3,768 research outputs found
Analysis and selection of the simulation environment
This document provides the initial report of the Simulation work package (Work Package 4,WP4) of the CATNETS project. It contains an analisys of the requirements for a simulation tool to be used in CATNETS and an evaluation of a number of grid and general purpose simulators with respect to the selected requirements. A reasoned choice of a suitable simulator is performed based on the evaluation conducted. -- Diese Arbeit analysiert die Anforderungen an eine Simulationsumgebung für die Analyse der Katallaxie. Anhand von Kennzahlen wird die Auswahl der Simulationsumgebung bestimmt.Grid Computing
Preliminary specification and design documentation for software components to achieve catallaxy in computational systems
This Report is about the preliminary specifications and design documentation for software components to achieve Catallaxy in computational systems. -- Die Arbeit beschreibt die Spezifikation und das Design von Softwarekomponenten, um das Konzept der Katallaxie in Grid Systemen umzusetzen. Eine Einführung ordnet das Konzept der Katallaxie in bestehende Grid Taxonomien ein und stellt grundlegende Komponenten vor. Anschließend werden diese Komponenten auf ihre Anwendbarkeit in bestehenden Application Layer Netzwerken untersucht.Grid Computing
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A survey of simulation techniques in commerce and defence
Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches
Analysis of simulation environment
In this paper the requirements for an ALN simulation environment are analysed, as needed in the CATNETS Project. A number of grid and general purpose simulators are evaluated regarding the identified requirements for simulating economical resource allocation mechanisms in ALNs. Subsequently a suitable simulator is chosen for usage in the CATNETS project. --CATNETS simulator,requirements analysis,simulator selection
Bulk Scheduling with the DIANA Scheduler
Results from the research and development of a Data Intensive and Network
Aware (DIANA) scheduling engine, to be used primarily for data intensive
sciences such as physics analysis, are described. In Grid analyses, tasks can
involve thousands of computing, data handling, and network resources. The
central problem in the scheduling of these resources is the coordinated
management of computation and data at multiple locations and not just data
replication or movement. However, this can prove to be a rather costly
operation and efficient sing can be a challenge if compute and data resources
are mapped without considering network costs. We have implemented an adaptive
algorithm within the so-called DIANA Scheduler which takes into account data
location and size, network performance and computation capability in order to
enable efficient global scheduling. DIANA is a performance-aware and
economy-guided Meta Scheduler. It iteratively allocates each job to the site
that is most likely to produce the best performance as well as optimizing the
global queue for any remaining jobs. Therefore it is equally suitable whether a
single job is being submitted or bulk scheduling is being performed. Results
indicate that considerable performance improvements can be gained by adopting
the DIANA scheduling approach.Comment: 12 pages, 11 figures. To be published in the IEEE Transactions in
Nuclear Science, IEEE Press. 200
Agent-based transportation planning compared with scheduling heuristics
Here we consider the problem of dynamically assigning vehicles to transportation orders that have di¤erent time windows and should be handled in real time. We introduce a new agent-based system for the planning and scheduling of these transportation networks. Intelligent vehicle agents schedule their own routes. They interact with job agents, who strive for minimum transportation costs, using a Vickrey auction for each incoming order. We use simulation to compare the on-time delivery percentage and the vehicle utilization of an agent-based planning system to a traditional system based on OR heuristics (look-ahead rules, serial scheduling). Numerical experiments show that a properly designed multi-agent system may perform as good as or even better than traditional methods
Decentralized Scheduling for Many-Task Applications in the Hybrid Cloud
While Cloud Computing has transformed how we solve many computing tasks, some scientific and many-task applications are not efficiently executed on cloud resources. Decentralized scheduling, as studied in grid computing, can provide a scalable system to organize cloud resources and schedule a variety of work. By measuring simulations of two algorithms, the fully decentralized Organic Grid, and the partially decentralized Air Traffic Controller from IBM, we establish that decentralization is a workable approach, and that there are bottlenecks that can impact partially centralized algorithms. Through measurements in the cloud, we verify that our simulation approach is sound, and assess the variable performance of cloud resources. We propose a scheduler that measures the capabilities of the resources available to execute a task and distributes work dynamically at run time. Our scheduling algorithm is evaluated experimentally, and we show that performance-aware scheduling in a cloud environment can provide improvements in execution time. This provides a framework by which a variety of parameters can be weighed to make job-specific and context-aware scheduling decisions. Our measurements examine the usefulness of benchmarking as a metric used to measure a node\u27s performance, and drive scheduling. Benchmarking provides an advantage over simple queue-based scheduling on distributed systems whose members vary in actual performance, but the NAS benchmark we use does not always correlate perfectly with actual performance. The utilized hardware is examined, as are enforced performance variations, and we observe changes in performance that result in running on a system in which different workers receive different CPU allocations. As we see that performance metrics are useful near the end of the execution of a large job, we create a new metric from historical data of partially completed work, and use that to drive execution time down further. Interdependent task graph work is introduced and described as a next step in improving cloud scheduling. Realistic task graph problems are defined and a scheduling approach is introduced. This dissertation lays the groundwork to expand the types of problems that can be solved efficiently in the cloud environment
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