622 research outputs found
Mapping of SLA-Based Workflows with Light Communication onto Grid Resources
Service Level Agreements (SLAs) are currently one of the
major research topics in Grid Computing. Among those system compo-
nents that support SLA-aware Grid jobs, the SLA mapping mechanism
has an important position. It is responsible for assigning sub-jobs of
the work
ow to Grid resources in a way that meets the user's dead-
line and minimizes costs. Assuming many dierent kinds of sub-jobs and
resources, the process of mapping an SLA-based work
ow with light
communication denes an unfamiliar and dicult problem. This paper
presents a solution to this problem. The quality and eciency of the
algorithm is validated through performance measurements
Mapping Light Communication SLA-Based Workflows onto Grid Resources with Parallel Processing Technology
Service Level Agreements (SLAs) are currently one of the
major research topics in Grid Computing. Amongmany system
components for supporting of SLA-aware Grid-based
workflows, the SLA mapping module receives an important
position. Mapping light communication workflows is
one main part of the mapping module. With the previously
proposed mapping algorithm, the mapping module may become
the bottleneck of the system when many requests come
in a short period of time. This paper presents a parallel
mapping algorithm for light communication SLA-based
workflows, which can cope with the problem. Performance
measurements deliver evaluation results on the quality of
the method
Cloud computing resource scheduling and a survey of its evolutionary approaches
A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon
Mapping Heavy Communication SLA-based Workflows onto Grid Resources with Parallel Processing Technology
Service Level Agreements (SLAs) are currently one of the
major research topics in Grid Computing. Amongmany system
components for supporting of SLA-aware Grid jobs, the
SLA mapping module holds an important position and the
capability of the mapping module depends on the runtime of
the mapping algorithm. With the previously proposed mapping
algorithm, the mapping module may develop into the
bottleneck of the system if many requests come in during a
short period of time. This paper presents a parallel mapping
algorithm to map heavy communication SLA-based
workflow onto Grid resources which can cope with the problem.
Performance measurements thereby deliver evaluation
results showing the quality of the method
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GRIDCC: Real-time workflow system
The Grid is a concept which allows the sharing of resources between distributed communities, allowing each to progress towards potentially different goals. As adoption of the Grid increases so are the activities that people wish to conduct through it. The GRIDCC project is a European Union funded project addressing the issues of integrating instruments into the Grid. This increases the requirement of workflows and Quality of Service upon these workflows as many of these instruments have real-time requirements. In this paper we present the workflow management service within the GRIDCC project which is tasked with optimising the workflows and ensuring that they meet the pre-defined QoS requirements specified upon them
Concepts and algorithms of mapping Grid-based workflow to resources within an SLA context
With the popularity of Grid-based workflow, ensuring the Quality of
Service (QoS) for workflow by Service Level Agreements (SLAs) is an emerging
trend in the business Grid. Among many system components for supporting SLAaware
Grid-based workflow, the SLA mapping mechanism is allotted an important
position as it is responsible for assigning sub-jobs of the workflow to Grid resources
in a way that meets the user's deadline and minimizes costs. With many different
kinds of sub-jobs and resources, the process of mapping a Grid-based workflow
within an SLA context defines an unfamiliar and difficult problem. To solve this
problem, this chapter describes related concepts and mapping algorithms
Joint Elastic Cloud and Virtual Network Framework for Application Performance-cost Optimization
International audienceCloud computing infrastructures are providing resources on demand for tackling the needs of large-scale distributed applications. To adapt to the diversity of cloud infras- tructures and usage, new operation tools and models are needed. Estimating the amount of resources consumed by each application in particular is a difficult problem, both for end users who aim at minimizing their costs and infrastructure providers who aim at control- ling their resources allocation. Furthermore, network provision is generally not controlled on clouds. This paper describes a framework automating cloud resources allocation, deploy- ment and application execution control. It is based on a cost estimation model taking into account both virtual network and nodes managed by the cloud. The flexible provisioning of network resources permits the optimization of applications performance and infrastructure cost reduction. Four resource allocation strategies relying on the expertise that can be cap- tured in workflow-based applications are considered. Results of these strategies are confined virtual infrastructure descriptions that are interpreted by the HIPerNet engine responsible for allocating, reserving and configuring physical resources. The evaluation of this framework was carried out on the Aladdin/Grid'5000 testbed using a real application from the area of medical image analysis
Optimizing the Execution Time of the SLA-Based Workflow in the Grid with Parallel Processing Technology
Service Level Agreements (SLAs) is currently one of the
major research topics in Grid Computing. Among many
system components for the supporting of SLA-aware Gridbased
workflow, the SLA mapping module receives important
positions. Optimizing execution time is an important
task of the mapping module as it helps in finding out a feasible
solution when the Grid is busy or by eliminating the
negative effects of the error. With the previously proposed
algorithm for optimizing the execution time of the workflow,
the mapping module may, when many requests come in a
short period of time, become the bottleneck of the system.
This paper presents a parallel mapping algorithm for optimizing
the execution time of the workflow, which can cope
with the problem. Performance measurements deliver evaluation
results on the quality of the method
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