Static priority scheduling for ATM networks

A priority scheduling algorithm with double threshold and a traffic control mechanism with hysteresis effect are proposed. The double threshold priority scheduling is studied based on the minimum laxity threshold (MLT) and the queue length threshold (QLT). The hysteresis effect traffic control is specified by the hysteresis effect QLT and traffic rate control. According to the simulation results, it can be shown that the proposed dynamic priority scheduling has a better processing performance than the existing MLT and QLT algorithm. The results also demonstrate that the QLT with hysteresis effect and traffic rate control with the hysteresis effect enhance the performance in comparison with those of single threshold.

Recent advances in high-speed wireless LANs with physical layer (PHY) rates reaching 600Mbps make them ideal for multimedia applications. It has been shown that efficiency at medium access control (MAC) layer decreases with increasing the PHY rate. To achieve high efficiency, few researches have tried to use aggregation in which few packets are concatenated into a larger frame. The resultant frame is sent at once in order to reduce the media access protocol overhead. Unfortunately larger frames increase delays. Since demand for real-time data communication and delay-sensitive applications have become more critical, especially for high-speed networks, a thorough delay analysis is required to examine the effect of aggregation on delay in high-speed networks. In this paper, we propose an analytical model for examining packet delay in IEEE 802.11n networks in the saturation mode. To the best of our knowledge, this is the first work which focuses on packet delay analysis in the presence of aggregation. Analysis and simulation results show that packet delay increases in larger aggregation sizes, and IEEE 802.11n performs poorly in high rates in terms of packet delay. Moreover, based on two new metrics that we propose in the paper, it is shown that aggregation loses its effectiveness in higher rates.

We discuss the call admission control problem in ATM networks. In particular, we focus on a single node in isolation as a model for the ATM multiplexer, and consider the cell loss probability and the average cell queueing delay in the multiplexer as the quality of service (QoS) performance measures. Difficulties often arise in the analysis for such systems due to the so-called curse of dimensionality in calculating some integer-parametered functions, where the integer parameter represents the system size or dimension. Our basic idea is to develop global rational approximation for such systems. Various examples presented in the previous papers have demonstrated the power of the approach. In this paper we apply the rational approximation method to the call admission problem in ATM networks.

We present a task model for the real-time execution of event-driven tasks in which no a priori characterization of the actual arrival rates of events is known; only the expected arrival rates of events is known. The model, called rate-bared execution (RBE), is a generalization of Mok's sporadic task model. The RBE model is motivated naturally by distributed multimedia and digital signal processing applications. We derive necessary and sufficient conditions for determining the feasibility of an RBE task set and demonstrate that earliest deadline first (EDF) scheduling is an optimal scheduling algorithm for both preemptive and nonpreemptive execution environments, as well as hybrid environments wherein RBE tasks access shared resources. Our analysis of RBE tasks demonstrates a fundamental distinction between deadline based scheduling methods and static priority based methods. We show that for deadline-based scheduling methods, feasibility is solely a function of the distribution of task deadlines in time. This is contrasted with static priority schedulers where feasibility is a function of the actual arrival rates of work for tasks. Thus whereas the feasibility of static priority schedulers is a function of the periodicity of tasks, the feasibility of deadline schedulers is independent of task arrival processes and hence deadline schedulers are more suitable for use in distributed, event-driven, real-time systems.

Most existing real-time control systems use ad hoc static priority scheduling methods, in spite of the fact that the rate monotonic scheduling algorithm was proved to be the optimal static priority scheduling algorithm over 20 years ago. In this paper, we discuss a task library we are using for the real-time control of autonomous robots. The task library comprises a preemptive rate-monotonic scheduler which provides guaranteed optimal scheduling when certain conditions of processor utilization are met. The task library has been implemented as a collection of lightweight threads, which operate entirely in user-space for maximum efficiency. We show the performance advantages resulting from the reduced overhead of this approach, compared with commercial operating systems. The task system is robust, extensible, and portable, and has been successfully used to control the autonomous mobile robot Yamabico-11 developed at the Naval Postgraduate School.

Petri net extensions for the development of MIMO net models of automated manufacturing systems

Queue assignment for fixed-priority real-time flows in time-sensitive networks: Hardness and algorithm

The number of virtual connections in the nodal space of an ATM network of arbitrary structure and topology is computed by a method based on a new concept—a covering domain having a concrete physical meaning. The method is based on a “network information sources—boundary switches” model developed for an “ATM transfer network” by the entropy approach. Computations involve the solution of systems of linear equations. The optimization model used to compute the number of virtual connections in a many-category traffic in an ATM network component is useful in estimating the resource of nodal equipment and communication channels. The variable parameters of the model are the transmission bands for different traffic categories.

