaS Cloud infrastructure that allows algorithm engineers and data center operators to eval- uate optimization algorithms without investing additional effort to reimplement them in a simulation environment. By leveraging runtime monitoring data, we automatically construct the simula- tion models used to test the algorithms. Our validation shows that algorithm tests conducted using our IaaS Cloud simulator match the measured behavior on actual hardware.