scispace - formally typeset
Search or ask a question
Author

Ohad Perry

Other affiliations: Columbia University
Bio: Ohad Perry is an academic researcher from Northwestern University. The author has contributed to research in topics: Queue & Fluid limit. The author has an hindex of 10, co-authored 35 publications receiving 312 citations. Previous affiliations of Ohad Perry include Columbia University.

Papers
More filters
Journal ArticleDOI
TL;DR: The simulations show that the proposed queue-ratio control with thresholds outperforms the optimal fixed partition of the servers given known fixed arrival rates during the overload, even though the proposed control does not use information about the arrival rates.
Abstract: We consider how two networked large-scale service systems that normally operate separately, such as call centers, can help each other when one encounters an unexpected overload and is unable to immediately increase its own staffing. Our proposed control activates serving some customers from the other system when a ratio of the two queue lengths (numbers of waiting customers) exceeds a threshold. Two thresholds, one for each direction of sharing, automatically detect the overload condition and prevent undesired sharing under normal loads. After a threshold has been exceeded, the control aims to keep the ratio of the two queue lengths at a specified value. To gain insight, we introduce an idealized stochastic model with two customer classes and two associated service pools containing large numbers of agents. To set the important queue-ratio parameters, we consider an approximating deterministic fluid model. We determine queue-ratio parameters that minimize convex costs for this fluid model. We perform simulation experiments to show that the control is effective for the original stochastic model. Indeed, the simulations show that the proposed queue-ratio control with thresholds outperforms the optimal fixed partition of the servers given known fixed arrival rates during the overload, even though the proposed control does not use information about the arrival rates.

50 citations

Journal ArticleDOI
TL;DR: In this article, it was shown that there always exists a matching policy that is strictly smaller than the set of arrival intensities satisfying NCOND, which is not the case in general.
Abstract: A matching queue is described via a graph, an arrival process and a matching policy. Specifically, to each node in the graph there is a corresponding arrival process of items, which can either be queued or matched with queued items in neighboring nodes. The matching policy specifies how items are matched whenever more than one matching is possible. Given the matching graph and the matching policy, the stability region of the system is the set of intensities of the arrival processes rendering the underlying Markov process positive recurrent. In a recent paper, a condition on the arrival intensities, which was named NCOND, was shown to be necessary for the stability of a matching queue. That condition can be thought of as an analogue to the usual traffic condition for traditional queueing networks, and it is thus natural to study whether it is also sufficient. In this paper, we show that this is not the case in general. Specifically, we prove that, except for a particular class of graphs, there always exists a matching policy rendering the stability region strictly smaller than the set of arrival intensities satisfying NCOND. Our proof combines graph- and queueing-theoretic techniques: After showing explicitly, via fluid-limit arguments that the stability regions of two basic models is strictly included in NCOND, we generalize this result to any graph inducing either one of those two basic graphs.

41 citations

Journal ArticleDOI
TL;DR: The new fluid model developed here is an ordinary differential equation driven by the instantaneous steady- state probabilities of a fast-time-scale stochastic process, which provides the basis for an effective Gaussian approximation for the steady-state queue lengths.
Abstract: In a recent paper we considered two networked service systems, each having its own customers and designated service pool with many agents, where all agents are able to serve the other customers, although they may do so inefficiently. Usually the agents should serve only their own customers, but we want an automatic control that activates serving some of the other customers when an unexpected overload occurs. Assuming that the identity of the class that will experience the overload or the timing and extent of the overload are unknown, we proposed a queue-ratio control with thresholds: When a weighted difference of the queue lengths crosses a prespecified threshold, with the weight and the threshold depending on the class to be helped, serving the other customers is activated so that a certain queue ratio is maintained. We then developed a simple deterministic steady-state fluid approximation, based on flow balance, under which this control was shown to be optimal, and we showed how to calculate the control parameters. In this sequel we focus on the fluid approximation itself and describe its transient behavior, which depends on a heavy-traffic averaging principle. The new fluid model developed here is an ordinary differential equation driven by the instantaneous steady-state probabilities of a fast-time-scale stochastic process. The averaging principle also provides the basis for an effective Gaussian approximation for the steady-state queue lengths. Effectiveness of the approximations is confirmed by simulation experiments.