Fixed-priority preemption-threshold scheduling (FPTS) is a generalization of fixed-priority preemptive scheduling (FPPS) and fixed-priority non-preemptive scheduling (FPNS). Since FPPS and FPNS are incomparable in terms of potential schedulability, FPTS has the advantage that it can schedule any task set schedulable by FPPS or FPNS and some that are not schedulable by either. FPTS is based on the idea that each task is assigned a priority and a preemption threshold. While tasks are admitted into the system according to their priorities, they can only be preempted by tasks that have priority higher than the preemption threshold. This paper presents a new optimal priority and preemption threshold assignment (OPTA) algorithm for FPTS which in general outperforms the existing algorithms in terms of the size of the explored state-space and the total number of worst case response time calculations performed. The algorithm is based on back-tracking, i.e. it traverses the space of potential priorities and preemption thresholds, while pruning infeasible paths, and returns the first assignment deemed schedulable. We present the evaluation results where we compare the complexity of the new algorithm with the existing one. We show that the new algorithm significantly reduces the time needed to find a solution. Through a comparative evaluation, we show the improvements that can be achieved in terms of schedulability ratio by our OPTA compared to a deadline monotonic priority assignment.

The network planning problems for ATM networks are completely different from conventional ones because ATM networks must support various types of traffic, each of which has different characteristics such as holding time, average bit rate, and peak bit rate. In the initial deployment of ATM networks, basic network planning problems are to determine the locations of switching nodes and link capacities between selected nodes. We propose detailed mathematical models and algorithms useful for the problems encountered in planning ATM networks. These models include the facility location and dimensioning problems. We also consider routing problems which are closely related to the dimensioning problem.

The large gap between the systems analyzed by classical queueing theory and ATM networks cries out for solutions based on learning. Even those few problems amenable to classical analysis techniques have a component that defies explicit analysis — the intrinsic uncertainties associated with describing and controlling the flows in high performance, mixed service networks. Unlike the stationary, uncorrelated sources characteristic of queueing theory, the pattern of arrivals in these systems are highly correlated in time. Exploiting these correlations, either directly, with a predictive model, or indirectly, as in reinforcement learning, can result in significant performance gains. Queuing systems have another property requiring the application of non-traditional control techniques; the rewards, or more often penalties, associated with control actions are delayed and non-linear. For example, a control action can allow a buffer to fill up without incurring a short term performance penalty but may result in a large delayed penalty if a subsequent burst of activity causes an overflow. Control problems with delayed rewards require techniques that find optimal sequences or trajectories instead of responding to just the instantaneous state of the system.

This paper studies preemptive static-priority scheduling on multiprocessors. We consider two approaches: global pfair static-priority scheduling and partitioned traditional static priority scheduling. We prove that if presented algorithms are used and if less than 50% of the capacity is used then all deadlines are met. It is known that no static-priority multiprocessor scheduling algorithm can achieve a utilization bound greater than 50%.

Bandwidth allocation mechanism for LAN/MAN interworking with an ATM network

For admitting a hard real-time connection to an ATM network, it is required that the end-to-end delays of cells belonging to the connection meet their deadlines without violating the guarantees already provided to the currently active connections. There are two kinds of methods to analyze the end-to-end delay in an ATM network. A decomposed method analyzes the worst case delay for each switch and then computes the total delay as the sum of the delays at individual switches. On the other hand, an integrated method analyzes all the switches involved in an integrated manner and derives the total delay directly. In this paper, we present an efficient and effective integrated method to compute the end-to-end delay. We evaluate the network performance under different system parameters and we compare the performance of the proposed method with the conventional decomposed and other integrated methods [1], [3], [5]–[9].

Real-time systems are often designed using a set of periodic tasks. Task periods are usually set by the system requirements, but deadlines and computation times can be modified in order to improve system performance. Sensitivity analysis in real-time systems has focused on changes in task computation times using fixed priority analysis. Only a few studies deal with the modification of deadlines in dynamic priority scheduling. The aim of this work is to provide a sensitivity analysis for task deadlines in the context of dynamic-priority, pre-emptive, uniprocessor scheduling. In this paper, we present a deadline minimisation method that achieves the maximum reduction. As undertaken in other studies concerning computation times, we also define and calculate the critical scaling factor for task deadlines. Our proposal is evaluated and compared with other works in terms of jitter. The deadline minimisation can be used to strongly reduce jitter of control tasks, in a real-time control application.