1,103 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
Resource provisioning in Science Clouds: Requirements and challenges
Cloud computing has permeated into the information technology industry in the
last few years, and it is emerging nowadays in scientific environments. Science
user communities are demanding a broad range of computing power to satisfy the
needs of high-performance applications, such as local clusters,
high-performance computing systems, and computing grids. Different workloads
are needed from different computational models, and the cloud is already
considered as a promising paradigm. The scheduling and allocation of resources
is always a challenging matter in any form of computation and clouds are not an
exception. Science applications have unique features that differentiate their
workloads, hence, their requirements have to be taken into consideration to be
fulfilled when building a Science Cloud. This paper will discuss what are the
main scheduling and resource allocation challenges for any Infrastructure as a
Service provider supporting scientific applications
Executing distributed applications on virtualized infrastructures specified with the VXDL language and managed by the HIPerNET framework
International audienceWith the convergence of computing and communication, and the expansion of cloud computing, new models and tools are needed to allow users to define, create, and exploit on-demand virtual infras- tructures within wide area distributed environments. Optimally design- ing customized virtual execution-infrastructure and executing them on a physical substrate remains a complex problem. This paper presents the VXDL language, a language for specifying and describing virtual infras- tructures and the HIPerNET framework to manage them. Based on the example of a specific biomedical application and workflow engine, this paper illustrates how VXDL enables to specify different customized vir- tual infrastructures and the HIPerNET framework to execute them on a distributed substrate. The paper presents experiments of the deploy- ment and execution of this application on different virtual infrastructures managed by our HIPerNet system. All the experiments are performed on the Grid'5000 testbed substrate
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On Optimal and Fair Service Allocation in Mobile Cloud Computing
This paper studies the optimal and fair service allocation for a variety of
mobile applications (single or group and collaborative mobile applications) in
mobile cloud computing. We exploit the observation that using tiered clouds,
i.e. clouds at multiple levels (local and public) can increase the performance
and scalability of mobile applications. We proposed a novel framework to model
mobile applications as a location-time workflows (LTW) of tasks; here users
mobility patterns are translated to mobile service usage patterns. We show that
an optimal mapping of LTWs to tiered cloud resources considering multiple QoS
goals such application delay, device power consumption and user cost/price is
an NP-hard problem for both single and group-based applications. We propose an
efficient heuristic algorithm called MuSIC that is able to perform well (73% of
optimal, 30% better than simple strategies), and scale well to a large number
of users while ensuring high mobile application QoS. We evaluate MuSIC and the
2-tier mobile cloud approach via implementation (on real world clouds) and
extensive simulations using rich mobile applications like intensive signal
processing, video streaming and multimedia file sharing applications. Our
experimental and simulation results indicate that MuSIC supports scalable
operation (100+ concurrent users executing complex workflows) while improving
QoS. We observe about 25% lower delays and power (under fixed price
constraints) and about 35% decrease in price (considering fixed delay) in
comparison to only using the public cloud. Our studies also show that MuSIC
performs quite well under different mobility patterns, e.g. random waypoint and
Manhattan models
Exploring the Virtual Infrastructures as a Service concept with HIPerNET
With the expansion and convergence of communication and computing, dynamic provisioning of customized networking and processing infrastructures, as well as resource virtualization, are appealing concepts and technologies. Therefore, new models and tools are needed to allow users to create, trust and enjoy such on-demand virtual infrastructures within a wide area context. This research report presents the HIPerNET framework that we are designing and developing for creating, managing and controlling virtual infrastructures in the context of high-speed Internet. The key idea of this proposal is the combination of network- and system-virtualization associated with controlled resource reservation to provide fully isolated environments. HIPerNET's motivations and design principles are presented. We then examine specifically how this framework handles the virtual infrastructures, called Virtual Private eXecution Infrastructures (VPXI). To help specifying customized isolated infrastructures, HIPerNET relies on VXDL, a language for VPXI description and modeling which considers end-host resource as well as the virtual network topology interconnecting them, including virtual routers. We exemplify the VPXI specification, allocation and execution using a real large-scale distributed medical application. Experimental results obtained within the Grid'5000 testbed are presented and analyzed
Enhancing Job Scheduling of an Atmospheric Intensive Data Application
Nowadays, e-Science applications involve great deal of data to have more accurate analysis. One of its application domains is the Radio Occultation which manages satellite data. Grid Processing Management is a physical infrastructure geographically distributed based on Grid Computing, that is implemented for the overall processing Radio Occultation analysis. After a brief description of algorithms adopted to characterize atmospheric profiles, the paper presents an improvement of job scheduling in order to decrease processing time and optimize resource utilization. Extension of grid computing capacity is implemented by virtual machines in existing physical Grid in order to satisfy temporary job requests. Also scheduling plays an important role in the infrastructure that is handled by a couple of schedulers which are developed to manage data automaticall
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