Task Scheduling for Multiprocessor Systems Using Queuing Theory

This research focuses on comparing different multi-processor task scheduling algorithms. Each algorithm has been simulated using one of queuing theory models in Operations Research (OR) science to evaluate its behavior and efficiency. The comparison includes an analysis of the behavior of central processing unit (CPU) when receiving number of jobs at four random job duration patterns that are; (random, ascending, descending, and volatile low-high). Microsoft Excel 2010 was used to form the data of each case, and the result shows convergence and divergence among the studied algorithms at different patterns. Also it has been found that the Fleischer algorithm is very efficient in enhancing and minimizing the waiting duration for each job at the total job queue of the CPU. Keywords: Operations Research, Queuing Theory, Multiprocessor, Scheduling Algorithms, Simulation

Algoritmos online para escalonamento de tarefas em sistemas multiprocessados

Trabalho de Conclusão de Curso (Graduação)O escalonamento de processos é uma atividade de grande importância para garantir que os sistemas computacionais trabalhem de forma otimizada. Diversos algoritmos foram estabelecidos para resolver este problema de maneira a realizar uma distribuição equitativa das tarefas entre as máquinas disponíveis para executá-las. Existem diversas métricas de avaliação que auxiliam a determinar se a solução proposta por esses algoritmos podem ser aplicadas ao escopo do problema analisado, dentre as quais podemos citar o Makespan e a utilização média. Este trabalho possui o objetivo de implementar e avaliar três algoritmos heurísticos para solucionar o problema do escalonamento de processos: List-scheduling, Random e Round-robin. Resultados mostraram que o List-scheduling apresentou a melhor solução para este problema enquanto que o Random apresentou a pior solução. Um detalhe importante observado foi que os algoritmos List-scheduling e Round-robin produzem o mesmo resultado com tarefas ordenadas por sua carga em ordem crescente

Machine Scheduling Performance with Maintenance and Failure

In manufacturing control, machine scheduling research has mostly dealt with problems either without maintenance or with deterministic maintenance when no failure can occur. This can be unrealistic in practical settings. In this work, an experimental model is developed to evaluate the effect of corrective and preventive maintenance schemes on scheduling performance in the presence of machine failure where the scheduling objective is to minimize schedule duration. We show that neither scheme is clearly superior, but that the applicability of each depends on several system parameters as well as the scheduling environment itself. Further, we show that parameter values can be chosen for which preventive maintenance does better than corrective maintenance. The results provided in this study can be useful to practitioners and to system or machine administrators in manufacturing and elsewhere. (c) 2006 Elsevier Ltd. All rights reserved

New utilization criteria for online scheduling

In the classical scheduling problems, it has been assumed that complete knowledge of the problem was available when it was to be solved. However, scheduling problems in the real world face the possibility of the lack of the knowledge. Uncertainties frequently encountered in scheduling environments include the appearance of new jobs and unknown processing times. In this work, we take into account these realistic issues. This thesis deals with the problem of non-preemptive scheduling independent jobs on m identical parallel machines. In our online model, the jobs are submitted over time non-clairvoyantly. Therefore, the processing times of the jobs are unknown until they complete. Further, we assume that the ratio of weight to processing time is equal for all jobs, that is, all jobs have the same priorities. The jobs are assigned to the machines in a nondelay fashion. Our main scheduling objective is to maximize the utilization of the system. We show that the commonly used makespan criterion usually cannot reflect the true utilization of this kind of online scheduling problems. For this reason, it is very important to find another criterion capable of evaluating system utilization. Therefore, we introduce two new alternative criteria that more accurately capture the utilization of the machines. Moreover, we derive competitive factors for both criteria. Those competitive factors are tight for one criterion and almost tight for the other. Finally, we present an experimental investigation to evaluate the performance of the nondelay online algorithm with respect to our criteria. The experimental results show the confirmation of our theoretical results

Online scheduling for real-time multitasking on reconfigurable hardware devices

Nowadays the ever increasing algorithmic complexity of embedded applications requires the designers to turn towards heterogeneous and highly integrated systems denoted as SoC (System-on-a-Chip). These architectures may embed CPU-based processors, dedicated datapaths as well as recon gurable units. However, embedded SoCs are submitted to stringent requirements in terms of speed, size, cost, power consumption, throughput, etc. Therefore, new computing paradigms are required to ful l the constraints of the applications and the requirements of the architecture. Recon gurable Computing is a promising paradigm that provides probably the best trade-o between these requirements and constraints. Dynamically recon gurable architectures are their key enabling technology. They enable the hardware to adapt to the application at runtime. However, these architectures raise new challenges in SoC design. For example, on one hand, designing a system that takes advantage of dynamic recon guration is still very time consuming because of the lack of design methodologies and tools. On the other hand, scheduling hardware tasks di ers from classical software tasks scheduling on microprocessor or multiprocessors systems, as it bears a further complicated placement problem. This thesis deals with the problem of scheduling online real-time hardware tasks on Dynamically Recon gurable Hardware Devices (DRHWs). The problem is addressed from two angles : (i) Investigating novel algorithms for online real-time scheduling/placement on DRHWs. (ii) Scheduling/Placement algorithms library for RTOS-driven Design Space Exploration (DSE). Regarding the first point, the thesis proposes two main runtime-aware scheduling and placement techniques and assesses their suitability for online real-time scenarios. The first technique discusses the impact of synthesizing, at design time, several shapes and/or sizes per hardware task (denoted as multi-shape task), in order to ease the online scheduling process. The second technique combines a looking-ahead scheduling approach with a slots-based recon gurable areas management that relies on a 1D placement. The results show that in both techniques, the scheduling and placement quality is improved without signi cantly increasing the algorithm time complexity. Regarding the second point, in the process of designing SoCs embedding recon gurable parts, new design paradigms tend to explore and validate as early as possible, at system level, the architectural design space. Therefore, the RTOS (Real-Time Operating System) services that manage the recon gurable parts of the SoC can be re fined. In such a context, gathering numerous hardware tasks scheduling and placement algorithms of various complexity vs performance trade-o s in a kind of library is required. In this thesis, proposed algorithms in addition to some existing ones are purposely implemented in C++ language, in order to insure the compatibility with any C++/SystemC based SoC design methodology.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

An Experimental Study of Online Scheduling Algorithms

We present the first comprehensive experimental study of online algorithms for Graham's scheduling problem. Graham's scheduling problem is a fundamental problem in scheduling theory where a sequence of jobs has to be scheduled on m identical parallel machines so as to minimize the makespan. Graham gave an elegant algorithm that is (2 - 1/m)-competitive. Recently a number of new online algorithms were developed that achieve competitive ratios around 1.9. Since competitive analysis can only capture the worst case behavior of an algorithm a question often asked is: Are these new algorithms geared only towards a pathological case or do they perform better in practice, too? We address this question by analyzing the algorithms on various job sequences. We have implemented a general testing environment that allows a user to generate jobs, execute the algorithms on arbitrary job sequences and obtain a graphical representation of the results. In our actual tests, we analyzed the al..