Showing papers on "Scheduling (computing) published in 1995"

A scheduling model for reduced CPU energy

Abstract: The energy usage of computer systems is becoming an important consideration, especially for battery-operated systems. Various methods for reducing energy consumption have been investigated, both at the circuit level and at the operating systems level. In this paper, we propose a simple model of job scheduling aimed at capturing some key aspects of energy minimization. In this model, each job is to be executed between its arrival time and deadline by a single processor with variable speed, under the assumption that energy usage per unit time, P, is a convex function, of the processor speed s. We give an off-line algorithm that computes, for any set of jobs, a minimum-energy schedule. We then consider some on-line algorithms and their competitive performance for the power function P(s)=s/sup p/ where p/spl ges/2. It is shown that one natural heuristic, called the Average Rate heuristic, uses at most a constant times the minimum energy required. The analysis involves bounding the largest eigenvalue in matrices of a special type.

Efficient fair queueing using deficit round robin

Abstract: Fair queuing is a technique that allows each flow passing through a network device to have a fair share of network resources. Previous schemes for fair queuing that achieved nearly perfect fairness were expensive to implement: specifically, the work required to process a packet in these schemes was O(log(n)), where n is the number of active flows. This is expensive at high speeds. On the other hand, cheaper approximations of fair queuing that have been reported in the literature exhibit unfair behavior. In this paper, we describe a new approximation of fair queuing, that we call Deficit Round Robin. Our scheme achieves nearly perfect fairness in terms of throughput, requires only O(1) work to process a packet, and is simple enough to implement in hardware. Deficit Round Robin is also applicable to other scheduling problems where servicing cannot be broken up into smaller units, and to distributed queues.

Cilk: an efficient multithreaded runtime system

Abstract: Cilk (pronounced “silk”) is a C-based runtime system for multi-threaded parallel programming. In this paper, we document the efficiency of the Cilk work-stealing scheduler, both empirically and analytically. We show that on real and synthetic applications, the “work” and “critical path” of a Cilk computation can be used to accurately model performance. Consequently, a Cilk programmer can focus on reducing the work and critical path of his computation, insulated from load balancing and other runtime scheduling issues. We also prove that for the class of “fully strict” (well-structured) programs, the Cilk scheduler achieves space, time and communication bounds all within a constant factor of optimal.The Cilk runtime system currently runs on the Connection Machine CM5 MPP, the Intel Paragon MPP, the Silicon Graphics Power Challenge SMP, and the MIT Phish network of workstations. Applications written in Cilk include protein folding, graphic rendering, backtrack search, and the *Socrates chess program, which won third prize in the 1994 ACM International Computer Chess Championship.

Probabilistic diversification and intensification in local search for vehicle routing

Abstract: This article presents a probabilistic technique to diversify, intensify, and parallelize a local search adapted for solving vehicle routing problems. This technique may be applied to a very wide variety of vehicle routing problems and local searches. It is shown that efficient first-level tabu searches for vehicle routing problems may be significantly improved with this technique. Moreover, the solutions produced by this technique may often be improved by a postoptimization technique presented in this article, too. The solutions of nearly forty problem instances of the literature have been improved.

Characterization and generation of a general class of resource-constrained project scheduling problems

Abstract: This paper addresses the issue of how to generate problem instances of controlled difficulty. It focuses on precedence- and resource-constrained (project) scheduling problems, but similar ideas may be applied to other network optimization problems. It describes a network construction procedure that takes into account a) constraints on the network topology, b) a resource factor that reflects the density of the coefficient matrix, and c) a resource strength, which measures the availability of resources. The strong impact of the chosen parametric characterization of the problems is shown via an in depth computational study. Instances for the single- and multi-mode resource-constrained project scheduling problem are benchmarked by using the state of the art (branch and bound) procedures. The results provided, demonstrate that the classical benchmark instances used by several researchers over decades belong to the subset of the very easy ones. In addition, it is shown that hard instances, being far more smalle...

