Cloud Computing and Software Services: Theory and Techniques

Thanks to its inherent resilience to failure and the increasing availability of open-source cloud infrastructure software and virtualization software stacks, services delivered from the cloud have expanded past web applications to include storage, raw computing, and access to specialized services. The possibility of satisfying maintenance and technical support needs by leasing services from commercial cloud infrastructures has also generated a new wave of interest in the cost and efficiency enhancements cloud computing can bring to organizations big and small. Whether youre already in the cloud, or determining whether or not it makes sense for your organization, Cloud Computing and Software Services: Theory and Techniques provides you with the technical understanding needed to develop and maintain state-of-the-art cloud computing and software services. From basic concepts and recent research findings to future directions, it gathers the insight of 50 experts from around the world to present the most up-to-date global perspective on the broad range of technical topics related to cloud computing and Software as a Service (SaaS). The book also: Reviews real cases and applications of cloud computingDiscusses the infrastructure cloud and Infrastructure as a Service (IaaS)Considers the cloud and data- and compute-intensive environmentsExamines security and reliability in the cloud Witten in a manner that makes this complex subject easy to understand, this is an ideal one-stop reference for anyone interested in cloud computing. The accessible language and wealth of illustrations also make it suitable for academic or research-oriented settings. The comprehensive coverage supplies you with the up-to-date understanding of cloud computing technologies and trends in parallel computing needed to establish and maintain effective and efficient computing and software services.

[1]  Carole A. Goble,et al.  Taverna/myGrid: Aligning a Workflow System with the Life Sciences Community , 2007, Workflows for e-Science, Scientific Workflows for Grids.

[2]  Frédéric Desprez,et al.  Large scale execution of a bioinformatic application on a volunteer grid , 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

[3]  Susan E. Minkoff,et al.  Spatial Parallelism of a 3D Finite Difference Velocity-Stress Elastic Wave Propagation Code , 1999, SIAM J. Sci. Comput..

[4]  Jano I. van Hemert,et al.  Eliminating the middleman: peer-to-peer dataflow , 2008, HPDC '08.

[5]  Carole A. Goble,et al.  myExperiment: Defining the Social Virtual Research Environment , 2008, 2008 IEEE Fourth International Conference on eScience.

[6]  Miron Livny,et al.  Distributed computing in practice: the Condor experience: Research Articles , 2005 .

[7]  L. Youseff,et al.  Toward a Unified Ontology of Cloud Computing , 2008, 2008 Grid Computing Environments Workshop.

[8]  Thomas Bohlen,et al.  Paralel 3-D viscoelastic finite difference seismic modelling , 2002 .

[9]  Miron Livny,et al.  The cost of doing science on the cloud: The Montage example , 2008, 2008 SC - International Conference for High Performance Computing, Networking, Storage and Analysis.

[10]  David P. Anderson,et al.  BOINC: a system for public-resource computing and storage , 2004, Fifth IEEE/ACM International Workshop on Grid Computing.

[11]  Johan Montagnat,et al.  Modeling the latency on production grids with respect to the execution context , 2009, Parallel Comput..

[12]  Jason Lee,et al.  High-Performance Remote Access to Climate Simulation Data: A Challenge Problem for Data Grid Technologies , 2001, ACM/IEEE SC 2001 Conference (SC'01).

[13]  Paolo Bientinesi,et al.  Can cloud computing reach the top500? , 2009, UCHPC-MAW '09.

[14]  David P. Anderson,et al.  SETI@home-massively distributed computing for SETI , 2001, Comput. Sci. Eng..

[15]  Leonard A. Smith,et al.  Uncertainty in predictions of the climate response to rising levels of greenhouse gases , 2005, Nature.

[16]  Daniel S. Katz,et al.  Pegasus: A framework for mapping complex scientific workflows onto distributed systems , 2005, Sci. Program..

[17]  George Lawton,et al.  Moving the OS to the Web , 2008, Computer.

[18]  Radu Prodan,et al.  ASKALON: a tool set for cluster and Grid computing , 2005, Concurr. Pract. Exp..

[19]  Sang-Min Park,et al.  Data throttling for data-intensive workflows , 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

[20]  José A. B. Fortes,et al.  CloudBLAST: Combining MapReduce and Virtualization on Distributed Resources for Bioinformatics Applications , 2008, 2008 IEEE Fourth International Conference on eScience.

[21]  Edward Walker,et al.  The Real Cost of a CPU Hour , 2009, Computer.

[22]  I. Sfiligoi,et al.  Making science in the Grid world: using glideins to maximize scientific output , 2007, 2007 IEEE Nuclear Science Symposium Conference Record.

[23]  Ian T. Foster,et al.  The anatomy of the grid: enabling scalable virtual organizations , 2001, Proceedings First IEEE/ACM International Symposium on Cluster Computing and the Grid.

[24]  Xuebin Chi,et al.  An Implementation of Interactive Jobs Submission for Grid Computing Portals , 2005, ACSW.

[25]  Thomas Hérault,et al.  Computing on large-scale distributed systems: XtremWeb architecture, programming models, security, tests and convergence with grid , 2005, Future Gener. Comput. Syst..

[26]  Li Zhao,et al.  Managing Large-Scale Workflow Execution from Resource Provisioning to Provenance Tracking: The CyberShake Example , 2006, 2006 Second IEEE International Conference on e-Science and Grid Computing (e-Science'06).

[27]  David P. Anderson,et al.  Celebrating Diversity in Volunteer Computing , 2009 .

[28]  Carl Kesselman,et al.  GriPhyN and LIGO, building a virtual data Grid for gravitational wave scientists , 2002, Proceedings 11th IEEE International Symposium on High Performance Distributed Computing.

[29]  N. Jacq,et al.  Grid-Enabled High-Throughput In Silico Screening Against Influenza A Neuraminidase , 2006, IEEE Transactions on NanoBioscience.

[30]  Chandra Krintz,et al.  Evaluating the Performance Impact of Xen on MPI and Process Execution For HPC Systems , 2006, First International Workshop on Virtualization Technology in Distributed Computing (VTDC 2006).

[31]  Shantenu Jha,et al.  Grid Interoperability at the Application Level Using SAGA , 2007, Third IEEE International Conference on e-Science and Grid Computing (e-Science 2007).

[32]  Franck Cappello,et al.  Grid'5000: A Large Scale And Highly Reconfigurable Experimental Grid Testbed , 2006, Int. J. High Perform. Comput. Appl..

[33]  Martin Hofmann,et al.  Grid Added Value to Address Malaria , 2006, CCGRID.

[34]  M. Livny,et al.  High-Throughput, Kingdom-Wide Prediction and Annotation of Bacterial Non-Coding RNAs , 2008, PloS one.

[35]  Richard Wolski,et al.  The Eucalyptus Open-Source Cloud-Computing System , 2009, 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid.

[36]  Vanish Talwar,et al.  An environment for enabling interactive grids , 2003, High Performance Distributed Computing, 2003. Proceedings. 12th IEEE International Symposium on.

[37]  Johan Montagnat,et al.  Workflow-Based Data Parallel Applications on the EGEE Production Grid Infrastructure , 2008, Journal of Grid Computing.

[38]  Matthew R. Pocock,et al.  Taverna: a tool for the composition and enactment of bioinformatics workflows , 2004, Bioinform..

[39]  Mei-Hui Su,et al.  Characterization of scientific workflows , 2008, 2008 Third Workshop on Workflows in Support of Large-Scale Science.