Showing papers on "Dynamic priority scheduling published in 2000"

Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid

Abstract: The availability of powerful microprocessors and high-speed networks as commodity components has enabled high-performance computing on distributed systems (wide-area cluster computing). In this environment, as the resources are usually distributed geographically at various levels (department, enterprise or worldwide), there is a great challenge in integrating, coordinating and presenting them as a single resource to the user, thus forming a computational grid. Another challenge comes from the distributed ownership of resources, with each resource having its own access policy, cost and mechanism. The proposed Nimrod/G grid-enabled resource management and scheduling system builds on our earlier work on Nimrod (D. Abramson et al., 1994, 1995, 1997, 2000) and follows a modular and component-based architecture enabling extensibility, portability, ease of development, and interoperability of independently developed components. It uses the GUSTO (GlobUS TOolkit) services and can be easily extended to operate with any other emerging grid middleware services. It focuses on the management and scheduling of computations over dynamic resources scattered geographically across the Internet at department, enterprise or global levels, with particular emphasis on developing scheduling schemes based on the concept of computational economy for a real testbed, namely the Globus testbed (GUSTO).

Real-time calculus for scheduling hard real-time systems

Abstract: This paper establishes a link between three areas, namely Max-Plus Linear System Theory as used for dealing with certain classes of discrete event systems, Network Calculus for establishing time bounds in communication networks, and real-time scheduling. In particular, it is shown that important results from scheduling theory can be easily derived and unified using Max-Plus Algebra. Based on the proposed network theory for real-time systems, the first polynomial algorithm for the feasibility analysis and optimal priority assignment for a general task model is derived.

OR Scheduling Algorithms

Abstract: We study some classical problems in scheduling. In the rst problem a sequence of jobs must be scheduled on m identical parallel machines. As each job arrives, its processing time(pj) is known. We have to assign the job to one of the machines immediately, without knowledge of the jobs that arrive later. Jobs cannot be preempted. The goal is to minimize the makespan, the time when the last job is completed. The second problem deals with scheduling jobs on a single machine/processor. With each job we have an associated weight(wj), release time(rj) and processing time(pj). Now the objective is to minimize the weighted sum of completion times,Pnj=0wjCj . The constraints are that a job can only be scheduled after its release time, and preemption is not allowed. In the third problem again there are m machines. Each job has to visit the machines in the same xed order. The processing time pij of job j on machine i is known. We want a schedule which minimizes the makespan. A job can only be processed on a single machine at a time. Chapter

Speed is as powerful as clairvoyance

Abstract: We introduce resource augmentation as a method for analyzing online scheduling problems. In resource augmentation analysis the on-line scheduler is given more resources, say faster processors or more processors, than the adversary. We apply this analysis to two well-known on-line scheduling problems, the classic uniprocessor CPU scheduling problem 1 |ri, pmtn|S Fi, and the best-effort firm real-time scheduling problem 1|ri, pmtn| S wi( 1- Ui). It is known that there are no constant competitive nonclairvoyant on-line algorithms for these problems. We show that there are simple on-line scheduling algorithms for these problems that are constant competitive if the online scheduler is equipped with a slightly faster processor than the adversary. Thus, a moderate increase in processor speed effectively gives the on-line scheduler the power of clairvoyance. Furthermore, the on-line scheduler can be constant competitive on all inputs that are not closely correlated with processor speed. We also show that the performance of an on-line scheduler is best-effort real time scheduling can be significantly improved if the system is designed in such a way that the laxity of every job is proportional to its length.

The benefits of event: driven energy accounting in power-sensitive systems

Abstract: A prerequisite of energy-aware scheduling is precise knowledge of any activity inside the computer system. Embedded hardware monitors (e.g., processor performance counters) have proved to offer valuable information in the field of performance analysis. The same approach can be applied to investigate the energy usage patterns of individual threads. We use information about active hardware units (e.g., integer/floating-point unit, cache/memory interface) gathered by event counters to establish a thread-specific energy accounting. The evaluation shows that the correlation of events and energy values provides the necessary information for energy-aware scheduling policies.Our approach to OS-directed power management adds the energy usage pattern to the runtime context of a thread. Depending on the field of application we present two scenarios that benefit from applying energy usage patterns: Workstations with passive cooling on the one hand and battery-powered mobile systems on the other hand.Energy-aware scheduling evaluates the energy usage of each thread and throttles the system activity so that the scheduling goal is achieved. In workstations we throttle the system if the average energy use exceeds a predefined power-dissipation capacity. This makes a compact, noiseless and affordable system design possible that meets sporadic yet high demands in computing power. Nowadays, more and more mobile systems offer the features of reducible clock speed and dynamic voltage scaling. Energy-aware scheduling can employ these features to yield a longer battery life by slowing down low-priority threads while preserving a certain quality of service.

