EUROPEAN CONFERENCE ON QUEUEING THEORY 2016

International audienceThis booklet contains the proceedings of the second European Conference in Queueing Theory (ECQT) that was held from the 18th to the 20th of July 2016 at the engineering school ENSEEIHT, Toulouse, France. ECQT is a biannual event where scientists and technicians in queueing theory and related areas get together to promote research, encourage interaction and exchange ideas. The spirit of the conference is to be a queueing event organized from within Europe, but open to participants from all over the world. The technical program of the 2016 edition consisted of 112 presentations organized in 29 sessions covering all trends in queueing theory, including the development of the theory, methodology advances, computational aspects and applications. Another exciting feature of ECQT2016 was the institution of the Takács Award for outstanding PhD thesis on "Queueing Theory and its Applications"

Lindley-type recursions

In dit proefschrift staat de volgende Lindley-achtige recursie centraal: Wn+1 = max{0,Bn+1 - An -Wn}. (1) Deze "niet-stijgende" recursie is belangrijk in de analyse van systemen waarbij een bediende alterneert tussen twee bedieningsstations. Een station biedt ruimte voor ´e´en klant. De bediende alterneert tussen beide stations en bediend ´e´en klant per keer. Aangenomen wordt dat voortdurend bij beide stations klanten staan te wachten. Zodra een wachtende klant een station betreed, begint de eerste fase van zijn bediening, die bestaat uit een voorbereidende fase. De bediende is hier niet bij betrokken: pas nadat de voorbereidende fase is afgerond kan een klant aan de tweede fase van zijn bediening beginnen, welke wordt uitgevoerd door de bediende. Dus de eigenlijke bediening bestaat alleen uit de tweede fase. Het kan voorkomen dat de bediende moet wachten totdat de voorbereiding van de volgende klant is afgelopen. We zijn dan ook ge¨interesseerd in de wachttijd van de bediende. Als Bn de voorbereidingstijd is voor de n-de klant en An de bedieningstijd is van de n-de klant, dan kan de wachttijd van de bediende voor de (n + 1)-ste klant beschreven worden door middel van Recursie (1). Een belangrijke observatie is dat deze recursie vrijwel identiek is aan Lindley’s recursie. Het enige verschil is het min-teken voor Wn. Dit model is gemotiveerd door diverse toepassingen waarvan er twee worden besproken in Hoofdstuk 1. De eerste toepassing betreft oog-operaties. De tweede toepassing is gerelateerd aan carousel systemen. Dit soort systemen zijn uitgebreid bestudeerd; Sectie 1.3 geeft een literatuuroverzicht. Verderop in dit hoofdstuk geven we een gedetailleerde modelbeschrijving en noemen we enkele verschillen tussen de analyse van dit model en het standaard wachtrijmodel. Hoofdstuk 2 bestudeert enkele algemene eigenschappen van Recursie (1), zoals de stabiliteit van het systeem, existentie van een evenwichtsverdeling, convergentie naar deze verdeling als n naar oneindig gaat en het staartgedrag en de covariantie functie van de verdeling van de wachttijd van de bediende. Een rode draad in dit proefschrift is de afleiding van de evenwichtsverdeling van de wachttijd van de bediende. In de volgende drie hoofdstukken leiden we deze verdeling af onder diverse aannames over de verdeling van de voorbereidingstijd en bedieningstijd van een generieke klant. We bestuderen gevallen die analoog zijn aan de klassieke M/G/1, G/PH/1 en PH/P/1 wachtrijmodellen, waarbij "P" staat voor polynomiale verdelingen. Ge¨inspireerd door de toepassingen van ons model, bekijken we enkele prestatiematen voor dit systeem, zoals de doorzet. Dit maakt een vergelijk met de prestatie van niet-alternerende systemen mogelijk. In Hoofdstuk 6 onderzoeken we methoden om de wachttijdverdeling te benaderen door de verdeling van de voorbereidingstijd of bedieningstijd te benaderen met een verdeling die exacte berekeningen mogelijk maakt. We beschrijven hoe zo’n verdel- ing kan worden gevonden en we geven een bovengrens voor de fout tussen de werkelijke wachttijdverdeling en zijn benadering. In alle voorgaande hoofdstukken hebben we aangenomen dat alle voorbereidingstijden en bedieningstijden onafhankelijk van elkaar zijn. In Hoofdstuk 7 laten we deze aanname vallen. We onderzoeken twee specifieke vormen van afhankelijkheid tussen deze variabelen. Voor beide vormen leiden we opnieuw de limietverdeling af van de wachttijd van de bediende. Hoofdstuk 8 analyseert een recursie welke een uitbreiding is van zowel Lindley’s recursie als (1). We bekijken, namelijk, de recursie Wn+1 = max{0,Bn+1 - An + YnWn}, met Yn een stochastische variabele die zowel de waarde 1 als -1 kan aannemen. Voor deze recursie onderzoeken we stabiliteit, en we berekenen de limietverdeling in twee specifieke gevallen, waarmee we de bestaande theorie voor Lindley’s recursie en Recursie (1) generaliseren. De analyse maakt duidelijk dat de technieken voor het analyseren van (1) en voor het analyseren Lindley’s recursie moeten worden gecombineerd. Diverse methoden om Lindley’s recursie te analyseren zijn ook nuttig voor de analyse van (1). Wanneer we aannemen dat de voorbereidingstijd een fase-type verdeling heeft, dan reduceert de analyse van (1) tot de analyse van een Markovketen met eindige toestandsruimte. Ook kunnen Laplace-transformaties of Wiener- Hopf technieken in diverse gevallen worden toegepast (cf. Sectie 1.6). In andere gevallen moet een niet-standaard differentiaalvergelijking worden opgelost, of moet uitgeweken worden naar een iteratieve benadering van de wachttijdverdeling. In Hoofdstuk 5 dient ook een speciale klasse van verdelingen ge¨introduceerd te worden die het mogelijk maakt om een Fredholm vergelijking op te lossen. In de meeste gevallen zijn de resultaten expliciet of kunnen worden weergegeven in termen van de oplossing van een lineair stelsel vergelijkingen, zie bijvoorbeeld Stelling 4.8. Het proefschrift wordt afgesloten met enkele afsluitende opmerkingen en diverse suggesties voor verder onderzoek

