HTC Scientific Computing in a Distributed Cloud Environment

This paper describes the use of a distributed cloud computing system for high-throughput computing (HTC) scientific applications. The distributed cloud computing system is composed of a number of separate Infrastructure-as-a-Service (IaaS) clouds that are utilized in a unified infrastructure. The distributed cloud has been in production-quality operation for two years with approximately 500,000 completed jobs where a typical workload has 500 simultaneous embarrassingly-parallel jobs that run for approximately 12 hours. We review the design and implementation of the system which is based on pre-existing components and a number of custom components. We discuss the operation of the system, and describe our plans for the expansion to more sites and increased computing capacity

A look at cloud architecture interoperability through standards

Enabling cloud infrastructures to evolve into a transparent platform while preserving integrity raises interoperability issues. How components are connected needs to be addressed. Interoperability requires standard data models and communication encoding technologies compatible with the existing Internet infrastructure. To reduce vendor lock-in situations, cloud computing must implement universal strategies regarding standards, interoperability and portability. Open standards are of critical importance and need to be embedded into interoperability solutions. Interoperability is determined at the data level as well as the service level. Corresponding modelling standards and integration solutions shall be analysed

Cloud Computing and Open Source Software: Issues and Developments

Cloud computing is a global paradigm that is offering useful services in virtually all spheres of human endeavor based on infrastructure made available to users on demand. The cloud provides on demand, elastic and scalable resources to meet the needs of users. The cloud has application deployed by cloud service providers that can be accessed by several users at the same time. Cloud computing also offers a programming environment that allows users deploy and run their own in-house applications. Massive storage and computing resources are also available on the cloud. There are currently open source applications that can be used to implement cloud applications. The source code which can be improved on and adapted for use is available to the user online. Such open source software tools allow the deployment of cloud for any type of domain. The study was executed by means of review of some literature available on cloud computing and open source software. This paper examines present trends in cloud computing and open source software and provides a guide for future research. In the present work, the objective is to answer the following question: what is the current trend and development in cloud computing and open source software? The review’s finding is that OpenStack provides the most comprehensive infrastructure in cloud computing and open source software

Exploitation and Sustainability First Plan

This document describes StratusLab's plans for exploitation and sustainability during the second year of the project and beyond. The plans cover commercial exploitation, primarily through commercial integration and support; and non-commercial exploitation, through use in national and international research e-infrastructures: for operating grid resources on private clouds, and for running research-oriented community clouds. In addition, we plan exploitation through projects such as OpenNebula and EGI, and through training and future research. Sustainability is driven by a desire to support critical infrastructures and as a basis for future research. Public funding, private funding and community contributions will play a role in sustainability through promotion, community development, support of cloud strategies, national cloud infrastructures, and cloud research

Energy efficiency of dynamic management of virtual cluster with heterogeneous hardware

Cloud computing is an essential part of today's computing world. Continuously increasing amount of computation with varying resource requirements is placed in large data centers. The variation among computing tasks, both in their resource requirements and time of processing, makes it possible to optimize the usage of physical hardware by applying cloud technologies. In this work, we develop a prototype system for load-based management of virtual machines in an OpenStack computing cluster. Our prototype is based on an idea of 'packing' idle virtual machines into special park servers optimized for this purpose. We evaluate the method by running real high-energy physics analysis software in an OpenStack test cluster and by simulating the same principle using the Cloudsim simulator software. The results show a clear improvement, 9-48 %, in the total energy efficiency when using our method together with resource overbooking and heterogeneous hardware.Peer reviewe