The algorithms described in this thesis are designed to schedule cells in a very high-speed, parallel, input-queued crossbar switch. We present several novel scheduling algorithms that we have devised, each aims to match the set of inputs of an input-queued switch to the set of outputs more efficiently, fairly and quickly than existing techniques. In Chapter 2 we present the simplest and fastest of these algorithms: SLIP --- a parallel algorithm that uses rotating priority ("round-robin") arbitration. SLIP is simple: it is readily implemented in hardware and can operate at high speed. SLIP has high performance: for uniform i.i.d. Bernoulli arrivals, SLIP is stable for any admissible load, because the arbiters tend to desynchronize. We present analytical results to model this behavior. However, SLIP is not always stable and is not always monotonic: adding more traffic can actually make the algorithm operate more efficiently. We present an approximate analytical model of this behavior. SLIP prevents starvation: all contending inputs are eventually served. We present simulation results, indicating SLIP's performance. We argue that SLIP can be readily implemented for a 32x32 switch on a single chip. In Chapter 3 we present i-SLIP, an iterative algorithm that improves upon SLIP by converging on a maximal size match. The performance of i-SLIP improves with up to log 2 N iterations. We show that although it has a longer running time than SLIP, an i-SLIP scheduler is little more complex to implement. In Chapter 4 we describe maximum or maximal weight matching algorithms based on the occupancy of queues, or waiting times of cells. These algorithms are stabl...

In this tutorial we give an overview of the process algebra EMPA, a calculus devised in order to model and analyze features of real-world concurrent systems such as nondeterminism, priorities, probabilities and time, with a particular emphasis on performance evaluation. The purpose of this tutorial is to explain the design choices behind the development of EMPA and how the four features above interact, and to show that a reasonable trade off between the expressive power of the calculus and the complexity of its underlying theory has been achieved.

We consider an ATM system with an architecture which is designed to accommodate users with very different quality of service requirements. In the base case with only two services, sources which require low loss belong to a High Priority class, and share a FCFS buffer, which has priority access to the trunk. A Low Priority class of sources with typically less stringent requirements on loss have a separate FCFS buffer, which receives the time-varying, residual bandwidth, if any, of the trunk. By administering admission control and restricting the combination of sources to an admissible set, the service guarantees for both classes may be satisfied. The sources are bursty and stochastic fluid models are used to handle burst-scale congestion effects. Our contributions are: (i) we develop simple, fast and robust analytic approximations for the queue distributions in the two buffers; (ii) for admission control, we calculate the admissible set by using our analytic approximations and find that...

We define Recursive Markov Chains (RMCs), a class of finitely presented denumerable Markov chains, and we study algorithms for their analysis. Informally, an RMC consists of a collection of finite-state Markov chains with the ability to invoke each other in a potentially recursive manner. RMCs offer a natural abstract model for probabilistic programs with procedures. They generalize, in a precise sense, a number of well studied stochastic models, including Stochastic Context-Free Grammars (SCFG) and Multi-Type Branching Processes (MT-BP). We focus on algorithms for reachability and termination analysis for RMCs: what is the probability that an RMC started from a given state reaches another target state, or that it terminates? These probabilities are in general irrational, and they arise as (least) fixed point solutions to certain (monotone) systems of nonlinear equations associated with RMCs. We address both the qualitative problem of determining whether the probabilities are 0, 1 or in-between, and

This paper surveys the theoretical developments in the field of stochastic process algebras, process algebras where action occurrences may be subject to a delay that is determined by a random variable. A huge class of resource-sharing systems --- like large-scale computers, client-server architectures, networks --- can accurately be described using such stochastic specification formalisms.

In this paper we present a language for finite state continuous time Bayesian networks (CTBNs), which describe structured stochastic processes that evolve over continuous time. The state of the system is decomposed into a set of local variables whose values change over time. The dynamics of the system are described by specifying the behavior of each local variable as a function of its parents in a directed (possibly cyclic) graph. The model specifies, at any given point in time, the distribution over two aspects: when a local variable changes its value and the next value it takes. These distributions are determined by the variable’s current value and the current values of its parents in the graph. More formally, each variable is modelled as a finite state continuous time Markov process whose transition intensities are functions of its parents. We present a probabilistic semantics for the language in terms of the generative model a CTBN defines over sequences of events. We list types of queries one might ask of a CTBN, discuss the conceptual and computational difficulties associated with exact inference, and provide an algorithm for approximate inference which takes advantage of the structure within the process.

In this paper we establish asymptotics for the basic steady-state distributions in a large class of single-server queues. We consider the waiting time, the workload (virtual waiting time) and the steady-state queue lengths at an arbitrary time, just before an arrival and just after a departure. We start by establishing asymptotics for steady-state distributions of Markov chains of M/GI/1 type. Then we treat steady-state distributions in the BMAP/GI/1 queue, which has a batch Markovian arrival process (BMAP). The BMAP is equivalent to the versatile Markovian point process or Neuts (N) process; it generalizes the Markovian arrival process (MAP) by allowing batch arrivals. The MAP includes the Markov-modulated Poisson process (MMPP), the phase-type renewal process (PH) and independent superpositions of these as special cases. We also establish asymptotics for steady-state distributions in the MAP/MSP/1 queue, which has a Markovian service process (MSP). The MSP is a MAP independent of the arrival process generating service completions during the time the server is busy. In great generality (but not always), the basic steady-state distributions have asymptotically exponential tails in all these models. When they do, the asymptotic parameters of the different distributions are closely related. 1.

This paper presents a new computational method for steady state analysis of finite QBDprocess with level-dependent transitions. The QBD state space is defined in two-dimension with N phases and K levels. Instead of formulating solutions in matrix-geometric form, the Foldingalgorithm provides a technique for direct computation of ßP = 0, where P is the QBD generator which is an (NK) \Theta (NK) matrix. Taking a finite sequence of fixed-cost binary reduction steps, the K-level matrix P is eventually reduced to a single-level matrix, from which a boundary vector is obtained. Each step halves the matrix size but keeps the QBD form. The solution ß is expressed as a product of the boundary vector and a finite sequence of expansion factors. The time and space complexity for solving ßP = 0 is therefore reduced from O(N 3 K) and O(N 2 K) to O(N 3 log 2 K)andO(N 2 log 2 K), respectively. The Folding-algorithm has a number of highly desirable advantages when it is applied to queueing an...

Abstract not found

Supporting data applications over networks comprising both wireless and wireline links is of increasing importance for both military and commercial systems. Many standard data applications on current wireline networks are based on TCP/IP, the end-to-end flow and congestion control protocol widely used on the Internet, so that it is of crucial importance to devise network level controls that enable TCP to perform well when the path from source to destination includes one or more wireless links. Since TCP has been recently shown to perform poorly in the presence of random loss, its performance over a lossy wireless link subject to deep fades and other impairments may be unsatisfactory. In this paper, we show that a suitable link level error recovery mechanism can "hide" the fluctuations of the wireless medium from TCP, and we provide an analytical framework for predicting TCP performance as a function of the wireless channel characteristics and the size of the wireless-wireline interface...