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 ANL/IBM SP Scheduling System

Abstract: During the past five years scientists discovered that modern UNIX workstations connected with ethernet and fiber networks could provide enough computational performance to compete with the supercomputers of the day. As this concept became increasingly popular, the need for distributed queuing and scheduling systems became apparent. Systems such as DQS from Florida State were developed and worked very well. Today, supercomputers, such as Argonne National Laboratory's IBM SP system, can provide more CPU and networking speed than can be obtained from these networks of workstations. These modern supercomputers look like clusters of workstations, however, so developers felt that the scheduling systems that were previously used on clusters of workstations should still apply. After trying to apply some of these scheduling systems to Argonne's SP environment, it became obvious that these two computer environments have very different scheduling needs. Recognizing this need and realizing that no one has addressed it, I developed a new scheduling system. The approach taken in creating this system was unique in that user input and interaction were encouraged throughout the development process. Thus, a scheduler was built that actually “worked” the way the users wanted it to work.

A dynamic priority assignment technique for streams with (m, k)-firm deadlines

Abstract: The problem of scheduling multiple streams of real-time customers, is addressed in this paper. The paper first introduces the notion of (m, k)-firm deadlines to better characterize the timing constraints of real-time streams. More specifically, a stream is said to have (m, k)-firm deadlines if at least m out of any k consecutive customers must meet their deadlines. A stream with (m, k)-firm deadlines experiences a dynamic failure if fewer than m out of any k consecutive customers meet their deadlines. The paper then proposes a priority-based policy for scheduling N such streams on a single server to reduce the probability of dynamic failure. The basic idea is to assign higher priorities to customers from streams that are closer to a dynamic failure so as to improve their chances of meeting their deadlines. The paper proposes a heuristic for assigning these priorities. The effectiveness of this approach is evaluated through simulation under various customer arrival and service patterns. The scheme is compared to a conventional scheme where all customers are serviced at the same priority level and to an imprecise computation model approach. The evaluation shows that substantial reductions in the probability of dynamic failure are achieved when the proposed policy is used.

Quality of service guarantees in virtual circuit switched networks

Abstract: We review some recent results regarding the problem of providing deterministic quality of service guarantees in slot-based virtual circuit switched networks. The concept of a service curve is used to partially characterize the service that virtual circuit connections receive. We find that service curves provide a convenient framework for managing the allocation of performance guarantees. In particular, bounds on end-to-end performance measures can be simply obtained in terms of service curves and burstiness constraints on arriving traffic. Service curves can be allocated to the connections, and we consider scheduling algorithms that can support the allocated service curves. Such an approach provides the required degree of isolation between the connections in order to support performance guarantees, without precluding statistical multiplexing. Finally, we examine the problem of enforcing burstiness constraints in slot-based networks. >

Scheduling and Load Balancing in Parallel and Distributed Systems

Abstract: Advances in hardware and software technologies have led to an increased interest in the use of large-scale parallel and distributed systems for database, real-time, defense, and large-scale commercial applications. One of the biggest system issues is developing effective techniques for the distribution of multiple program processes on multiple processors. This book discusses how to schedule the processes among processing elements to achieve the expected performance goals, such as minimizing execution time, minimizing communication delays, or maximizing resource utilization.

A reinforcement learning approach to job-shop scheduling

Abstract: We apply reinforcement learning methods to learn domain-specific heuristics for job shop scheduling. A repair-based scheduler starts with a critical-path schedule and incrementally repairs constraint violations with the goal of finding a short conflict-free schedule. The temporal difference algorithm TD(λ) is applied to tram a neural network to learn a heuristic evaluation function over states. This evaluation function is used by a one-step lookahead search procedure to find good solutions to new scheduling problems. We evaluate this approach on synthetic problems and on problems from a NASA space shuttle pay load processing task. The evaluation function is trained on problems involving a small number of jobs and then tested on larger problems. The TD scheduler performs better than the best known existing algorithm for this task--Zwehen's iterative repair method based on simulated annealing. The results suggest that reinforcement learning can provide a new method for constructing high-performance scheduling systems.

Implications of classical scheduling results for real-time systems

Abstract: Knowledge of complexity, fundamental limits and performance bounds-well known for many scheduling problems-helps real time designers choose a good design and algorithm and avoid poor ones. The scheduling problem has so many dimensions that it has no accepted taxonomy. We divide scheduling theory between uniprocessor and multiprocessor results. In the uniprocessor section, we begin with independent tasks and then consider shared resources and overload. In the multiprocessor section, we divide the work between static and dynamic algorithms. >

Scheduling groups of jobs on a single machine

Abstract: Economies of scale are fundamental to manufacturing operations. With respect to scheduling, this phenomenon manifests itself in efficiencies gained from grouping similar jobs together. This paper reviews the rapidly growing literature on single-machine scheduling models that incorporate benefits from job grouping. We focus on three basic models known as family scheduling with item availability, family scheduling with batch availability, and batch processing. We present known results and introduce new results, and we pay special attention to key theoretical properties and the use of these properties in optimization procedures.

