scholarly journals Stability of the stochastic matching model

2016 ◽  
Vol 53 (4) ◽  
pp. 1064-1077 ◽  
Author(s):  
Jean Mairesse ◽  
Pascal Moyal
Keyword(s):  
Markov Chain ◽  
Matching Model ◽  
New Model ◽  
Buffer Content ◽  
Finite Set ◽  
Matching Graph ◽  
Stochastic Matching ◽  
Independent And Identically Distributed

Abstract We introduce and study a new model that we call the matching model. Items arrive one by one in a buffer and depart from it as soon as possible but by pairs. The items of a departing pair are said to be matched. There is a finite set of classes 𝒱 for the items, and the allowed matchings depend on the classes, according to a matching graph on 𝒱. Upon arrival, an item may find several possible matches in the buffer. This indeterminacy is resolved by a matching policy. When the sequence of classes of the arriving items is independent and identically distributed, the sequence of buffer-content is a Markov chain, whose stability is investigated. In particular, we prove that the model may be stable if and only if the matching graph is nonbipartite.

scholarly journals A product form for the general stochastic matching model

2021 ◽  
Vol 58 (2) ◽  
pp. 449-468
Author(s):  
Pascal Moyal ◽  
Ana Bušić ◽  
Jean Mairesse
Keyword(s):  
Stationary Distribution ◽  
Product Form ◽  
Necessary Condition ◽  
Matching Model ◽  
Bipartite Matching ◽  
Compatibility Graph ◽  
Stochastic Matching ◽  
Dynamic Reversibility ◽  
Original Dynamic ◽  
Do So

AbstractWe consider a stochastic matching model with a general compatibility graph, as introduced by Mairesse and Moyal (2016). We show that the natural necessary condition of stability of the system is also sufficient for the natural ‘first-come, first-matched’ matching policy. To do so, we derive the stationary distribution under a remarkable product form, by using an original dynamic reversibility property related to that of Adan, Bušić, Mairesse, and Weiss (2018) for the bipartite matching model.

Infinite dams with inputs forming a Markov chain

1968 ◽  
Vol 5 (1) ◽  
pp. 72-83 ◽  
Author(s):  
M. S. Ali Khan ◽  
J. Gani
Keyword(s):  
Markov Chain ◽  
Storage Systems ◽  
Random Variables ◽  
Time Intervals ◽  
Storage Theory ◽  
Annual Time ◽  
Theory Of Storage ◽  
Independent And Identically Distributed

Moran's [1] early investigations into the theory of storage systems began in 1954 with a paper on finite dams; the inputs flowing into these during consecutive annual time-intervals were assumed to form a sequence of independent and identically distributed random variables. Until 1963, storage theory concentrated essentially on an examination of dams, both finite and infinite, fed by inputs (discrete or continuous) which were additive. For reviews of the literature in this field up to 1963, the reader is referred to Gani [2] and Prabhu [3].

scholarly journals A general stochastic matching model on multigraphs

2021 ◽  
Vol 18 (1) ◽  
pp. 1325
Author(s):  
Jocelyn Begeot ◽  
Irène Marcovici ◽  
Pascal Moyal ◽  
Youssef Rahme
Keyword(s):  
Matching Model ◽  
Stochastic Matching ◽  
General Stochastic

scholarly journals Random semigroup acts on a finite set

1977 ◽  
Vol 23 (4) ◽  
pp. 481-498 ◽  
Author(s):  
Göran Högnäs
Keyword(s):  
Markov Chain ◽  
Random Walk ◽  
Finite Set ◽  
Semigroup Of Transformations

AbstractLet X be a finite set and S a semigroup of transformations of X. We investigate the trace on X of a random walk on S. We relate the structure of the trace process, which turns out to be a Markov chain, to that of the random walk. We show, for example, that all periods of the trace process divide the period of the random walk.

Matrix product-form solutions for Markov chains with a tree structure

1994 ◽  
Vol 26 (04) ◽  
pp. 965-987 ◽  
Author(s):  
Raymond W. Yeung ◽  
Bhaskar Sengupta
Keyword(s):  
Markov Chain ◽  
Markov Chains ◽  
Closed Form Solution ◽  
Steady State Solution ◽  
Form Solution ◽  
Product Form ◽  
Matrix Product ◽  
Preemptive Resume ◽  
Finite Set ◽  
Markov Modulated

