HCC: Evaluating the Performance of Distributed Synchronous Collaboration Architectures

最近出现了工业级同步协作系统的激增，然而，很少有研究比较它们的分布式体系结构的性能，尽管性能不足可能是一个令人惊叹的问题。在系统地研究这个建筑设计空间的过程中，这个项目将为目前的协作系统设计的“黑术”提供一个重要的基础。这将对研究和工业产生广泛的影响。体系结构设计空间将由影响性能的若干体系结构参数(例如，传输协议、服务器配置、I/O调度)、系统参数(例如，网络等待时间、处理能力)和任务参数(例如，I/O大小、思考时间)来建模。将根据体系结构、系统和任务参数，根据加入、离开、响应、反馈和任务完成等关键指标，开发出给出时间值的公式。将进行实验，以使用不同类型协作的日志来验证这些公式，例如多用户演示、聊天和科学可视化。这一新颖的实验试验台将实现以前无法进行的性能比较。更广泛的影响：这项研究产生的分析模型将允许应用程序和基础设施开发人员确定他们应该实现的体系结构的范围。它将使科学家、工程师、作家和其他协作技术用户更好地了解设计空间，以便他们可以选择适合自己需求的正确架构，同时了解选择的性能结果。此外，该项目的基础设施将形成第一个支持整个协作架构空间的概念验证系统，一个用于实验的新型研究试验台，以及一个用于教学协作架构的载体。为这些实验创建的多用户活动日志将被公布，以便它们可以成为学术和工业研究中的基准，用于比较新体系结构的性能。

There has been a recent proliferation of industrial-strength synchronous collaborative systems, however, there has been little research comparing the performance of their distributed architectures, even though inadequate performance can be a show-stopper. In systematically examining this architectural design space, this project will provide a critical foundation for what is currently the ''black art'' of collaborative system design. This will have broad ranging impact in both research and industry. The architecture design space will be modeled by several architecture parameters (e.g., transport protocol, server configuration, I/O scheduling), system parameters (e.g., network latency, processing power) and task parameters (e.g., I/O size, think time) that impact performance. Equations will be developed that give the value of the time, along key metrics such as join, leave, response, feedthrough, and task-completion, as a function of the architecture, system, and task parameters. Experiments will be performed to validate these equations using logs of different kinds of collaborations such as multi-user presentations, chats, and scientific visualizations. This novel experimental test bed will enable performance comparisons that have not been possible before. Broader impact: The analytic model resulting from this research will allow application and infrastructure developers to determine the range of architectures they should implement. It will provide scientists, engineers, writers, and other users of collaboration technology a better understanding of the design space so they can choose the correct architecture to fit their needs while appreciating the performance consequences of that choice. In addition, the project infrastructure will form the first proof-of-concept system supporting the entire space of collaborative architectures, a novel research test-bed for experimentation, and a vehicle for teaching collaboration architectures. The multi-user activity logs created for these experiments will be publicized so that they can become benchmarks, in both academic and industrial research, used to compare performance of new architectures.