Robust scheduling to hedge against processing time uncertainty in single-stage production

Abstract: Schedulers confronted with significant processing time uncertainty often discover that a schedule which is optimal with respect to a deterministic or stochastic scheduling model yields quite poor performance when evaluated relative to the actual processing times. In these environments, the notion of schedule robustness, i.e., determining the schedule with the best worst-case performance compared to the corresponding optimal solution over all potential realizations of job processing times, is a more appropriate guide to schedule selection. In this paper, we formalize the robust scheduling concept for scheduling situations with uncertain or variable processing times. To illustrate the development of solution approaches for a robust scheduling problem, we consider a single-machine environment where the performance criterion of interest is the total flow time over all jobs. We define two measures of schedule robustness, formulate the robust scheduling problem, establish its complexity, describe properties of the optimal schedule, and present exact and heuristic solution procedures. Extensive computational results are reported to demonstrate the efficiency and effectiveness of the proposed solution procedures.

Job Scheduling Under the Portable Batch System

Abstract: The typical batch queuing system schedules jobs for execution by a set of queue controls. The controls determine the queue from which jobs will be selected. Within each queue, jobs are typically selected in first-in, first-out (FIFO) order. This limits the set of scheduling policies available to a site.

A heuristic algorithm for a dial-a-ride problem with time windows, multiple capacities, and multiple objectives

Abstract: The paper describes a system for the solution of a static dial-a-ride routing and scheduling problem with time windows (DARPTW). The problem statement and initialization of the development project was made by the Copenhagen Fire-Fighting Service (CFFS). The CFFS needed a new system for scheduling elderly and disabled persons, involving about 50.000 requests per year. The problem is characterized by, among other things, multiple capacities and multiple objectives. The capacities refer to the fact that a vehicle may be equipped with e.g. normal seats, children seats or wheel chair places. The objectives relate to a number of concerns such as e.g. short driving time, high vehicle utilization or low costs. A solution algorithm REBUS based on an insertion heuristics was developed. The algorithm permits in a flexible way weighting of the various goals such that the solution reflects the user's preferences. The algorithm is implemented in a dynamic environment intended for on-line scheduling. Thus, a new request for service is treated in less than 1 second, permitting an interactive user interface.

A Continuous Time Mixed Integer Linear Programming Model for Short Term Scheduling of Multistage Batch Plants

Abstract: The problem of short term scheduling of batch plants consists of determining the optimal production policy for satisfying the production demands for different products at due dates and/or at the end of a given time horizon. The objective of the work is to propose an optimization model and solution method to the short term scheduling of batch plants with multiple stages which may contain equipment in parallel. A large scale mixed integer linear programming (MILP) model with continuous time domain representation is proposed that relies on the use of parallel time axes for units and tasks. Although in principle an LP-based branch and bound method can be used to solve the problem, there is a limitation when the instances become large. The first solution strategy that is proposed consists of the use of preordering constraints. Furthermore, a second strategy relies on a decomposition scheme for large systems which is based on the solution of an MILP model that minimizes total in process time in which assignments are determined and the subsequent solution of an LP to minimize earliness and to eliminate unnecessary setups. Several examples are presented, including a large real world problem, to illustrate the performance of the model and solution method

Chapter 2 Time constrained routing and scheduling

Abstract: Publisher Summary Time constrained routing and scheduling problems are encountered in a variety of industrial and service sector applications, ranging from logistics and transportation systems to material handling systems in manufacturing. The traveling salesman problem with time windows has applications in single and multiple vehicle problems. The vehicle routing problem with time windows has many industrial applications including those where dock availability is a bottleneck such as for distribution centers. This chapter describes the significant advances made in time constrained routing and scheduling. In terms of solution methodology capable of solving realistic size problems, this field has seen a natural progression from ad-hoc methods to simple heuristics, to optimization-based heuristics and recently optimal algorithms. The chapter discusses fixed schedule problems and develops in detail the Dantzig-Wolfe decomposition/column generation approach which will then be applied to many of the other problem types. The vehicle routing problem with time windows and several important problem variants including the multiple traveling salesman problems is explored. The chapter examines a unified framework for fleet and crew scheduling problems.

