In this work we consider a problem from the field of power- and energy-aware scheduling, in which a set of batteries have to be charged in a minimum time. The formulated problem is to schedule independent and nonpreemptable jobs to minimize the schedule length, where each job requires some amount of power and consumes a certain amount of energy during its processing. We assume that the power demand of each job linearly decreases with time, as it is the case when Li-ion batteries are being charged. For the assumed job model we prove that each next job should be started as soon as the required amount of power is available. Basing on the proven theorem we formulate a procedure generating a minimum-length schedule for an assumed order of jobs. We also analyze the case of identical jobs, and show some interesting properties of this case.
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In many distributed computing systems, aspects related to security are getting more and more relevant. Security is ubiquitous and could not be treated as a separated problem or a challenge. In our opinion it should be considered in the context of resource management in distributed computing environments like Grids and Clouds, e.g. scheduled computations can be much delayed because of cyber-attacks, inefficient infrastructure or users valuable and sensitive data can be stolen even in the process of correct computation. To prevent such cases there is a need to introduce new evaluation metrics for resource management that will represent the level of security of computing resources and more broadly distributed computing infrastructures. In our approach, we have introduced a new metric called reputation, which simply determines the level of reliability of computing resources from the security perspective and could be taken into account during scheduling procedures. The new reputation metric is based on various relevant parameters regarding cyber-attacks (also energy attacks), administrative activities such as security updates, bug fixes and security patches. Moreover, we have conducted various computational experiments within the Grid Scheduling Simulator environment (GSSIM) inspired by real application scenarios. Finally, our experimental studies of new resource management approaches taking into account critical security aspects are also discussed in this paper.
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In this work we consider a problem of scheduling preemptable, independent jobs, characterized by the fact that their processing speeds depend on the amounts of a continuous, renewable resource allocated to jobs at a time. Jobs are scheduled on parallel, identical machines, with the criterion of minimization of the schedule length. Since two categories of resources occur in the problem: discrete (set of machines) and continuous, it is generally called a discrete-continuous scheduling problem. The model studied in this paper allows the total available amount of the continuous resource to vary over time, which is a practically important generalization that has not been considered yet for discrete-continuous scheduling problems. For this model we give some properties of optimal schedules on a basis of which we propose a general methodology for solving the considered class of problems. The methodology uses a two-phase approach in which, firstly, an assignment of machines to jobs is defined and, secondly, for this assignment an optimal continuous resource allocation is found by solving an appropriate mathematical programming problem. In the approach various cases are considered, following from assumptions made on the form of the processing speed functions of jobs. For each case an iterative algorithm is designed, leading to an optimal solution in a finite number of steps.
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In this paper, discrete-continuous project scheduling problems with preemptable activities are considered. In these problems, activities of a project simultaneously require discrete and continuous resources for their execution. The activities are preemptable, and the processing rate of each activity is a continuous, increasing function of the amount of a single continuous resource allotted to the activity at a time. The problem is to find a precedence- and discrete resource-feasible schedule and, simultaneously, continuous resource allocation that would minimize the project duration. Convex and concave processing rate functions are considered separately. We show that for convex functions the problem is simple, whereas for concave functions a special methodology has to be developed. We discuss the methodology for three cases of the problem: no discrete resource constraints, one discrete resource being a set of parallel, identical machines, and an arbitrary number of discrete resources. In each case we analyze separately independent and precedence-related activities. Some conclusions and directions for future research are given.
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Heterogeneous many-core computing resources are increasingly popular among users due to their improved performance over homogeneous systems. Many developers have realized that heterogeneous systems, e.g. a combination of a shared memory multi-core CPU machine with massively parallel Graphics Processing Units (GPUs), can provide significant performance opportunities to a wide range of applications. However, the best overall performance can only be achieved if application tasks are efficiently assigned to different types of processor units in time taking into account their specific resource requirements. Additionally, one should note that available heterogeneous resources have been designed as general purpose units, however, with many built-in features accelerating specific application operations. In other words, the same algorithm or application functionality can be implemented as a different task for CPU or GPU. Nevertheless, from the perspective of various evaluation criteria, e.g. the total execution time or energy consumption, we may observe completely different results. Therefore, as tasks can be scheduled and managed in many alternative ways on both many-core CPUs or GPUs and consequently have a huge impact on the overall computing resources performance, there are needs for new and improved resource management techniques. In this paper we discuss results achieved during experimental performance studies of selected task scheduling methods in heterogeneous computing systems. Additionally, we present a new architecture for resource allocation and task scheduling library which provides a generic application programming interface at the operating system level for improving scheduling polices taking into account a diversity of tasks and heterogeneous computing resources characteristics.
