Analysis of a discrete-time single-server queue with bursty imputs for traffic control in ATM networks

Due to a large number of bursty traffic sources that an ATM network is expected to support, controlling network traffic becomes essential to provide a desirable level of network performance with its users. Admission control and traffic smoothing are among the most promising control techniques for an ATM network. To evaluate the performance of an ATM network when it is subject to admission control or traffic smoothing, we build a discrete-time single-server queueing model where a new call joins the existing calls.In our model. it is assumed that the cell arrivals from a new call follow a general distribution. It is also assumed that the aggregated arrivals of cells from the existing calls form batch arrivals with a general distribution for the batch size and a geometric distribution for the interarrival times of batches. We consider both finite and infinite buffer cases, and analytically obtain the waiting time distribution and cell loss probability for a new call and for existing calls. Our analysis is an exact one. Through numerical examples, we investigate how the network performance depends on the statistics of a new call (burstiness, time that a call stays in active or inactive state, etc.). We also demonstrate the effectiveness of traffic smoothing to reduce network congestion

Fast Ensemble Smoothing

Smoothing is essential to many oceanographic, meteorological and hydrological applications. The interval smoothing problem updates all desired states within a time interval using all available observations. The fixed-lag smoothing problem updates only a fixed number of states prior to the observation at current time. The fixed-lag smoothing problem is, in general, thought to be computationally faster than a fixed-interval smoother, and can be an appropriate approximation for long interval-smoothing problems. In this paper, we use an ensemble-based approach to fixed-interval and fixed-lag smoothing, and synthesize two algorithms. The first algorithm produces a linear time solution to the interval smoothing problem with a fixed factor, and the second one produces a fixed-lag solution that is independent of the lag length. Identical-twin experiments conducted with the Lorenz-95 model show that for lag lengths approximately equal to the error doubling time, or for long intervals the proposed methods can provide significant computational savings. These results suggest that ensemble methods yield both fixed-interval and fixed-lag smoothing solutions that cost little additional effort over filtering and model propagation, in the sense that in practical ensemble application the additional increment is a small fraction of either filtering or model propagation costs. We also show that fixed-interval smoothing can perform as fast as fixed-lag smoothing and may be advantageous when memory is not an issue

Parallel Working-Set Search Structures

In this paper we present two versions of a parallel working-set map on p processors that supports searches, insertions and deletions. In both versions, the total work of all operations when the map has size at least p is bounded by the working-set bound, i.e., the cost of an item depends on how recently it was accessed (for some linearization): accessing an item in the map with recency r takes O(1+log r) work. In the simpler version each map operation has O((log p)^2+log n) span (where n is the maximum size of the map). In the pipelined version each map operation on an item with recency r has O((log p)^2+log r) span. (Operations in parallel may have overlapping span; span is additive only for operations in sequence.) Both data structures are designed to be used by a dynamic multithreading parallel program that at each step executes a unit-time instruction or makes a data structure call. To achieve the stated bounds, the pipelined data structure requires a weak-priority scheduler, which supports a limited form of 2-level prioritization. At the end we explain how the results translate to practical implementations using work-stealing schedulers. To the best of our knowledge, this is the first parallel implementation of a self-adjusting search structure where the cost of an operation adapts to the access sequence. A corollary of the working-set bound is that it achieves work static optimality: the total work is bounded by the access costs in an optimal static search tree.Comment: Authors' version of a paper accepted to SPAA 201

Parameter estimation for stochastic hybrid model applied to urban traffic flow estimation

This study proposes a novel data-based approach for estimating the parameters of a stochastic hybrid model describing the traffic flow in an urban traffic network with signalized intersections. The model represents the evolution of the traffic flow rate, measuring the number of vehicles passing a given location per time unit. This traffic flow rate is described using a mode-dependent first-order autoregressive (AR) stochastic process. The parameters of the AR process take different values depending on the mode of traffic operation – free flowing, congested or faulty – making this a hybrid stochastic process. Mode switching occurs according to a first-order Markov chain. This study proposes an expectation-maximization (EM) technique for estimating the transition matrix of this Markovian mode process and the parameters of the AR models for each mode. The technique is applied to actual traffic flow data from the city of Jakarta, Indonesia. The model thus obtained is validated by using the smoothed inference algorithms and an online particle filter. The authors also develop an EM parameter estimation that, in combination with a time-window shift technique, can be useful and practical for periodically updating the parameters of hybrid model leading to an adaptive traffic flow state estimator

A general multiblock Euler code for propulsion integration. Volume 3: User guide for the Euler code

This manual explains the procedures for using the general multiblock Euler (GMBE) code developed under NASA contract NAS1-18703. The code was developed for the aerodynamic analysis of geometrically complex configurations in either free air or wind tunnel environments (vol. 1). The complete flow field is divided into a number of topologically simple blocks within each of which surface fitted grids and efficient flow solution algorithms can easily be constructed. The multiblock field grid is generated with the BCON procedure described in volume 2. The GMBE utilizes a finite volume formulation with an explicit time stepping scheme to solve the Euler equations. A multiblock version of the multigrid method was developed to accelerate the convergence of the calculations. This user guide provides information on the GMBE code, including input data preparations with sample input files and a sample Unix script for program execution in the UNICOS environment