Goal-directed elaboration of requirements for a meeting scheduler: problems and lessons learnt

Abstract: Recently a number of requirements engineering languages and methods have flourished that not only address 'what' questions but also 'why', 'who' and 'when' questions. The objective of the paper is twofold: to assess the strengths and weaknesses of one of these methodologies on a nontrivial benchmark; and to illustrate and discuss a number of challenging issues that need to be addressed for such methodologies to become effective in supporting real, complex requirements engineering tasks. The problem considered here is that of a distributed meeting scheduler system; the methodology considered is the KAOS goal directed language and method. The issues raised from this case study include goal identification, the "deidelization" of unachievable goals, the handling of interfering goals, the impact of early formal reasoning, the merits of early reuse of abstract descriptions and categories, requirements traceability and the need to link requirements to retractable assumptions, and the potential benefits of hybrid acquisition strategies.

The generalized unit commitment problem

Abstract: The authors formulate a generalized version of the unit commitment problem that can treat minimum up- and down-time constraints, power flow constraints, line flow limits, voltage limits, reserve constraints, ramp limits, and total fuel and energy limits on hydro and thermal power generating units. They propose an algorithm for this problem, based on Lagrangian decomposition, and demonstrate the algorithm with reference to a simple model system. >

Lottery and stride scheduling: flexible proportional-share resource management

Abstract: This thesis presents flexible abstractions for specifying resource management policies, together with efficient mechanisms for implementing those abstractions. Several novel scheduling techniques are introduced, including both randomized and deterministic algorithms that provide proportional-share control over resource consumption rates. Such control is beyond the capabilities of conventional schedulers, and is desirable across a broad spectrum of systems that service clients of varying importance. Proportional-share scheduling is examined for several diverse resources, including processor time, memory, access to locks, and disk bandwidth. Resource rights are encapsulated by abstract, first-class objects called tickets. An active client consumes resources at a rate proportional to the number of tickets that it holds. Tickets can be issued in different amounts and may be transferred between clients. A modular currency abstraction is also introduced to flexibly name, share, and protect sets of tickets. Currencies can be used to isolate or group sets of clients, enabling the modular composition of arbitrary resource management policies. Two different underlying mechanisms are introduced to support these abstractions. Lottery scheduling is a novel randomized resource allocation mechanism. An allocation is performed by holding a lottery, and the resource is granted to the client with the winning ticket. Stride scheduling is a deterministic resource allocation mechanism that computes a representation of the time interval, or stride, that each client must wait between successive allocations. Stride scheduling cross-applies and generalizes elements of rate-based flow control algorithms designed for networks to dynamically schedule other resources such as processor time. A novel hierarchical stride algorithm is also introduced that achieves better throughput accuracy than prior schemes, and can reduce response-time variability for some workloads. The proposed techniques are compared and evaluated using a variety of quantitative experiments. Simulation results and prototype implementations for operating system kernels demonstrate flexible control over a wide range of resources and applications.

Allocation and scheduling of precedence-related periodic tasks

Abstract: This paper discusses a static algorithm for allocating and scheduling components of periodic tasks across sites in distributed systems. Besides dealing with the periodicity constraints, (which have been the sole concern of many previous algorithms), this algorithm handles precedence, communication, as well as replication requirements of subtasks of the tasks. The algorithm determines the allocation of subtasks of periodic tasks to sites, the scheduled start times of subtasks allocated to a site, and the schedule for communication along the communication channel(s). Simulation results show that the heuristics and search techniques incorporated in the algorithm are very effective. >

New strategies for assigning real-time tasks to multiprocessor systems

Abstract: Optimal scheduling of real-time tasks on multiprocessor systems is known to be computationally intractable for large task sets. Any practical scheduling algorithm for assigning real-time tasks to a multiprocessor system presents a trade-off between its computational complexity and its performance. In this study, new schedulability conditions are presented for homogeneous multiprocessor systems where individual processors execute the rate-monotonic scheduling algorithm. The conditions are used to develop new strategies for assigning real-time tasks to processors. The performance of the new strategies is shown to be significantly better than suggested by the existing literature. Under the realistic assumption that the load of each real-time task is small compared to the processing speed of each processor, it is shown that the processors can be almost fully utilized.

