The proliferation of smart devices, computational and storage resources is predicted to continue aggressively in the near future. Such “networked” devices and resources which are distributed in a physical space and provide services are collectively referred to as a distributed service network. Assigning users or applications to available resources is important to sustain high performance of the distributed service network. In this work, we consider a one-dimensional service network where both users and resources are located on a line, and analyze a unidirectional assignment policy Move To Right (MTR), which sequentially assigns users to resources available to their right. We express the communication cost for a user-resource assignment as an increasing function of the distance traveled by the user request (request distance) and analyze the expected communication cost for the service network when locations of users and resources are modeled by different spatial point processes. We use results from the literature that map the request distance of an assigned user in a one-dimensional service network to the sojourn time of a customer in an exceptional service accessible batch queueing system. We compute the Laplace–Stieltjes transform of the sojourn time distribution for this queueing system for Poisson distributed users with general inter-resource distance distributions and in the process also generate new results for batch service queues. Unlike previous work (Panigrahy et al. in Perform Eval 142:102, 2020), our framework not only captures the first-order moment of the request distance, but also the request distance distribution itself, thus allowing us to compute the expected communication cost under different cost models.

预计在不久的将来，智能设备，计算和存储资源的激增将继续积极发展。分布在物理空间中并提供服务的此类“联网”设备和资源统称为分布式服务网络。为可用资源分配用户或应用程序对于维持分布式服务网络的高性能非常重要。在这项工作中，我们考虑用户和资源都位于一条线上的一维服务网络，并分析单向分配策略“向右移动”（MTR），该策略将用户依次分配给其可用的资源。我们将用户资源分配的通信成本表示为用户请求行进的距离（请求距离），并在通过不同的空间点过程对用户和资源的位置进行建模时分析服务网络的预期通信成本。我们使用来自文献的结果，这些结果将一维服务网络中指定用户的请求距离映射到特殊服务可访问批处理排队系统中客户的停留时间。对于具有一般资源间距离分布的Poisson分布式用户，我们为该排队系统计算了停留时间分布的Laplace–Stieltjes变换，并且在此过程中还为批处理服务队列生成了新结果。与以前的工作不同（Panigrahy等人在2020年的Perform Eval 142：102中），我们的框架不仅捕获了请求距离的一阶矩，而且还捕获了请求距离分布 本身，从而使我们能够计算不同成本模型下的预期通信成本。