The problem of scheduling n tasks in a multiprocessor system with m processors to minimize the makespan is studied. Tasks are malleable, which means that a task can be executed by several processors at a time, its processing speed depends on the number of allocated processors, and a set of processors allocated to the same task can change over time. The processing speed of a task is a strictly increasing function of the number of processors allocated to this task. The earlier studies considered the case n ≤ m. This paper presents results for arbitrary n and m including characterizations of a feasible domain and an optimal solution, polynomial time algorithms for strictly increasing convex and concave processing speed functions, and a combinatorial exponential algorithm for arbitrary strictly increasing functions.
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The problem of scheduling workflow applications in a grid environment is considered. The problem is divided into two stages: (i) resource allocation, which consists in allocating distributed grid resources to tasks of a workflow in such a way that the resource demands of each task are satisfied, and (ii) scheduling performed by local grid schedulers. Grid resources are divided into computational and network resources. Computational and transmission workflow tasks are distinguished. A computational experiment is presented in order to show the importance of resource allocation, as well as examine the influence of the local scheduling policy. Certain conclusions and directions for future research are given.
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Specialized software, on-line tools and computational resources are very common in contemporary science. One of the exemplary domain is genomics – a new branch of science that developed rapidly in the last decade. As the genome research is very complex, it must be supported by professional informatics. In a microarray field the following steps cannot be performed without computational work: design of probes, quantitative analysis of hybridization results, post-processing, and finally data storage and management. Here, the general aspects of virtual laboratory systems are presented together with perspectives of their implementation in genomics in order to automate and facilitate this area of research.
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In the paper a model of job processing is presented where processing speed is related to the amount of power allotted to this job at a moment. Basic time-optimal results are showed assuming that energy is treated as a scarce doubly-constrained resource in a computer system. The proposed approach is applicable to the practical power management problems appearing in modem portable device systems.
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Grid simulation tools provide frameworks for simulating application scheduling in various Grid infrastructures. However, while experimenting with many existing tools, we have encountered two main shortcomings: (i) there are no tools for generating workloads, resources and events; (ii) it is difficult and time consuming to model different Grid levels, i.e. resource brokers, and local level scheduling systems. In this paper we present the Grid Scheduling Simulator (GSSIM), a framework that addresses these shortcomings and provides an easy-to-use Grid scheduling framework for enabling simulations of a wide range of scheduling algorithms in multi-level, heterogeneous Grid infrastructures. In order to foster more collaboration in the community at large, GSSIM is complemented with a portal (http://www.gssim.org) that provides a repository of Grid scheduling algorithms, synthetic workloads and benchmarks for use with GSSIM.
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In the paper we present two different models of Grid resource management problems: (i) Grid scheduling problems with no time characteristics available, and (ii) scheduling of jobs in presence of time characteristics achieved by using some prediction techniques, and resource reservation mechanisms. We focus on demonstrating how these two scenarios, which are important examples of Grid environments, can be modeled as multi-criteria decision support problems. We also discuss advantages and disadvantages of these models as well as practical applications.
Dark fibre networks are considered the key element of future research infrastructures. The ownership of fibre leads to the freedom of development, freedom of choice of technology and freedom of design for research networks, as well as virtually unlimited transmission capacity. This concept has been confirmed by the new design of the GÉANT2 [1] network, where majority of links will be based on dark fibre. At the same time, while the GÉANT2 network has been upgraded to a level of technology that allows multiple 10 Gbit/s connections between most of the GÉANT2 partners, many countries of Eastern Europe are still suffering from insufficient connectivity to the Internet. It is expected that a strong role in the development of pan-European research network can be played by so called “Cross Border Fibres” (CBF), owned and operated by NRENs. This paper provides an overview of the PIONIER infrastructure and the Porta Optica initiative, which aims to improve the connectivity of Eastern European NRENs to GÉANT2, using a CBF infrastructure.