Resource management of replicated service systems provisioned in the cloud

Service providers seek scalable and cost-effective cloud solutions for hosting their applications. Despite significant recent advances facilitating the deployment and management of services on cloud platforms, a number of challenges still remain. Service providers are confronted with time-varying requests for the provided applications, inter- dependencies between different components, performance variability of the procured virtual resources, and cost structures that differ from conventional data centers. Moreover, fulfilling service level agreements, such as the throughput and response time percentiles, becomes of paramount importance for ensuring business advantages.In this thesis, we explore service provisioning in clouds from multiple points of view. The aim is to best provide service replicas in the form of VMs to various service applications, such that their tail throughput and tail response times, as well as resource utilization, meet the service level agreements in the most cost effective manner. In particular, we develop models, algorithms and replication strategies that consider multi-tier composed services provisioned in clouds. We also investigate how a service provider can opportunistically take advantage of observed performance variability in the cloud. Finally, we provide means of guaranteeing tail throughput and response times in the face of performance variability of VMs, using Markov chain modeling and large deviation theory. We employ methods from analytical modeling, event-driven simulations and experiments. Overall, this thesis provides not only a multi-faceted approach to exploring several crucial aspects of hosting services in clouds, i.e., cost, tail throughput, and tail response times, but our proposed resource management strategies are also rigorously validated via trace-driven simulation and extensive experiment

Many-Server Queues with Time-Varying Arrivals, Customer Abandonment, and non-Exponential Distributions

