The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The quality of service is one of challenges posed by the Cloud Computing. This issue plays an important role in making the Cloud services acceptable to customers, denotes the levels of performance, reliability, and availability offered by Cloud services. Literature has reported many implementations for measuring and ensuring QoS in Cloud Computing systems to achieve better results and meet the needs...
Limited power budgets will be one of the biggest challenges for deploying future exascale supercomputers. One of the promising ways to deal with this challenge is hardware overprovisioning, that is, installingmore hardware resources than can be fully powered under a given power limit coupled with software mechanisms to steer the limited power to where it is needed most. Prior research has demonstrated...
Workflows are a widely used abstraction for describing large scientific applications and running them on distributed systems. However, most workflow systems have been silent on the question of what execution environment each task in the workflow is expected to run in. Consequently, a workflow may run successfully in the environment it was created, but fail on other platforms due to the differences...
Virtualization technology not only improves the utilization rate of server resources effectively, but also realizes resource restructuring management, so as to meet the diversity of different user's needs. Cloud computing technology can be widely used depends on the virtualized resource scheduling can timely and reliably guarantee user service quality. So efficient and flexible resource scheduling...
In a cloud environment, uncertainty and resource dispersion lead to problems with resource allocation due, for instance, to heterogeneity, dynamism, and failures. Unfortunately, existing resource management techniques, frameworks, and mechanisms are insufficient to handle these environments, applications, and resource behaviors. To provide efficient workload performance and applications, these issues...
In this paper we investigate the general problem of controlling a scientic workflow service in termsof data management. We focus on the data managementproblem for the RedisDG scientific workflow engine.RedisDG is based on the Publish/Subscribe paradigmfor the interaction between the different componentsof the system, hence new issues appear for scheduling. Indeed, the Publish/Subscribe paradigm utilization...
The world is driven by data intensive applications and eventually volume of data is generated out of these applications. These data do not yield benefits in its native form. It requires a different mechanism to collect, store, process and derive insights from these data. Apache Hadoop is one of the open source frameworks intended for this purpose. Apache Hadoop provides mechanism to distribute the...
For commercial software in scientific and engineering computing, software licenses are needed when running them in high performance computing systems. Usually, there is a constraint for the number of software licenses. With the traditional software licenses management approaches, there is a prominent issue. The jobs will fail immediately without available software licenses. However, the existing job...
Current processors provide a variety of different processing units to improve performance and power efficiency. For example, ARM's big.LITTLE, AMD's APUs, and Oracle's M7 provide heterogeneous processors, on-die GPUs, and on-die accelerators. However, the performance experienced by programs using these processing units can vary widely due to contention from multiprogramming, thermal constraints and...
Modern latency-critical online services often rely on composing results from a large number of server components. Hence the tail latency (e.g. The 99th percentile of response time), rather than the average, of these components determines the overall service performance. When hosted on a cloud environment, the components of a service typically co-locate with short batch jobs to increase machine utilizations,...
The Mnemos resource management and scheduling architecture uses portfolio scheduling, topology-aware virtual-resource management, and state information to self-adapt to significant workload changes and to analyze risks. Simulations with real-world workload traces reveal the potential for significant cost savings.
Hadoop MapReduce is one of the largely used platforms for large scale data processing. Hadoop cluster has machines with different resources, including memory size, CPU capability and disk space. This introduces challenging research issue of improving Hadoop's performance through proper resource provisioning. The work presented in this paper focuses on optimizing job scheduling in Hadoop. Workload...
PT is a lightweight job scheduler based on client-server architecture with remote interfaces. PTServer, the server-side of PT, is designed as an open service running on the multiprocessor system to collaborate with any PTClient, the client-side of PT, on top of PTComer protocol. In PT, we call once execute of program as a task and several tasks formed into a job. The two functionality PT need to implement...
Cloud platforms are becoming more prevalent in every computational domain, particularly in e-Science. A typical scientific workload will have a long execution time or be data intensive. Providing an execution environment for these applications, which belong to different tenants, has to deal with the horizontal scaling of execution flows (i.e. threads) and an effective allocation of resources that...
Today's extensive business process landscapes make it necessary to handle the execution of a large number of workflows. Especially if workflow steps require the invocation of resource-intensive applications or a large number of applications needs to be carried out concurrently, process owners may have to allocate extensive computational resources, leading to high fixed costs. Instead, process owners...
Scientific workflow management systems have been around for many years and provide essential support such as management of data and task dependencies, job scheduling and execution, provenance tracking, etc. to scientific computing. While we are entering into a """"big data"""" era, it is necessary for scientific workflow systems to integrate with Cloud platforms...
Job scheduling is a critical and complex task on large-scale supercomputers where a scheduling policy is expected to fulfill amorphous and sometimes conflicting goals from both users and system owners. Moreover, the effectiveness of a scheduling policy is dependent on workload characteristics which vary from time to time. Thus it is challenging to design a versatile scheduling policy that is effective...
Cloud computing is a cluster of virtual computing resources pool, converge all computing resources. Cloud platforms manage and schedule unified computing resources. It provides highly scalable and balance the terminals' services. In order to improve the cloud platform for resource utilization and the efficiency of task distribution, this paper proposes a method that the resource manager and scheduler...
Computational grids using heterogeneous and geographically distributed resources. The unreliable nature of grid infrastructure make the challenges of managing, scheduling, reliability arise. Effective utilization of computational resources is efficient scheduling of jobs and providing fault tolerance in a reliable manner. This paper addresses these problems by combining the checkpoint replication...
In this paper, we propose a taxonomy that characterizes and classifies different components of autonomic application management in Grids. We also survey several representative Grid systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the similarities and differences of state-of-the-art technologies utilized in autonomic...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.