Collaborative Research: QNATS - The Queueing Network Approximator for Time-Dependent Systems

这项NSF拨款将为具有时变输入参数、特征和协议的一般到达/服务过程排队网络的数值分析和近似的算法和支持理论的发展提供资金。其结果将是QNATS，即时间相关系统的排队网络近似器，这是NSF网络基础设施的一个补充，可供工程和科学界使用。QNATS将包括分析到达和服务机制随时间变化的系统，以及排队节点容量和服务器数量的设施。还将考虑从排队节点中作为时间函数的实体的确定性添加/删除。QNATS将允许基于时间的到达间隔时间和服务时间分布，而不是教科书模型中通常不切实际的基于时间的指数/泊松分布。QNATS模型易于构建，QNATS分析将能够足够快地提供结果，以便通过网络服务进行交互使用。排队模型是设计和改进制造业、服务业、数字电信和计算机系统性能的最广泛使用的技术之一。事实上，排队模型对于评估网络基础设施本身的附加功能的性能非常有用。实际上，在任何系统中，离散实体从一个或多个服务节点争夺资源都可以表示为队列网络。例如，时间依赖、无限服务器排队网络已经成为蜂窝通信系统分析的标准模型。其他的应用来自许多不同的领域，包括生物学中的人口过程、迁移/移民过程和流行病学。QNATS将允许许多领域的工程师和科学家避免当时变系统特性被忽略或用它们的时间平均值近似时可能发生的灾难性后果，从而导致对系统拥塞的严重低估。

This NSF grant will provide funding for the development of algorithms and supporting theory for numerical analysis and approximation of general arrival/service-process queueing networks having time-dependent input parameters, characteristics and protocols. The result will be QNATS, the Queueing Network Approximator for Time-Dependent Systems---an addition to the NSF Cyberinfrastructure of web-useable software that is available to the engineering and scientific community. QNATS will include the facility to analyze systems in which arrival and service mechanisms change with time, as well as queueing nodal capacity and the number of servers. Also considered will be deterministic additions/deletions of entities from queueing nodes as a function of time. QNATS will allow for time-dependent interarrival- and service-time distributions that are general in shape, rather than the often unrealistic time-dependent exponential/Poisson distributions of textbook models. QNATS models will be easy to build and QNATS analysis will be able to deliver results quickly enough to be used interactively via web services Queueing models are among the most widely used techniques to design and improve the performance of manufacturing, service-sector, digital-telecommunications and computer systems. In fact, queueing models are useful for assessing the performance of additions to the Cyberinfrastructure itself. Virtually any system in which discrete entities contend for resources from one or more service nodes can be represented as a network of queues. For example, time-dependent, infinite-server queueing networks have become a standard model for analysis of cellular telecommunication systems. Other applications come from a large variety of fields, including population processes in biology, migration/immigration processes, and epidemiology. QNATS will allow engineers and scientists in many fields to avoid the disastrous consequences that can occur when time-varying system characteristics are ignored or are approximated by their time-averaged values, leading to severe underestimation of system congestion.