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A problem of scheduling jobs on parallel, identical machines under an additional continuous resource to minimize the makespan is considered. Jobs are non-preemtable and independent, and all are available at the start of the process. The total amount of the continuous resource available at a time is limited, and the resource is a renewable one. Each job simultaneously requires for its processing a machine, and an amount (unknown in advance) of the continuous resource. Processing rate of a job depends on the amount of the resource allotted to this job at a time. The problem is to find a sequence of jobs on machines and, simultaneously, a continuous resource allocation that minimize the makespan. The tabu search metaheuristic is presented to attack the problem. Probabilistic implementations of tabu search are discussed and examined. A computational experiment is described, and the results obtained for the probabilistic version of tabu search are compared to optimal solutions. A few conclusions and final remarks are presented.
Przedstawiono tutaj problem szeregowania n niezależnych zadań w systemie procesorów równoległych. Zadania są elastyczne, tj. zadanie może być wykonywane przez kilka procesorów jednocześnie oraz prędkość wykonywania zadania jest nieliniową funkcją od ilości procesorów przydzielonych do niego. Całkowita liczba procesorów w systemie wynosi m i jest to górna granica liczby procesorów, które mogą być używane przez wszystkie zadania w tym samym czasie. Dodatkowym założeniem jest podzielność zadań oraz możliwość zmiany liczby procesorów przydzielonych do zadania w trakcie jego wykonywania. Celem jest znalezienie uszeregowania, dla którego czas zakończenia wszystkich zadań jest najkrótszy z możliwych. Prezentowany jest prosty algorytm o złożoności 0(n), rozwiązujący ten problem w przypadku, kiedy wszystkie funkcje prędkości wykonywania są wypukłe. Jeżeli funkcje te są wszystkie wklęsłe, przedstawiono algorytm pakowania prostokątów (PACK), który rozwiązuje ten problem w czasie wielomianowym.
EN
The problem of optimal scheduling n independent tasks on a parallel processor system is studied. The tasks are malleable, i.e. a task may be executed by several processors simultaneously and the processing speed of a task is a non-linear function of the number of processors allotted to it. The total number of processors is m and it is an upper bound on the number of processors that can be used by all the tasks simultaneously. It is assumed that the tasks are preemptable and the number of processors allotted to one task may change during its execution. The objective is to find a schedule for which the makespan, is minimized. An 0(n) algorithm is presented to solve this problem when all the processing speed functions are convex. If these functions are all concave the rectangles packing (PACK) algorithm is presented, which solves the problem in polynomial time.
W pracy rozważa się problem rozdziału zasobów z wieloma sposobami wykonywania czynności. Z terminem zakończenia każdej czynności związany jest dodatni przepływ gotówkowy. Celem jest znalezienie zasobowe i kolejnościowo dopuszczalnego uszeregowania, które maksymalizuje sumaryczną zaktualizowaną wartość netto wszystkich przepływów gotówkowych projektu. Zaproponowano dwa algorytmy metaheurystyczne: algorytm symulowanego wyżarzania oraz algorytm przeszukiwania tabu. Obszerny eksperyment obliczeniowy stanowi podstawę do porównania obydwu algorytmów.
EN
In this paper the multi-mode resource-constrained project scheduling problem with discounted cash flows is considered. A positive cash flow is associated with completion of each activity. The objective is the maximization of the net present value of all cash flows, subject to precedence and resource constraints. Local search metaheuristics: simulated annealing and tabu search are proposed to solve this problem. Both algorithms are compared on the basis of an extensive computational experiment.
Rozważane są problemy rozdziału zasobów z kryterium maksymalizacji zaktualizowanej wartości netto. Praca zawiera przegląd modeli i algorytmów dotyczących rozważanej klasy problemów szeregowania i jednocześnie jest próbą podsumowania aktualnego stanu badań w tym zakresie oraz ukazania na tym tle nowych kierunków badawczych.
EN
Project scheduling problems with the maximization of the net present value (NPV) criterion are considered. The paper surveys models and algorithms concerning this class of problems. The state-of-the-art in this area and the future research directions are presented.
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