Tandem stochastic systems: Jackson networks, asymmetric exclusion processes, asymmetric inclusion processes and Catalan numbers

U. Yechiali
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Abstract

A tandem stochastic system is a network of n sites (queues) in series, where particles (customers, jobs, packets, etc.) move unidirectionally from one site to the next until they leave the system. When each site is an M/M/1 queue, i.e., where the buffer size of each site is unlimited and only single particles move between sites, the system is known as Tandem Jackson Network (TJN) [3]. The TJN is famous for its product-form solution of the multi-dimensional distribution function of the sites' queue-sizes (occupancies). Another well-known tandem stochastic system is the Asymmetric Simple Exclusion Process (ASEP) [1], where each site can hold at most a single particle, a constraint that causes blockings on particles' forward movements. The ASEP is a paradigmatic model in non-equilibrium statistical mechanics. In contrast, the newly introduced (Reuveni, Eliazar and Yechiali) Asymmetric Inclusion Process (ASIP) is a tandem series of sites, each with unbounded buffer capacity and with unlimited-size batch service [5]. That is, when service is completed at site k, all particles present there move simultaneously to site k + 1 and form a cluster together with the cluster of particles (if any) already residing in site k + 1. The ASIP is a showcase of complexity [6]. We analyze the innovative ASIP and show that its multi-dimensional Probability Generating Function (PGF) does not admit a product-form solution. Nevertheless, we present a method to calculate this PGF [5]. Surprisingly though, the load (total number of particles up to site k) does admit a product-form solution. It is consequently shown that homogeneous systems (i.e. systems with identical servers) are optimal for various load-related objective functions [5]. Considering the total number of particles in a site-interval of length m (m = 1, 2,..., n) that starts at site k, the corresponding probability generating functions create a discrete two-dimensional boundary-value problem which is solved explicitly [8]. Catalan's numbers, and their generalizations, arise naturally in this context [4]. It is further proved [8] that the probability of site k being positively occupied is proportional to 1/√k, while the variance in the occupancy of site k is proportional to √k. Finally, we derive limit laws (when the number of sites becomes large) for various system's variables [7]. In particular, we show that the 'load', as well as the 'draining time', each obeys a Gaussian distribution (with corresponding coefficients), while the 'inter-exit time' follows a Rayleigh distribution. An extension of the basic ASIP model with a fairly general arrival scheme, where gate opening intervals follow a Markov renewal process, is studied in [2]. The steady-state distribution of the total number of customers in the first k queues is determined.
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串联随机系统:Jackson网络,不对称排斥过程,不对称包含过程和加泰罗尼亚数
串联随机系统是一个由n个站点(队列)串联组成的网络,其中粒子(客户、作业、数据包等)单向地从一个站点移动到下一个站点,直到它们离开系统。当每个站点为M/M/1队列时,即每个站点的缓冲区大小是无限的,并且只有单个粒子在站点之间移动,该系统称为串联杰克逊网络(Tandem Jackson Network, TJN)[3]。TJN以其对场地排队大小(入住率)的多维分布函数的产品形式解决方案而闻名。另一个著名的串联随机系统是不对称简单排斥过程(ASEP)[1],其中每个位点最多可以容纳一个粒子,这是一个限制,导致粒子向前运动受阻。ASEP是非平衡统计力学中的一个典型模型。相比之下,新引入的(Reuveni, Eliazar和yechhiali)不对称包含过程(ASIP)是一系列串联的位点,每个位点具有无限大的缓冲容量和无限大的批处理服务[5]。也就是说,当在站点k完成服务时,所有存在于站点k + 1的粒子同时移动到站点k + 1,并与已经驻留在站点k + 1的粒子簇(如果有的话)一起形成一个簇。ASIP是复杂性的展示[6]。我们分析了创新的ASIP,并证明了它的多维概率生成函数(PGF)不承认乘积形式的解。然而,我们提出了一种计算PGF的方法[5]。然而,令人惊讶的是,载荷(到k点的粒子总数)确实允许产品形式的解决方案。结果表明,同构系统(即具有相同服务器的系统)对于各种与负载相关的目标函数是最优的[5]。考虑长度为m (m = 1,2,…)的位置区间内粒子总数。, n),对应的概率生成函数产生一个离散的二维边值问题,该问题显式求解[8]。加泰罗尼亚的数字,以及它们的概括,在这种背景下自然产生[4]。进一步证明[8],站点k被正占用的概率与1/√k成正比,而站点k占用的方差与√k成正比。最后,我们推导了各种系统变量的极限定律(当站点数量变大时)[7]。特别是,我们表明,“负荷”和“排水时间”都服从高斯分布(具有相应的系数),而“出口间时间”遵循瑞利分布。[2]研究了基本ASIP模型的扩展,采用相当一般的到达方案,其中闸门打开间隔遵循马尔可夫更新过程。确定了前k个队列中客户总数的稳态分布。
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Revenue-Driven Scheduling in Drone Delivery Networks with Time-sensitive Service Level Agreements A proof of the conjecture in "Pricing surplus server capacity for mean waiting time sensitive customers" Tandem stochastic systems: Jackson networks, asymmetric exclusion processes, asymmetric inclusion processes and Catalan numbers Ultimately Stationary Policies to Approximate Risk-Sensitive Discounted MDPs A bottleneck with randomly distorted arrival times
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