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1999 | Buch

Sample-Path Analysis of Queueing Systems

verfasst von: Muhammad El-Taha, Shaler Stidham Jr.

Verlag: Springer US

Buchreihe : International Series in Operations Research & Management Science

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Über dieses Buch

Sample-Path Analysis of Queueing Systems uses a deterministic (sample-path) approach to analyze stochastic systems, primarily queueing systems and more general input-output systems. Among other topics of interest it deals with establishing fundamental relations between asymptotic frequencies and averages, pathwise stability, and insensitivity. These results are utilized to establish useful performance measures. The intuitive deterministic approach of this book will give researchers, teachers, practitioners, and students better insights into many results in queueing theory. The simplicity and intuitive appeal of the arguments will make these results more accessible, with no sacrifice of mathematical rigor. Recent topics such as pathwise stability are also covered in this context.
The book consistently takes the point of view of focusing on one sample path of a stochastic process. Hence, it is devoted to providing pure sample-path arguments. With this approach it is possible to separate the issue of the validity of a relationship from issues of existence of limits and/or construction of stationary framework. Generally, in many cases of interest in queueing theory, relations hold, assuming limits exist, and the proofs are elementary and intuitive. In other cases, proofs of the existence of limits will require the heavy machinery of stochastic processes. The authors feel that sample-path analysis can be best used to provide general results that are independent of stochastic assumptions, complemented by use of probabilistic arguments to carry out a more detailed analysis. This book focuses on the first part of the picture. It does however, provide numerous examples that invoke stochastic assumptions, which typically are presented at the ends of the chapters.

Inhaltsverzeichnis

Frontmatter
1. Introduction and Overview
Abstract
Studying the properties of one realization (sample path) of a stochastic process often leads to a better and deeper understanding of the properties of the system under study. It also provides a powerful tool for practitioners to determine which properties of a given system are independent of the usually imposed probabilistic assumptions. By its very nature a sample-path argument is deterministic and therefore requires no probabilistic assumptions. By focusing attention on a particular sample path, we are in effect assuming that the behavior of the system over time is completely known to us; thus probabilistic arguments are irrelevant.
Muhammad El-Taha, Shaler Stidham Jr.
2. Background and Fundamental Results
Abstract
In this chapter we present a number of fundamental results that will be used throughout the remainder of the book. The chapter is organized as follows. In Section 2.2 we collect some definitions and basic properties of deterministic point processes, and present two versions of Y = λX — the sample-path analogue of the renewal-reward theorem. (These generalize the simple version of Y = λX given in Chapter 1.) Section 2.3 presents fluid versions of Y = λX, in which the point process is replaced by a cumulative process. Section 2.4 shows how Y = λX can be used to give a simple proof of the sample-path rate-conservation law RCL under more general conditions than previously given. Section 2.5 gives discrete-variable and continuous-variable versions of the Fundamental Lemma of Maxima. In Section 2.6 we give a result that proves the equality of time-averages of a process and the mean of its asymptotic frequency distribution under a uniform integrability condition. In subsequent chapters we apply Y = λX and RCL to obtain simple proofs of relations between continuous-time frequencies of a process with a general state space and frequencies at the points of an imbedded point process.
Muhammad El-Taha, Shaler Stidham Jr.
3. Processes with Imbedded Point Process: General State Space
Abstract
This chapter presents a unified sample-path approach for deriving distribution- free relations between performance measures for processes with imbedded point processes. We consider processes with a general state space, specializing in the next chapter to a discrete state space. A unique feature of this approach is that all results are shown to follow from the three fundamental relations proved in Chapter 2: Lemma 2.1, the sample-path version of the elementary renewal theorem, and Theorems 2.2 and 2.3, the two sample-path versions of the renewal-reward theorem (Y = λX).
Muhammad El-Taha, Shaler Stidham Jr.
4. Processes with Imbedded Point Process: Countable State Space
Abstract
In this chapter we continue our study of processes with an imbedded point process, begun in Chapter 3. Now we specialize to a countable space. Again, the main focus is on the use of sample-path analysis to derive relations between various asymptotic state frequencies, such as the frequency at an arbitrary point in time and at the times of arrivals to a queueing system. In certain cases, we are also able to prove insensitivity.
Muhammad El-Taha, Shaler Stidham Jr.
5. Sample-Path Stability
Abstract
In the analysis of queues and other stochastic systems it is of primary importance to know whether an existing or a proposed system is stable. Roughly speaking, a stable system will tend to some sort of equilibrium, in which the state continues to fluctuate but such measures as the (average) probability distribution of the state or the fraction of time spent in various states do not change over time. By contrast, in an unstable system such limits do not exist. More drastically, the state (e.g., the number of customers or work in a queueing system) can grow without bound when the system is unstable.
Muhammad El-Taha, Shaler Stidham Jr.
6. Little’s Formula and Extensions
Abstract
Little’s formula, L = λW, is one of the most well-known and most useful conservation laws in queueing theory and stochastic systems. It states that the time average number of units in system equals the arrival rate of units × the average time-in-system per unit.
Muhammad El-Taha, Shaler Stidham Jr.
7. Insensitivity of Queueing Networks
Abstract
A queueing process is said to be insensitive if the distribution of the number of jobs in the system depends on the service-time distribution only through its mean. In Chapter 4 we give a sample-path proof of the insensitivity of a batch- arrival G/G/1-LCFS-PR queue, in which the batch sizes and service times are allowed to be state dependent (see also Stidham and El-Taha [182]). In this chapter we present a unified approach to proving insensitivity of symmetric queues in discrete-time using the method of time reversal. We use discrete- time sample-path analysis to show that the asymptotic frequency distribution of the number of jobs in infinite-server, Erlang loss, and round-robin models, is insensitive to the asymptotic distribution of service times under weak assumptions. For the infinite-server model, our assumptions allow batch arrivals and permit batch sizes and service times to be dependent. We show that insensitivity holds if the frequency distribution of batch sizes solves a system of equations. A solution to this set of equations occurs if the batch size of arrivals at each time unit follows a Poisson distribution. Similar results hold for the Loss model with constant batch sizes and deterministic service requirements, and for the round-robin queue.
Muhammad El-Taha, Shaler Stidham Jr.
8. Sample-Path Approach to Palm Calculus
Abstract
Previous chapters have established sample-path versions of relations between marginal time-stationary and event-stationary (Palm) state probabilities for a process with an imbedded point process. This chapter extends the use of sample-path analysis to characterize the complete frequency distributions of a process with an imbedded point process, rather than just the marginal distributions. We define sample-path analogues of the time-stationary and eventstationary (Palm) probability measures for the processes in question, and then derive sample-path versions of the Palm transformation and inversion formulas.
Muhammad El-Taha, Shaler Stidham Jr.
Backmatter
Metadaten
Titel
Sample-Path Analysis of Queueing Systems
verfasst von
Muhammad El-Taha
Shaler Stidham Jr.
Copyright-Jahr
1999
Verlag
Springer US
Electronic ISBN
978-1-4615-5721-0
Print ISBN
978-1-4613-7620-0
DOI
https://doi.org/10.1007/978-1-4615-5721-0