37 citations

Journal ArticleDOI
TL;DR: This work establishes approximations for overflow networks with many servers under a resource-pooling assumption that stipulates, in this context, that the fraction of overflowed calls is nonnegligible and shows that, as the system becomes large, the dependency between each in-house station and the overflow station becomes negligible.
Abstract: Motivated by call center cosourcing problems, we consider a service network operated under an overflow mechanism. Calls are first routed to an in-house (or dedicated) service station that has a finite waiting room. If the waiting room is full, the call is overflowed to an outside provider (an overflow station) that might also be serving overflows from other stations. We establish approximations for overflow networks with many servers under a resource-pooling assumption that stipulates, in our context, that the fraction of overflowed calls is nonnegligible. Our two main results are (i) an approximation for the overflow processes via limit theorems and (ii) asymptotic independence between each of the in-house stations and the overflow station. In particular, we show that, as the system becomes large, the dependency between each in-house station and the overflow station becomes negligible. Independence between stations in overflow networks is assumed in the literature on call centers, and we provide a rigorous support for those useful heuristics.

29 citations

Journal ArticleDOI
TL;DR: It is proved that it is possible to have almost all inbound calls answered immediately upon their arrival, in addition to satisfying a target long-run throughput rate of outbound calls, with at most a negligible proportion of those calls dropped.
Abstract: We consider large contact centers that handle two types of jobs-inbound and outbound-simultaneously, a process commonly referred to as call blending. Inbound work arrives to the system according to an exogenous arrival process, whereas outbound work is generated by the contact center. We assume that there is an infinite supply of outbound work to process, and that inbound calls are prioritized over the outbound calls. We propose a logarithmic safety staffing rule, combined with a threshold control policy, ensuring that agents' utilization is very close to one at all times, but that there are practically always idle agents present. Specifically, we prove that it is possible to have almost all inbound calls answered immediately upon their arrival, in addition to satisfying a target long-run throughput rate of outbound calls, with at most a negligible proportion of those calls dropped. Simulation experiments demonstrate the effectiveness and accuracy of our analysis. This paper was accepted by Assaf Zeevi, stochastic models and simulation.

26 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: Convergence of Probability Measures as mentioned in this paper is a well-known convergence of probability measures. But it does not consider the relationship between probability measures and the probability distribution of probabilities.
Abstract: Convergence of Probability Measures. By P. Billingsley. Chichester, Sussex, Wiley, 1968. xii, 253 p. 9 1/4“. 117s.

5,689 citations

Book ChapterDOI
01 Jan 2011
TL;DR: Weakconvergence methods in metric spaces were studied in this article, with applications sufficient to show their power and utility, and the results of the first three chapters are used in Chapter 4 to derive a variety of limit theorems for dependent sequences of random variables.
Abstract: The author's preface gives an outline: "This book is about weakconvergence methods in metric spaces, with applications sufficient to show their power and utility. The Introduction motivates the definitions and indicates how the theory will yield solutions to problems arising outside it. Chapter 1 sets out the basic general theorems, which are then specialized in Chapter 2 to the space C[0, l ] of continuous functions on the unit interval and in Chapter 3 to the space D [0, 1 ] of functions with discontinuities of the first kind. The results of the first three chapters are used in Chapter 4 to derive a variety of limit theorems for dependent sequences of random variables. " The book develops and expands on Donsker's 1951 and 1952 papers on the invariance principle and empirical distributions. The basic random variables remain real-valued although, of course, measures on C[0, l ] and D[0, l ] are vitally used. Within this framework, there are various possibilities for a different and apparently better treatment of the material. More of the general theory of weak convergence of probabilities on separable metric spaces would be useful. Metrizability of the convergence is not brought up until late in the Appendix. The close relation of the Prokhorov metric and a metric for convergence in probability is (hence) not mentioned (see V. Strassen, Ann. Math. Statist. 36 (1965), 423-439; the reviewer, ibid. 39 (1968), 1563-1572). This relation would illuminate and organize such results as Theorems 4.1, 4.2 and 4.4 which give isolated, ad hoc connections between weak convergence of measures and nearness in probability. In the middle of p. 16, it should be noted that C*(S) consists of signed measures which need only be finitely additive if 5 is not compact. On p. 239, where the author twice speaks of separable subsets having nonmeasurable cardinal, he means "discrete" rather than "separable." Theorem 1.4 is Ulam's theorem that a Borel probability on a complete separable metric space is tight. Theorem 1 of Appendix 3 weakens completeness to topological completeness. After mentioning that probabilities on the rationals are tight, the author says it is an

3,554 citations

Journal ArticleDOI
TL;DR: In this paper, applied probability and queuing in the field of applied probabilistic analysis is discussed. But the authors focus on the application of queueing in the context of road traffic.
Abstract: (1987). Applied Probability and Queues. Journal of the Operational Research Society: Vol. 38, No. 11, pp. 1095-1096.

1,121 citations