Set Of Independent Tasks Research Articles

Feasible processor allocation in a Hard-Real-Time environment

Consider the problem of scheduling a set of preemptible tasks in one or more processor systems. The task system consists of a set of independent tasks or a task set with precedence relations. Each task is characterized by execution time and deadline. This article presents scheduling algorithms that guarantee all time constraints. These algorithms are so easy to implement that they can be used in real-time operating systems. An overview is given for the different feasible scheduling algorithms of some task and processor systems.

On a special case of uniform processor scheduling

We investigate the problem of nonpreemptively assigning a set of independent tasks to a system of uniform processors in an effort to minimize the overall finish time. Our attention is restricted to the special case in which all processors have the same speed, except for one which may be faster. This models the system configuration in which there is one fast central processor and a collection of slower peripheral processors. We analyze a variation of the MULTIFIT algorithm derived from bin-packing and prove that it possesses a tight worst-case performance bound of ( 17 + 1) 4 , which is approximately 1.28.

The complexity of preemptive scheduling given interprocessor communication delays

We discuss the problem of scheduling af set of independent tasks T, each t i ϵ T of lenght ℓ i ϵ Z +, on m identical processors. We allow preemption but assume a communication delay of time k ϵ N. Whenever a task is preempted from one processor to another, there must be a delay of at least k time units. We show that if k = 1, an optimal schedule can be found in polynomial time but if k ⩾ 2, the corresponding decision problem is NP-complete.

Experience with a Virtual Memory Based Data Acquisition System at CERN

This paper describes a Data Acquisition System which has been specifically designed to take advantage of modern operating systems. It is modular, structured as a set of independent tasks communicating via a shared data area. The design is based on the concept of circular buffers with associated data producer and (parallel) consumer tasks. By using privileged tasks in time critical areas, a fast and efficient system has been obtained: interrupt latency of less than 100 microseconds, and data transfer speeds essentially limited by hardware (CAMAC DMA or magnetic tape recording). The tasks may be distributed over different processors. For example, 16/32 bit multi-processors with a shared multi-port memory are used to implement systems where powerful data reduction and/or monitoring tasks are required. The system is in use at over 25 high energy and nuclear physics experiments at CERN and in other European laboratories.

Scheduling to Maximize the Minimum Processor Finish Time in a Multiprocessor System

This investigation considers the problem of nonpreemptively assigning a set of independent tasks to a system of identical processors to maximize the earliest processor finishing time. While this goal is a nonstandard scheduling criterion, it does have natural applications in certain maintenance scheduling and deterministic fleet sizing problems. The problem is NP-hard, justifying an analysis of heuristics such as the well-known LPT algorithm in an effort to guarantee near-optimal results. It is proved that the worst-case performance of the LPT algorithm has an asymptotically tight bound of $\frac{4}{3}$ times the optimal.

An experimental comparison of solution algorithms for the single‐machine tardiness problem

AbstractA basic problem in scheduling involves the sequencing of a set of independent tasks at a single facility with the objective of minimizing mean tardiness. Although the problem is relatively simple, the determination of an optimal sequence remains a challenging combinatorial problem. A number of algorithms have been developed for finding solutions, and this paper reports a comparative evaluation of these procedures. Computer programs for five separate algorithms were written and all were run on a data base designed to highlight computational differences. Optimizing algorithms developed by Emmons and by Srinivasan appeared to be particularly efficient in the comparative study.

Scheduling independent tasks to reduce mean finishing-time (extended abstract)

In this paper we study the problem of scheduling a set of independent tasks on m ≥ 1 processors to minimize the mean finishing-time (mean time in system). The importance of the mean finishing-time criterion is that its minimization tends to reduce the mean number of unfinished tasks in the system. In the paper we give a reduction of our scheduling problem to a transportation problem and thereby extend the class of known non enumerative scheduling algorithms [1]. Next we show that the inclusion of weights (weighted mean finishing-time) complicates the problem and speculate that there may be no non enumerative algorithm for this case. For the special case of identical processors we study the maximum finishing-time properties of schedules which are optimal with respect to mean finishing-time. Finally we give a scheduling algorithm having desirable properties with respect to both maximum finishing-time and mean finishing-time.

An Improved Method for Scheduling Independent Tasks

Abstract A computationally efficient algorithm is developed for scheduling an independent task set, characterized by deterministic processing times and due dates, on a single processor so that total tardiness is minimized. The performance index is assumed to be a loss function of the form max (0, Ci - Di) where Ci is the calendar completion time of task i and Di, is its due date. The method is in general sub-optimal, but conditions are given for which an optimal schedule is always obtained. In addition, a technique is presented for improving suboptimal solutions by merely interchanging certain nonadjacent pairs of tasks.