Providing Virtual Execution Environments: A Twofold Illustration

TL;DR

This paper presents two open source projects, Tycoon and SmartDomains, demonstrating virtual execution environments for resource sharing, isolation, and flexible deployment in grid computing, with practical implementations at CERN openlab.

Contribution

It introduces two novel virtual resource management systems, one optimizing resource usage through an economic model and the other automating virtual machine deployment with a description language.

Findings

Tycoon enables resource optimization via bidding and economic principles.

SmartDomains automates VM deployment using a description language.

Both approaches demonstrate flexible, client-server and peer-to-peer virtual resource management.

Abstract

Platform virtualization helps solving major grid computing challenges: share resource with flexible, user-controlled and custom execution environments and in the meanwhile, isolate failures and malicious code. Grid resource management tools will evolve to embrace support for virtual resource. We present two open source projects that transparently supply virtual execution environments. Tycoon has been developed at HP Labs to optimise resource usage in creating an economy where users bid to access virtual machines and compete for CPU cycles. SmartDomains provides a peer-to-peer layer that automates virtual machines deployment using a description language and deployment engine from HP Labs. These projects demonstrate both client-server and peer-to-peer approaches to virtual resource management. The first case makes extensive use of virtual machines features for dynamic resource allocation. The second translates virtual machines capabilities into a sophisticated language where resource management components can be plugged in configurations and architectures defined at deployment time. We propose to share our experience at CERN openlab developing SmartDomains and deploying Tycoon to give an illustrative introduction to emerging research in virtual resource management.