A Novel architecture for improving performance under virtualized environments

TL;DR

This paper proposes a novel architecture utilizing a Fast Genetic K-means++ algorithm to enhance performance isolation and resource management in virtualized cloud environments, demonstrating significant improvements over existing methods.

Contribution

The paper introduces a new architecture that applies a Fast Genetic K-means++ algorithm for better resource allocation and performance in virtualized systems.

Findings

Performance improvements over existing approaches

Effective resource management in virtual environments

Positive test results demonstrating architecture benefits

Abstract

Even though virtualization provides a lot of advantages in cloud computing, it does not provide effective performance isolation between the virtualization machines. In other words, the performance may get affected due the interferences caused by co-virtual machines. This can be achieved by the proper management of resource allocations between the Virtual Machines running simultaneously. This paper aims at providing a proposed novel architecture that is based on Fast Genetic K-means++ algorithm and test results show positive improvements in terms of performance improvements over a similar existing approach.