We have two aims in this paper. First, we generalize the well-known theory of matrix-geometric methods of Neuts to more complicated Markov chains. Second, we use the theory to solve a last-come-first-served queue with a generalized preemptive resume (LCFS-GPR) discipline. The structure of the Markov chain considered in this paper is one in which one of the variables can take values in a countable set, which is arranged in the form of a tree. The other variable takes values from a finite set. Each node of the tree can branch out into d other nodes. The steady-state solution of this Markov chain has a matrix product-form, which can be expressed as a function of d matrices Rl,· ··, Rd. We then use this theory to solve a multiclass LCFS-GPR queue, in which the service times have PH-distributions and arrivals are according to the Markov modulated Poisson process. In this discipline, when a customer's service is preempted in phase j (due to a new arrival), the resumption of service at a later time could take place in a phase which depends on j. We also obtain a closed form solution for the stationary distribution of an LCFS-GPR queue when the arrivals are Poisson. This result generalizes the known result on a LCFS preemptive resume queue, which can be obtained from Kelly's symmetric queue.

scholarly journals Hitting Time and Inverse Problems for Markov Chains

2008 ◽  
Vol 45 (03) ◽  
pp. 640-649
Author(s):  
Victor de la Peña ◽  
Henryk Gzyl ◽  
Patrick McDonald
Keyword(s):  
Markov Chain ◽  
Inverse Problems ◽  
Markov Chains ◽  
Transition Probabilities ◽  
Hitting Time ◽  
First Hitting Time ◽  
Joint Distributions ◽  
Finite Set

Let W n be a simple Markov chain on the integers. Suppose that X n is a simple Markov chain on the integers whose transition probabilities coincide with those of W n off a finite set. We prove that there is an M > 0 such that the Markov chain W n and the joint distributions of the first hitting time and first hitting place of X n started at the origin for the sets {-M, M} and {-(M + 1), (M + 1)} algorithmically determine the transition probabilities of X n .

Infinite dams with inputs forming a Markov chain

1968 ◽  
Vol 5 (01) ◽  
pp. 72-83 ◽  
Author(s):  
M. S. Ali Khan ◽  
J. Gani
Keyword(s):  
Markov Chain ◽  
Storage Systems ◽  
Random Variables ◽  
Time Intervals ◽  
Storage Theory ◽  
Annual Time ◽  
Theory Of Storage ◽  
Independent And Identically Distributed

Moran's [1] early investigations into the theory of storage systems began in 1954 with a paper on finite dams; the inputs flowing into these during consecutive annual time-intervals were assumed to form a sequence of independent and identically distributed random variables. Until 1963, storage theory concentrated essentially on an examination of dams, both finite and infinite, fed by inputs (discrete or continuous) which were additive. For reviews of the literature in this field up to 1963, the reader is referred to Gani [2] and Prabhu [3].

Distribution of the Time of the First k-Record

1997 ◽  
Vol 11 (3) ◽  
pp. 273-278 ◽  
Author(s):  
Ilan Adler ◽  
Sheldon M. Ross
Keyword(s):  
Generating Function ◽  
Random Variables ◽  
Recursive Formula ◽  
Finite Set ◽  
Independent And Identically Distributed

We compute the first two moments and give a recursive formula for the generating function of the first k-record index for a sequence of independent and identically distributed random variables that take on a finite set of possible values. When the random variables have an infinite support, we bound the distribution of the index of the first k-record and show that its mean is infinite.

scholarly journals First Occurrence in Pairs of Long Words: A Penney-ante Conjecture of Pevzner

1995 ◽  
Vol 4 (3) ◽  
pp. 279-285
Author(s):  
Dudley Stark
Keyword(s):  
Probability Distribution ◽  
Unique Element ◽  
Secondary Maximum ◽  
Maximum Value ◽  
Random Elements ◽  
Finite Set ◽  
First Occurrence ◽  
Independent And Identically Distributed

Suppose X1, X2,… is a sequence of independent and identically distributed random elements whose values are taken in a finite set S of size |S| ≥ 2 with probability distribution ℙ(X = s) = p(s) > 0 for s ∈ S. Pevzner has conjectured that for every probability distribution ℙ there exists an N > 0 such that for every word A with letters in S whose length is at least N, there exists a second word B of the same length as A, such that the event that B appears before A in the sequence X1, X2,… has greater probability than that of A appearing before B. In this paper it is shown that a distribution ℙ satisfies Pevzner's conclusion if and only if the maximum value of ℙ, p, and the secondary maximum c satisfy the inequality . For |S| = 2 or |S| = 3, the inequality is true and the conjecture holds. If , then the conjecture is true when A is not allowed to consist of pure repetitions of that unique element for which the distribution takes on its mode.

Large deviations for a Markov chain in a random landscape

2002 ◽  
Vol 34 (2) ◽  
pp. 375-393 ◽  
Author(s):  
Nadine Guillotin-Plantard
Keyword(s):  
Markov Chain ◽  
Large Deviations ◽  
State Space ◽  
Random Vectors ◽  
Independent And Identically Distributed

Let (Sk)k≥0 be a Markov chain with state space E and (ξx)x∊E be a family of ℝp-valued random vectors assumed independent of the Markov chain. The ξx could be assumed independent and identically distributed or could be Gaussian with reasonable correlations. We study the large deviations of the sum

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