What This Document Is
This instructional material provides a focused exploration of workload generators used in the context of distributed Web systems. It delves into the critical role these generators play in testing and ensuring the Quality of Service (QoS) of increasingly complex online platforms. The material is geared towards students and professionals seeking a deeper understanding of how to simulate realistic user activity for system evaluation. It originates from a course on Distributed Systems and Algorithms at West Virginia University.
Why This Document Matters
This resource is invaluable for anyone studying or working with distributed systems, web architecture, or performance testing. It’s particularly relevant when you need to understand how to rigorously test a system *before* deployment, or when analyzing potential bottlenecks and scalability issues. Students preparing for advanced coursework or research in these areas will find this a strong foundation. It’s also useful for system administrators and developers responsible for maintaining high-performing web applications.
Common Limitations or Challenges
This material concentrates specifically on the *types* and *characteristics* of workload generators. It does not offer a step-by-step guide to building a workload generator from scratch, nor does it provide code examples or detailed configuration instructions for specific tools. The focus is on conceptual understanding and comparative analysis, rather than practical implementation. It also acknowledges the evolving landscape of Web 2.0 and the current gaps in workload generation for modern social networking systems.
What This Document Provides
* A categorization of workload generators based on their underlying approach (existing traces vs. analytical models).
* An overview of the fundamental client-server architecture relevant to workload generation.
* A discussion of key characteristics to consider when emulating user behavior.
* A comparative review of several popular workload generators, highlighting their strengths and weaknesses.
* An examination of the trade-offs between emulating individual users and generating aggregate traffic.
* Insights into the challenges of testing Web 2.0 applications and social networking systems.
