IAD: Indirect Anomalous VMMs Detection in the Cloud-based Environment

by   Anshul Jindal, et al.

Server virtualization in the form of virtual machines (VMs) with the use of a hypervisor or a Virtual Machine Monitor (VMM) is an essential part of cloud computing technology to provide infrastructure-as-a-service (IaaS). A fault or an anomaly in the VMM can propagate to the VMs hosted on it and ultimately affect the availability and reliability of the applications running on those VMs. Therefore, identifying and eventually resolving it quickly is highly important. However, anomalous VMM detection is a challenge in the cloud environment since the user does not have access to the VMM. This paper addresses this challenge of anomalous VMM detection in the cloud-based environment without having any knowledge or data from VMM by introducing a novel machine learning-based algorithm called IAD: Indirect Anomalous VMMs Detection. This algorithm solely uses the VM's resources utilization data hosted on those VMMs for the anomalous VMMs detection. The developed algorithm's accuracy was tested on four datasets comprising the synthetic and real and compared against four other popular algorithms, which can also be used to the described problem. It was found that the proposed IAD algorithm has an average F1-score of 83.7 also outperforms other algorithms by an average F1-score of 11%.


page 1

page 2

page 3

page 4


Online Memory Leak Detection in the Cloud-based Infrastructures

A memory leak in an application deployed on the cloud can affect the ava...

Memory Leak Detection Algorithms in the Cloud-based Infrastructure

A memory leak in an application deployed on the cloud can affect the ava...

Clustering-based Anomaly Detection for microservices

Anomaly detection is an important step in the management and monitoring ...

Anomalous Sound Detection with Machine Learning: A Systematic Review

Anomalous sound detection (ASD) is the task of identifying whether the s...

On Machine Learning DoS Attack Identification from Cloud Computing Telemetry

The detection of Denial of Service (DoS) attacks remains a challenge for...

Learning State Machines to Monitor and Detect Anomalies on a Kubernetes Cluster

These days more companies are shifting towards using cloud environments ...

Exploring traditional machine learning for identification of pathological auscultations

Today, data collection has improved in various areas, and the medical do...

Please sign up or login with your details

Forgot password? Click here to reset