In many systems, servers do not turn on instantly; instead, a setup time must pass before a server can begin work. These "setup times" can wreak havoc on a system's queueing; this is especially true in modern systems, where servers are regularly turned on and off as a way to reduce operating costs (energy, labor, CO2, etc.). To design modern systems which are both efficient and performant, we need to understand how setup times affect queues. Unfortunately, despite successes in understanding setup in a single-server system, setup in a multiserver system remains poorly understood. To circumvent the main difficulty in analyzing multiserver setup, all existing results assume that setup times are memoryless, i.e. distributed Exponentially. However, in most practical settings, setup times are close to Deterministic, and the widely used Exponential-setup assumption leads to unrealistic model behavior and a dramatic underestimation of the true harm caused by setup times. This paper provides a comprehensive characterization of the average waiting time in a multiserver system with Deterministic setup times, the M/M/k/Setup-Deterministic. In particular, we derive upper and lower bounds on the average waiting time in this system, and show these bounds are within a multiplicative constant of each other. These bounds are the first closed-form characterization of waiting time in any finite-server system with setup times. Further, we demonstrate how to combine our upper and lower bounds to derive a simple and accurate approximation for the average waiting time. These results are all made possible via a new technique for analyzing random time integrals that we named the Method of Intervening Stopping Times, or MIST.
翻译:在许多系统中,服务器并非即时启动;在服务器开始工作前必须经历一段启动时间。这些“启动时间”可能严重扰乱系统的排队行为,这在现代系统中尤为突出,因为服务器常通过频繁启停来降低运营成本(如能源、人力、二氧化碳排放等)。为设计既高效又性能优异的现代系统,我们需要理解启动时间如何影响队列。遗憾的是,尽管单服务器系统的启动机制已得到较好理解,多服务器系统的启动机制仍缺乏深入研究。为规避多服务器启动分析的主要困难,现有研究均假设启动时间是无记忆的,即服从指数分布。然而,在多数实际场景中,启动时间接近确定性分布,广泛采用的指数启动假设会导致模型行为失真,并严重低估启动时间造成的实际危害。本文全面刻画了具有确定性启动时间的多服务器系统(M/M/k/Setup-Deterministic)中的平均等待时间特性。具体而言,我们推导了该系统平均等待时间的上界与下界,并证明这些界在乘法常数范围内相互接近。这些界是首个针对带启动时间的有限服务器系统等待时间的闭式表征。进一步,我们展示了如何结合上下界推导出简洁而精确的平均等待时间近似表达式。这些成果均通过一种分析随机时间积分的新技术实现,我们将其命名为“干预停时方法”(Method of Intervening Stopping Times, MIST)。