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Reproducibility of the execution of scientific applications on parallel and distributed systems is a growing interest, underlying the trustworthiness of the experiments and the conclusions derived from experiments. Dynamic loop scheduling (DLS) techniques are an effective approach towards performance improvement of scientific applications via load balancing. These techniques address algorithmic and...
Reproducibility of the execution of scientific applications on parallel and distributed systems is a growing concern, underlying the trustworthiness of the experiments and the conclusions derived from experiments. Dynamic loop scheduling (DLS) techniques are an effective approach towards performance improvement of scientific applications via load balancing. These techniques address algorithmic and...
Scheduling is one of the most important issues in executing tasks in grid systems. A data grid mainly deals with sharing and managing large amounts of distributed data in executing data-intensive applications. It is primarily a solution to satisfy the requirements of data-intensive tasks processing. OptorSim is a useful open source simulation tool for data grids. In this paper a new two-step data-intensive...
In this paper, we study the dynamics of coupled speed scaling systems, in which service rate is a function of system occupancy. We focus on both Processor Sharing (PS) and Shortest Remaining Processing Time (SRPT) as scheduling disciplines, and study their speed scaling dynamics under heavy load. Using a combination of Markov chain analysis and discrete-event simulation, we identify several important...
Workflows offer a great potential for enacting co-related jobs in an automated manner. This is especially desirable when workflows are large or there is a desire to run a workflow multiple times. Much research has been conducted in reducing the make span of running workflows and maximising the utilisation of the resources they run on, with some existing research investigates how to reduce the energy...
This paper studies the performance of a distributed system. In particular, our work focuses on the study and comparison of job scheduling techniques in a cluster that could be part of a computational Grid. We examine two different job allocation policies, one static and one dynamic, and three job scheduling policies combined together. The performance of different scheduling schemes is compared over...
To study scientific application different computing paradigm used. Simulation of tool base Grid infrastructure plays its roll for study of grid base computation. We introduce the here Grid computing paradigm for resource coordination over the global computation world. Resources management and scheduling of applications in such large-scale distributed systems is a complex undertaking in case of Grid...
Computing intensive applications are an important family of applications in distributed computing domain. They have been object of study using different distributed computing paradigms and infrastructures. Such applications distinguish for their demanding needs for CPU computing, independently of the amount of data associated with the problem instance. Among computing intensive applications, there...
A proper scheduling algorithm is critical for the performance of distributed systems. One of task scheduling algorithms for parallel and distributed systems is gang scheduling. In this paper we study gang scheduling performance in the presence of soft real-time periodic jobs which can tolerate deadline misses by bounded amounts. We employ a simulation model to address performance issues associated...
Simulation is one of the most popular evaluation methods in scientific workflow studies. However, existing workflow simulators fail to provide a framework that takes into consideration heterogeneous system overheads and failures. They also lack the support for widely used workflow optimization techniques such as task clustering. In this paper, we introduce WorkflowSim, which extends the existing CloudSim...
Auxiliary noise, injected in active noise control (ANC) system for on-line secondary path modeling (SPM), contributes to the residual error (which we want to minimize). In this paper, two new schemes for controlling the auxiliary noise injection are proposed. The first method is ON/OFF control in which an additional fixed filter is used to temporarily hold the tap-weights of the adaptive on-line SPM...
The aim of this work is to describe the design, implementation and evaluation of an e-learning course focused on scheduling jobs in a computer grid. These topics belong to applied informatics master's study program. Themes of grid scheduling are part of courses, term and research projects. Our course titled Research project uses inter-subject relations among distributed operating systems, optimization,...
The use of meta-heuristics for designing efficient Grid schedulers is currently a common approach. One issue related to Grid based schedulers is their evaluation under different Grid configurations, such as dynamics of tasks and machines, task arrival, scheduling policies, etc. In this paper we present a web application that interfaces the final user with several meta-heuristics based Grid schedulers...
The flow shop scheduling problem is a branch of production scheduling, which is among the hardest combinatorial optimization problem, and represents an important area in production scheduling. In this paper, a new effective hybrid algorithm is proposed which is based on plant growth simulation algorithm for permutation flow shop scheduling with the criterion to minimize the maximum completion time...
Simulation can be an approximate performance evaluation method of real-time scheduling strategies. This method is useful when the analytical evaluation is too complex to be put in practice. In this paper we use simulation to evaluate the performance of Rate Monotonic and FIFO scheduling algorithms in different multiprocessor scheduling approaches. We present the design of our real-time scheduling...
Cloud computing aims to give users virtually unlimited pay-per-use computing resources without the burden of managing the underlying infrastructure. We claim that, in order to realize the full potential of cloud computing, the user must be presented with a pricing model that offers flexibility at the requirements level, such as a choice between different degrees of execution speed and the cloud provider...
Future systems will have to support multiple and concurrent dynamic compute-intensive applications, while respecting real-time and energy consumption constraints. With the increase in the design complexity of MPSoC architectures that must support these constraints, flexible and accurate simulators become a necessity for exploring the vast design space solutions. In this paper, we present an asymmetric...
While volunteer computing (VC) systems reach the most powerful computing platforms, they still have the problem of guaranteeing computational correctness, due to the inherent unreliability of volunteer participants. Spot-checking technique, which checks each participant by allocating spotter jobs, is a promising approach to the validation of computation results. The current spot-checking technique...
Multiprocessor task scheduling is a well known NP-hard problem and numerous methods have been proposed to optimally solve it. The objective is makespan minimization, i.e. we want the last task to complete as early as possible. Simulated Annealing (SA) has been considered a very good tool for complex nonlinear optimization problem, such as multiprocessor task scheduling. However, a major disadvantage...
If cluster C1 consists of computers with a faster mean speed than the computers in cluster C2, does this imply that cluster C1 is more productive than cluster C2? What if the computers in cluster C1 have the same mean speed as the computers in cluster C2: is the one with computers that have a higher variance in speed more productive? Simulation experiments are performed to explore the above questions...
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