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

Autonomic Cloud Computing: Open Challenges and Architectural Elements

As Clouds are complex, large-scale, and heterogeneous distributed systems, management of their resources is a challenging task. They need automated and integrated intelligent strategies for provisioning of resources to offer services that are secure, reliable, and cost-efficient. Hence, effective management of services becomes fundamental in software platforms that constitute the fabric of computing Clouds. In this direction, this paper identifies open issues in autonomic resource provisioning and presents innovative management techniques for supporting SaaS applications hosted on Clouds. We present a conceptual architecture and early results evidencing the benefits of autonomic management of Clouds.Comment: 8 pages, 6 figures, conference keynote pape

AMP: A Science-driven Web-based Application for the TeraGrid

The Asteroseismic Modeling Portal (AMP) provides a web-based interface for astronomers to run and view simulations that derive the properties of Sun-like stars from observations of their pulsation frequencies. In this paper, we describe the architecture and implementation of AMP, highlighting the lightweight design principles and tools used to produce a functional fully-custom web-based science application in less than a year. Targeted as a TeraGrid science gateway, AMP's architecture and implementation are intended to simplify its orchestration of TeraGrid computational resources. AMP's web-based interface was developed as a traditional standalone database-backed web application using the Python-based Django web development framework, allowing us to leverage the Django framework's capabilities while cleanly separating the user interface development from the grid interface development. We have found this combination of tools flexible and effective for rapid gateway development and deployment.Comment: 7 pages, 2 figures, in Proceedings of the 5th Grid Computing Environments Worksho

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

Towards Grid Interoperability

The Grid paradigm promises to provide global access to computing resources, data storage and experimental instruments. It also provides an elegant solution to many resource administration and provisioning problems while offering a platform for collaboration and resource sharing. Although substantial progress has been made towards these goals, nevertheless there is still a lot of work to be done until the Grid can deliver its promises. One of the central issues is the development of standards and Grid interoperability. Job execution is one of the key capabilities in all Grid environments. This is a well understood, mature area with standards and implementations. This paper describes some proof of concept experiments demonstrating the interoperability between various Grid environments

Towards Business Integration as a Service 2.0

Cloud Computing Business Framework (CCBF) is a framework for designing and implementation of Could Computing solutions. This proposal focuses on how CCBF can help to address linkage in Cloud Computing implementations. This leads to the development of Business Integration as a Service 1.0 (BIaS 1.0) allowing different services, roles and functionalities to work together in a linkage-oriented framework where the outcome of one service can be input to another, without the need to translate between domains or languages. BIaS 2.0 aims to allow full automation, enhanced security, advanced risk modelling and improved collaboration between processes in BIaaS 1.0. The benefits from adopting BIaS 1.0 and developing BIaS 2.0 are illustrated using a case study from the University of Southampton and several collaborators including IBM US. BIaS 2.0 can work with mainstream technologies such as scientific workflows, and the proposal and demonstration of BIaaS 2.0 will certainly benefit industry and academia