Server Staffing to Meet Time-Varying Demand
研究多服务器服务系统中，如何根据随时间变化的到达和服务过程，动态配置服务器数量，使延迟概率始终接近目标值，并基于时变正态分布提出近似方法。
We consider a multiserver service system with general nonstationary arrival and service-time processes in which s(t), the number of servers as a function of time, needs to be selected to meet projected loads. We try to choose s(t) so that the probability of a delay (before beginning service) hits or falls just below a target probability at all times. We develop an approximate procedure based on a time-dependent normal distribution, where the mean and variance are determined by infinite-server approximations. We demonstrate that this approximation is effective by making comparisons with the exact numerical solution of the Markovian M t /M/s t model.