Nature's heuristics for scheduling jobs on Computational Grids

Abstract: Computational Grid (Grid Computing) is a new paradigm that will drive the computing arena in the new millennium. Unification of globally remote and diverse resources, coupled with the increasing computational needs for Grand Challenge Applications (GCA) and accelerated growth of the Internet and communication technology will further fuel the development of global computational power grids. In this paper, we attempt to address the scheduling of jobs to the geographically distributed computing resources. Conventional wisdom in the field of scheduling is that scheduling problems exhibit such richness and variety that no single scheduling method is sufficient. Heuristics derived from the nature has demonstrated a surprising degree of effectiveness and generality for handling combinatorial optimization problems. This paper begins with an introduction of computational grids followed by a brief description of the three nature's heuristics namely Genetic Algorithm (GA), Simulated Annealing (SA) and Tabu Search (TS). Experimental results using GA are included. We further demonstrate the hybridized usage of the above algorithms that can be applied in a computational grid environment for job scheduling.

A new model for packet scheduling in multihop wireless networks

Abstract: The goal of packet scheduling disciplines is to achieve fair and maximum allocation of channel bandwidth. However, these two criteria can potentially be in conflict in a generic-topology multihop wireless network where a single logical channel is shared among multiple contending flows and spatial reuse of the channel bandwidth is possible. In this paper, we propose a new model for packet scheduling that addresses this conflict. The main results of this paper are the following: (a) a two-tier service model that provides a minimum “fair” allocation of the channel bandwidth for each packet flow and additionally maximizes spatial reuse of bandwidth, (b) an ideal centralized packet scheduling algorithm that realizes the above service model, and (c) a practical distributed backoff-based channel contention mechanism that approximates the ideal service within the framework of the CSMA/CA protocol.

Single Machine Scheduling with Learning Effect Considerations

Abstract: In this paper we study a single machine scheduling problem in which the job processing times will decrease as a result of learning. A volume-dependent piecewise linear processing time function is used to model the learning effects. The objective is to minimize the maximum lateness. We first show that the problem is NP-hard in the strong sense and then identify two special cases which are polynomially solvable. We also propose two heuristics and analyse their worst-case performance.

Three Scheduling Algorithms Applied to the Earth Observing Systems Domain

Abstract: This paper describes three approaches to assigning tasks to earth observing satellites EOS. A fast and simple priority dispatch method is described and shown to produce acceptable schedules most of the time. A look ahead algorithm is then introduced that outperforms the dispatcher by about 12% with only a small increase in run time. These algorithms set the stage for the introduction of a genetic algorithm that uses job permutations as the population. The genetic approach presented here is novel in that it uses two additional binary variables, one to allow the dispatcher to occasionally skip a job in the queue and another to allow the dispatcher to occasionally allocate the worst position to the job. These variables are included in the recombination step in a natural way. The resulting schedules improve on the look ahead by as much as 15% at times and 3% on average. We define and use the "window-constrained packing" problem to model the bare bones of the EOS scheduling problem.

Early-release fair scheduling

Abstract: Presents a variant of Pfair scheduling (S. Baruah et al., 1995, 1996), which we call early-release fair (ERfair) scheduling. Like conventional Pfair scheduling, ERfair scheduling algorithms can be applied to optimally schedule periodic tasks on a multiprocessor system in polynomial time. However, ERfair scheduling differs from Pfair scheduling in that it is work-conserving. As a result, average job response times may be much lower under ERfair scheduling than under Pfair scheduling, particularly in lightly loaded systems. In addition, run-time costs are lower under ERfair scheduling.

Cyclic scheduling in robotic flowshops

Abstract: Fully automated production cells consisting of flexible machines and a material handling robot have become commonplace in contemporary manufacturing systems. Much research on scheduling problems arising in such cells, in particular in flowshop-like production cells, has been reported recently. Although there are many differences between the models, they all explicitly incorporate the interaction between the materials handling and the classical job processing decisions, since this interaction determines the efficiency of the cell. This paper surveys cyclic scheduling problems in robotic flowshops, models for such problems, and the complexity of solving these problems, thereby bringing together several streams of research that have by and large ignored one another, and describing and establishing links with other scheduling problems and combinatorial topics.