Determining End-to-End Delay Bounds in Heterogeneous Networks

Abstract: We define a class of Guaranteed Rate (GR) scheduling algorithms. The GR class includes Virtual Clock, Packet-by-Packet Generalized Processor Sharing and Self-Clocked Fair Queuing. For networks that employ scheduling algorithms belonging to GR, we present a method for determining an upper bound on end-to-end delay. The method facilitates determination of end-to-end delay bounds for a Variety of sources. We illustrate the method by determining end-to-end delay bounds for sources conforming to Leaky Bucket and exponentially bounded burstiness.

A Time Window Approach to Simultaneous Scheduling of Machines and Material Handling System in an FMS

Abstract: This paper exploits the interactions between the machine scheduling and the scheduling of the material handling system in an FMS by addressing them simultaneously. The material transfer between machines is done by a number of identical automated guided vehicles (AGVs) which are not allowed to return to the load/unload station after each delivery. This operating policy introduces an additional complexity to the problem because it results in sequence-dependent travel times for the deadheading trips between successive loaded trips of the AGVs. The problem is formulated as a nonlinear mixed integer programming model. Its objective is makespan minimization. The formulation consists of constraint sets of a machine scheduling subproblem and a vehicle scheduling subproblem which interact through a set of time window constraints for the material handling trip starting times. An iterative procedure is developed where, at each iteration, a new machine schedule is generated by a heuristic procedure, the operation com...

Scheduling Parallel Machines On-line

Abstract: The problem of scheduling jobs on parallel machines is studied when (1) the existence of a job is not known until its unknown release date and (2) the processing requirement of a job is not known until the job is processed to completion. Two general algorithmic techniques are demonstrated for converting existing polynomial-time algorithms that require complete knowledge about the input data into algorithms that need less advance knowledge. Information-theoretic lower bounds on the length of on-line schedules are proven for several basic parallel machine models, and that almost all of our algorithms construct schedules with lengths that either match or come within a constant factor of the lower bound.

System and method for scheduling service providers to perform customer service requests

Abstract: A scheduling system is disclosed for scheduling tasks for fulfilling a series of service requests. When each service request is received, a determination is made as to the amount of resources a task requires to provide the requested service. Further, a preferred time within which to perform the task is obtained from the requestor of the service request. For each service request, data for the estimated amount of resources and the preferred time are supplied, on a first-come-first-serve basis, to a scheduling component for solving a combinatorial optimization model which efficiently allocates a predetermined amount of resources for each time slot in a scheduling period by rearranging tasks for service requests previously received. The scheduling component provides for a service requestor, without regard to subsequently received service requests, a service time in which to perform the task for the requested service substantially immediately after the service request is made. Whenever possible, the service time coincides with the preferred time. Each previously received service request will have its related task performed within the service time provided to the requestor of the service request. The scheduling system is particularly useful in scheduling technician time for service calls received by customer representatives in the telecommunication and utility industries.

Scheduling batch processing machines with incompatible job families

Abstract: The problem of scheduling a single batch processing machine with incompatible job families was studied, where jobs of different families cannot be processed together in the same batch. First static problems where all jobs are available simultaneously were considered and showed that for a regular performance measure there will be no unnecessary partial batches. This allowed us to develop efficient optimal algorithms to minimize makespan (Cmax), maximum lateness (Lmax) and total weighted completion time and apply some of these results to problems with parallel identical batch processing machines. Then problems withdynamic job arrivals were considered and an efficient optimal algorithm for minimizing Cmax and several heuristics to minimize Lmax were provided. Computational experiments showed that the heuristics developed for the latter problem consistently improve on dispatching solutions in very reasonable CPU times.

Scheduling algorithm of data sampling times in the integrated communication and control systems

Abstract: Integrated communication and control systems (ICCS) consist of several distributed control processes which share a network medium. Performance of several feedback control loops in the ICCS is subject to the network-induced delays from sensor to controller and from controller to actuator. The network-induced delays are directly dependent upon the data sampling times of the control components which share a network medium. In this study, a scheduling algorithm of determining data sampling times is developed using the window concept, where the sampled data from the control components in the ICCS share a limited number of windows, so that the performance requirement of each control loop is satisfied as well as the utilization of network resources is considerably increased. The scheduling algorithm is verified by discrete-event/continuous-time simulation model of an example of ICCS. >