What This Document Is
This is a comprehensive survey exploring the complexities of performance modeling and analysis within resource management, specifically focusing on virtualized environments and enterprise cloud computing. It delves into the unique challenges presented by virtualization technologies – like hypervisors – and how traditional performance analysis methods need to adapt. The document provides a high-level overview of current research and approaches in this rapidly evolving field.
Why This Document Matters
This resource is invaluable for students and professionals in computer systems analysis, cloud computing, and virtualization. It’s particularly relevant for those seeking to understand the intricacies of optimizing performance in virtualized infrastructures. Individuals involved in system design, performance engineering, or cloud architecture will find this survey a useful starting point for deeper investigation. It’s ideal for those needing a broad understanding of the landscape before tackling specific implementation or research projects.
Common Limitations or Challenges
This survey offers a broad overview of the field and does *not* provide detailed, step-by-step instructions for implementing specific modeling techniques. It doesn’t offer code examples, practical case studies with specific configurations, or a comparative analysis of commercial tools. The document focuses on presenting the *issues* and *approaches* rather than providing definitive solutions or a “how-to” guide. It assumes a foundational understanding of computer systems and virtualization concepts.
What This Document Provides
* An overview of virtualization concepts and terminology, including a discussion of x86-based hypervisors.
* An exploration of the unique challenges to performance analysis introduced by virtualized environments.
* A survey of existing virtualization measurement tools and benchmarks.
* An examination of various modeling and simulation methodologies applicable to virtualized systems, including techniques like Linear Parameter Varying and Artificial Neural Networks.
* A comprehensive list of references for further research.
* A glossary of acronyms commonly used in the field of virtualization and cloud computing.