Robust scheduling of a two-machine flow shop with uncertain processing times

Abstract: This paper focuses on manufacturing environments where job processing times are uncertain. In these settings, scheduling decision makers are exposed to the risk that an optimal schedule with respect to a deterministic or stochastic model will perform poorly when evaluated relative to actual processing times. Since the quality of scheduling decisions is frequently judged as if processing times were known a priori, robust scheduling, i.e., determining a schedule whose performance (compared to the associated optimal schedule) is relatively insensitive to the potential realizations of job processing times, provides a reasonable mechanism for hedging against the prevailing processing time uncertainty. In this paper we focus on a two-machine flow shop environment in which the processing times of jobs are uncertain and the performance measure of interest is system makespan. We present a measure of schedule robustness that explicitly considers the risk of poor system performance over all potential realizations of...

Test scheduling for core-based systems using mixed-integer linear programming

Abstract: We present optimal solutions to the test scheduling problem for core-based systems. Given a set of tasks (test sets for the cores), a set of test resources (e.g., test buses, BIST hardware) and a test access architecture, we determine start times for the tasks such that the total test application time is minimized. We show that the test scheduling decision problem is equivalent to the m-processor open shop scheduling problem and is therefore NP-complete. However a commonly encountered instance of this problem (m=2) can be solved in polynomial time. For the general case (m>2), we present a mixed-integer linear programming (MILP) model for optimal scheduling and apply it to a representative core-based system using an MILP solver available in the public domain. We also extend the MILP model to allow optimal test set selection from a set of alternatives. Finally, we present an efficient heuristic algorithm for handling larger systems for which the MILP model may be infeasible.

Integration of process planning and scheduling— a review

Abstract: In recent years, a few researchers have addressed the need for the integration of process planning and scheduling functions in order to achieve superior overall system performance. Many of these researchers have discovered that the potential savings are substantial when process planning and scheduling are integrated. It has been reported that typical scheduling objectives, such as minimizing makespan, maximizing equipment utilization, etc, can be significantly improved as the result of integration of these two important manufacturing system functions. In this paper, we present a review of the reported research in this area, discuss the extent of applicability of various approaches, and suggest directions for future research.

An introduction to control and scheduling co-design

Abstract: The paper presents the emerging field of integrated control and CPU-time scheduling, where more general scheduling models and methods that better suit the needs of control systems are developed. This creates possibilities for dynamic and flexible integrated control and scheduling frameworks, where the control design methodology takes the availability of computing resources into account during design and allows online trade-offs between control performance and computing resource utilization.

Continuous-discrete interactions in chemical processing plants

Abstract: This paper discusses important hybrid aspects of chemical processing plants. It is outlined that discrete phenomena occur both on the physical level and in the control of these plants. As the dynamics of the transformations of energy and material are predominantly continuous, large and complex hybrid systems arise. We focus on three different aspects of dealing with such systems: (1) Modeling and simulation of hybrid systems for the design and optimization of plants, controllers and operating strategies. We present powerful simulation environments that have been developed in recent years. (2) Validation of plant instrumentation and discrete controllers. These systems are largely responsible for the safe and economic operation of chemical plants and the protection of the workforce, and the environment. Techniques for the verification of discrete controllers for continuous processes are discussed, which are based on a discrete approximation of the continuous dynamics. (3) Scheduling of batch plants. For plants that are operated in a discontinuous fashion, the timing and sequencing of the operations are very important for the efficient use of the equipment. This leads to large mixed-integer optimization problems. For a typical example, we show how the process and the constraints can be modeled and describe an efficient solution algorithm.

Worst-case utilization bound for EDF scheduling on real-time multiprocessor systems

Abstract: Presents the utilization bound for earliest deadline first (EDF) scheduling on homogeneous multiprocessor systems with partitioning strategies. Assuming that tasks are pre-emptively scheduled on each processor according to the EDF algorithm, and allocated according to the first-fit (FF) heuristic, we prove that the worst-case achievable utilization is 0.5(n+1), where n is the number of processors. This bound is valid for arbitrary utilization factors. Moreover, if all the tasks have utilization factors under a value /spl alpha/, the previous bound is raised, and the new utilization bound considering /spl alpha/ is calculated. In addition, we prove that no uniprocessor scheduling algorithm/allocation algorithm pair can provide a higher worst-case achievable utilization than that of EDF-FF. Finally, simulation provides the average-case achievable utilization for EDF-FF.

