1,238 research outputs found
Cloudbus Toolkit for Market-Oriented Cloud Computing
This keynote paper: (1) presents the 21st century vision of computing and
identifies various IT paradigms promising to deliver computing as a utility;
(2) defines the architecture for creating market-oriented Clouds and computing
atmosphere by leveraging technologies such as virtual machines; (3) provides
thoughts on market-based resource management strategies that encompass both
customer-driven service management and computational risk management to sustain
SLA-oriented resource allocation; (4) presents the work carried out as part of
our new Cloud Computing initiative, called Cloudbus: (i) Aneka, a Platform as a
Service software system containing SDK (Software Development Kit) for
construction of Cloud applications and deployment on private or public Clouds,
in addition to supporting market-oriented resource management; (ii)
internetworking of Clouds for dynamic creation of federated computing
environments for scaling of elastic applications; (iii) creation of 3rd party
Cloud brokering services for building content delivery networks and e-Science
applications and their deployment on capabilities of IaaS providers such as
Amazon along with Grid mashups; (iv) CloudSim supporting modelling and
simulation of Clouds for performance studies; (v) Energy Efficient Resource
Allocation Mechanisms and Techniques for creation and management of Green
Clouds; and (vi) pathways for future research.Comment: 21 pages, 6 figures, 2 tables, Conference pape
High-Performance Cloud Computing: A View of Scientific Applications
Scientific computing often requires the availability of a massive number of
computers for performing large scale experiments. Traditionally, these needs
have been addressed by using high-performance computing solutions and installed
facilities such as clusters and super computers, which are difficult to setup,
maintain, and operate. Cloud computing provides scientists with a completely
new model of utilizing the computing infrastructure. Compute resources, storage
resources, as well as applications, can be dynamically provisioned (and
integrated within the existing infrastructure) on a pay per use basis. These
resources can be released when they are no more needed. Such services are often
offered within the context of a Service Level Agreement (SLA), which ensure the
desired Quality of Service (QoS). Aneka, an enterprise Cloud computing
solution, harnesses the power of compute resources by relying on private and
public Clouds and delivers to users the desired QoS. Its flexible and service
based infrastructure supports multiple programming paradigms that make Aneka
address a variety of different scenarios: from finance applications to
computational science. As examples of scientific computing in the Cloud, we
present a preliminary case study on using Aneka for the classification of gene
expression data and the execution of fMRI brain imaging workflow.Comment: 13 pages, 9 figures, conference pape
The Making of Cloud Applications An Empirical Study on Software Development for the Cloud
Cloud computing is gaining more and more traction as a deployment and
provisioning model for software. While a large body of research already covers
how to optimally operate a cloud system, we still lack insights into how
professional software engineers actually use clouds, and how the cloud impacts
development practices. This paper reports on the first systematic study on how
software developers build applications in the cloud. We conducted a
mixed-method study, consisting of qualitative interviews of 25 professional
developers and a quantitative survey with 294 responses. Our results show that
adopting the cloud has a profound impact throughout the software development
process, as well as on how developers utilize tools and data in their daily
work. Among other things, we found that (1) developers need better means to
anticipate runtime problems and rigorously define metrics for improved fault
localization and (2) the cloud offers an abundance of operational data,
however, developers still often rely on their experience and intuition rather
than utilizing metrics. From our findings, we extracted a set of guidelines for
cloud development and identified challenges for researchers and tool vendors
StratusLab Cloud Distribution
International audienceCloud technologies provide many benefits for scientific and engineering applications, such as customised execution environments, near-instantaneous provisioning, elasticity, and the ability to run user-level services. However, a rapid, wholesale shift to using public, commercial cloud services is unlikely because of capital investments in existing resources and data management issues. To take full advantage of cloud technologies in the short term, institutes and companies must be able to deploy their own cloud infrastructures. The StratusLab project provides a complete, open-source cloud distribution that permits them to do this. The StratusLab services include the computing, storage, and networking services required for an Infrastructure as a Service (IaaS) cloud. It also includes high-level services like the Marketplace that facilitates the sharing of machine images and Claudia that allows the deployment and management of complete software systems
A Process Framework for Managing Quality of Service in Private Cloud
As information systems leaders tap into the global market of cloud computing-based services, they struggle to maintain consistent application performance due to lack of a process framework for managing quality of service (QoS) in the cloud. Guided by the disruptive innovation theory, the purpose of this case study was to identify a process framework for meeting the QoS requirements of private cloud service users. Private cloud implementation was explored by selecting an organization in California through purposeful sampling. Information was gathered by interviewing 23 information technology (IT) professionals, a mix of frontline engineers, managers, and leaders involved in the implementation of private cloud. Another source of data was documents such as standard operating procedures, policies, and guidelines related to private cloud implementation. Interview transcripts and documents were coded and sequentially analyzed. Three prominent themes emerged from the analysis of data: (a) end user expectations, (b) application architecture, and (c) trending analysis. The findings of this study may help IT leaders in effectively managing QoS in cloud infrastructure and deliver reliable application performance that may help in increasing customer population and profitability of organizations. This study may contribute to positive social change as information systems managers and workers can learn and apply the process framework for delivering stable and reliable cloud-hosted computer applications
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