This thesis develops deterministic heavy-traffic fluid approximations for many-server stochastic queueing models. The queueing models, with many homogeneous servers working independently in parallel, are intended to model large-scale service systems such as call centers and health care systems. Such models also have been employed to study communication, computing and manufacturing systems. The heavy-traffic approximations yield relatively simple formulas for quantities describing system performance, such as the expected number of customers waiting in the queue. The new performance approximations are valuable because, in the generality considered, these complex systems are not amenable to exact mathematical analysis. Since the approximate performance measures can be computed quite rapidly, they usefully complement more cumbersome computer simulation. Thus these heavy-traffic approximations can be used to improve capacity planning and operational control. More specifically, the heavy-traffic approximations here are for large-scale service systems, having many servers and a high arrival rate. The main focus is on systems that have time-varying arrival rates and staffing functions. The system is considered under the assumption that there are alternating periods of overloading and underloading, which commonly occurs when service providers are unable to adjust the staffing frequently enough to economically meet demand at all times. The models also allow the realistic features of customer abandonment and non-exponential probability distributions for the service times and the times customers are willing to wait before abandoning. These features make the overall stochastic model non-Markovian and thus thus very difficult to analyze directly. This thesis provides effective algorithms to compute approximate performance descriptions for these complex systems. These algorithms are based on ordinary differential equations and fixed point equations associated with contraction operators. Simulation experiments are conducted to verify that the approximations are effective. This thesis consists of four pieces of work, each presented in one chapter. The first chapter (Chapter 2) develops the basic fluid approximation for a non-Markovian many-server queue with time-varying arrival rate and staffing. The second chapter (Chapter 3) extends the fluid approximation to systems with complex network structure and Markovian routing to other queues of customers after completing service from each queue. The extension to open networks of queues has important applications. For one example, in hospitals, patients usually move among different units such as emergency rooms, operating rooms, and intensive care units. For another example, in manufacturing systems, individual products visit different work stations one or more times. The open network fluid model has multiple queues each of which has a time-varying arrival rate and staffing function. The third chapter (Chapter 4) studies the large-time asymptotic dynamics of a single fluid queue. When the model parameters are constant, convergence to the steady state as time evolves is established. When the arrival rates are periodic functions, such as in service systems with daily or seasonal cycles, the existence of a periodic steady state and the convergence to that periodic steady state as time evolves are established. Conditions are provided under which this convergence is exponentially fast. The fourth chapter (Chapter 5) uses a fluid approximation to gain insight into nearly periodic behavior seen in overloaded stationary many-server queues with customer abandonment and nearly deterministic service times. Deterministic service times are of applied interest because computer-generated service times, such as automated messages, may well be deterministic, and computer-generated service is becoming more prevalent. With deterministic service times, if all the servers remain busy for a long interval of time, then the times customers enter service assumes a periodic behavior throughout that interval. In overloaded large-scale systems, these intervals tend to persist for a long time, producing nearly periodic behavior. To gain insight, a heavy-traffic limit theorem is established showing that the fluid model arises as the many-server heavy-traffic limit of a sequence of appropriately scaled queueing models, all having these deterministic service times. Simulation experiments confirm that the transient behavior of the limiting fluid model provides a useful description of the transient performance of the queueing system. However, unlike the asymptotic loss of memory results in the previous chapter for service times with densities, the stationary fluid model with deterministic service times does not approach steady state as time evolves independent of the initial conditions. Since the queueing model with deterministic service times approaches a proper steady state as time evolves, this model with deterministic service times provides an example where the limit interchange (limiting steady state as time evolves and heavy traffic as scale increases) is not valid

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others

Energy-Efficient Algorithms and Access Schemes for Small Cell Networks

Dense deployment of small base stations (SBSs) brings new challenges such as growing energy consumption, increased carbon footprint, higher inter-cell interference, and complications in handover management. These challenges can be dealt with by taking advantage of sleep/idle mode capabilities of SBSs, and exploiting the delay tolerance of data applications, as well as utilizing information derived from the statistical distributions of SBSs and user equipment (UE)-SBS associations. This dissertation focuses on the formulation of mathematical models and proposes energy efficient algorithms for small cell networks (SCN). It is shown that delay tolerance of some data applications can be taken advantage of to save energy in SCN. This dissertation introduces practical models to study the performance of delayed access to SCNs. Operational states of SBS are modeled as a Markov chain and their probability distributions are analyzed. Also, it argues that SCN can be operated to save energy during low traffic periods by taking advantage of user equipments' (UEs) delay tolerance in SCN while providing high access probability within bounded transmission range. Dense deployment of SCNs cause an increase in overlapping SBS coverage areas, allowing UEs to establish communication with multiple SBSs. A new load metric as a function of the number of SBSs in UE's communication range is defined, and its statistics are rigorously analyzed. Energy saving algorithms based on aforementioned load metric are developed and their efficiencies are compared. Besides, UE's delay tolerance allows establishing communication with close-by SBSs that are either in fully active mode or in sleeping mode. Improvements in coverage probability and bitrate are analyzed by considering different delay tolerance values for UEs. Key parameters such as UE's communication range are optimized with respect to SBS density and delay tolerance. The fundamental problem of local versus remote edge/fog computing and its inherent tradeoffs are studied from a queuing perspective taking into account user/SBS density, server capacity and latency constraints. The task offloading problem is cast as an M/M/1(c) queue in which CPU intensive tasks arrive according to Poisson process and receive service subject to a tolerable delay. The higher the proportion of locally computed tasks, the less traffic SCN handles between edge processor and UE. Therefore, low utilization of SCN can be interperted as increased spectral efficiency due to low interference and close UE-SBS distance. Tradeoff between delay dependent SCN utilization and spectral efficiency is evaluated at high and low traffic loads