Scheduling with Inserted Idle Time: Problem Taxonomy and Literature Review

Abstract: In the context of production scheduling, inserted idle time (IIT) occurs whenever a resource is deliberately kept idle in the face of waiting jobs. IIT schedules are particularly relevant in multimachine industrial situations where earliness costs and/or dynamically arriving jobs with due dates come into play. We provide a taxonomy of environments in which IIT scheduling is relevant, review the extant literature on IIT scheduling, and identify areas of opportunity for future research.

Scheduling under Fuzziness

Abstract: Fuzzy Knowledge Representation in Scheduling: I.B. Turksen, M.H.F. Zarandi, M. Dudzic: Caster Scheduling System Analysis with Fuzzy Technology.- M. Litoiu, R. Tadei: Dynamic Scheduling on Distributed Real-Time Systems by Self-Learning Fuzzy Algorithms.- Fuzzy Constraints in Scheduling: H. Fagier, C. Thierry: The Use of Possibilistic Decision Theory in Manufacturing, Planning and Control: Recent Results in Fuzzy Master Production Scheduling.- P. Fortemps: Introducing Flexibility in Scheduling: The Preference Approach.- H. Ishii: Scheduling Problems with Fuzzy Constraints.- H. Ishibuchi, T. Murata: Flowshop Scheduling with Fuzzy Duedate and Fuzzy Processing Time.- Fuzzy Uncertainty in Scheduling: G. Adamopoulos, C.P. Pappis, N.I. Karacapilidis: A Methodology for Solving a Range of Scheduling Problems under Uncertainty.- S. Chanas, A. Kasperski, D. Kuchta: Two Approaches to Fuzzy Flow Shop Problem.- M. Hapke, R. Slowinski: Fuzzy Set Approach to Multi-Objective and Multi-Mode Project Scheduling under Uncertainty.- M. Vlach: Single Machine Scheduling under Fuzziness.- L. Geneste, B. Grabot, P. Moutarlier: Scheduling of Heterogeneous Data Using Fuzzy Logic in a Customer-Subcontractor Context.- N. Kubota, T. Fukuda: Virus-Evolutionary Genetic Algorithm for Sequencing Jobs in Fuzzy Environment.- N.I. Karacapilidis, C.P. Pappis, G. Adamopulos: Fuzzy Set Approaches to Lot Sizing.

Dynamic Scheduling and Division of Labor in Social Insects

Abstract: A method for assigning tasks or resources, based on a model of division of labor in social insects, is introduced and applied to a dynamic flow shop scheduling problem. The problem consists of assigning trucks to paint booths in a truck facility to minimize total makespan and the number of paint flushes. Similarities between the ant-based approach and a market-based approach are highlighted. Both systems are able to adapt well to changing conditions.

A task duplication based scheduling algorithm for heterogeneous systems

Abstract: Optimal scheduling of tasks of a directed acyclic graph (DAG) onto a set of processors is a strong NP-hard problem. In this paper we present a scheduling scheme called TDS to schedule tasks of a DAG onto a heterogeneous system. This models a network of workstations, with processors of varying computing power. The primary objective of this scheme is to minimize schedule length and scheduling time itself. The existing task duplication based scheduling scheme is primarily done for totally homogeneous systems. We compare the performance of this algorithm with an existing scheduling scheme for heterogeneous processors called BIL. In initial simulations TDS has been observed to generate scheduling lengths shorter than that of BIL, for communication-to-computation cost ratios (CCR) of 0.2 to 1. Moreover TDS is far more superior than BIL as far as scheduling time is concerned.

On pipelining dynamic instruction scheduling logic

Abstract: A machine's performance is the product of its IPC (Instructions Per Cycle) and clock frequency. Recently, S. Palacharla et al. (1997) warned that the dynamic instruction scheduling logic for current machines performs an atomic operation. Either you sacrifice IPC by pipelining this logic, thereby eliminating its ability to execute dependent instructions in consecutive cycles. Or you sacrifice clock frequency by not pipelining it, performing this atomic operation in a single long cycle. Both alternatives are unacceptable for high performance. The paper offers a third, acceptable, alternative: pipelined scheduling with speculative wakeup. This technique pipelines the scheduling logic without eliminating its ability to execute dependent instructions in consecutive cycles. With this technique, you sacrifice little IPC, and no clock frequency. Our results show that on the SPECint95 benchmarks, a machine using this technique has an average IPC that is 13% greater than the IPC of a baseline machine that pipelines the scheduling logic but sacrifices the ability to execute dependent instructions in consecutive cycles, and within 2% of the IPC of a conventional machine that uses single cycle scheduling logic.