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An exploration of the benefits of cloud computing in geoscience research and applications as well as future research directions, Spatial Cloud Computing: A Practical Approach discusses the essential elements of cloud computing and their advantages for geoscience. Using practical examples, it details the geoscience requirements of cloud computing, covers general procedures and considerations when migrating geoscience applications onto cloud services, and demonstrates how to deploy different applications. The book discusses how to choose cloud services based on the general cloud computing measurement criteria and cloud computing cost models. The authors examine the readiness of cloud computing to support geoscience applications using open source cloud software solutions and commercial cloud services. They then review future research and developments in data, computation, concurrency, and spatiotemporal intensities of geosciences and how cloud service can be leveraged to meet the challenges. They also introduce research directions from the aspects of technology, vision, and social dimensions. Spatial Cloud Computing: A Practical Approach a common workflow for deploying geoscience applications and provides references to the concepts, technical details, and operational guidelines of cloud computing. These features and more give developers, geoscientists, and IT professionals the information required to make decisions about how to select and deploy cloud services.
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Table of Contents

Introduction to Cloud Computing for GeosciencesGeoscience Application Challenges to Computing InfrastructuresChallenges and Opportunities for Geoscience Applications in the 21st CenturyThe Needs of a New Computing InfrastructureThe Birth of Cloud Computing The Advantages and Disadvantages of Cloud Computing for Geoscience ApplicationsSummary Problems References Cloud Computing Architecture, Concepts, and CharacteristicsConceptsCloud Computing ArchitectureCharacteristicsService ModelsDeployment Models and Cloud TypesReview of Cloud Computing ResourcesSummaryProblemsReferencesEnabling TechnologiesHardware AdvancementsComputing TechnologiesVirtualizationDistributed File SystemWeb x.0ConclusionSummaryProblemsReferencesDeploying Applications onto Cloud ServicesHow to Use Cloud ComputingPopular Cloud ServicesUse Case: A Simple Web ApplicationDeploying the Web Application onto Cloud ServicesConclusion and DiscussionSummaryProblemsReferencesCloud-Enabling Geoscience ApplicationsCommon Components for Geoscience ApplicationsCloud-Enabling Geoscience ApplicationsUse CasesSummaryProblemsReferencesHow to Choose Cloud Services: Toward a Cloud Computing Cost ModelThe Importance and Challenges of Selecting Cloud Services The Factors Impacting Cloud Service Selection Selecting Cloud Services Using the Earth Science Information Partners (ESIP) Cloud Adoption Advisory Tool as an Example In-Depth Considerations in Cloud Service Selection and the Development of Advisory Tools SummaryProblemsReferencesCloud-Enabling Geoscience ProjectsArcGIS in the CloudIntroductionArcGIS in the CloudUse CasesSummaryProblemsReferencesCloud-enabling GEOSS Clearinghouse GEOSS Clearinghouse: Background and ChallengesSystem Demonstration Conclusion Problems Appendix 8.1 Template for Creating an Auto-Scaling Function References Cloud-enabling Climate@Home Climate@Home: Background and Challenges Deployment and Optimizations System Demonstrations Conclusion Summary Problems Appendix 9.1 E4M20a_000040_wu.xml Appendix 9.2 Climateathome_re.xml References 159Cloud-Enabling Dust Storm Forecasting Dust Storm Modeling: Background and challenges Deployment and Optimization DemonstrationConclusionSummaryProblemsReferencesCloud Computing Status and ReadinessCloud ServicesIntroduction to Cloud ServicesAmazon Web Services (AWS)Windows AzureNebulaConclusionSummaryProblemsReferencesHow to Test the Readiness of Cloud Services Introduction Test Environment Concurrent Intensity Test Using GEOSS Clearinghouse (CLH) Data and Computing Intensities Test Using Climate@Home Cloud Test Using Dust Storm Forecasting Summary Problems Appendix 12.1: GetRecords example to search metadata Appendix 12.2: Example of Jmeter test plan References 221Contents xiiiOpen-Source Cloud Computing Solutions Introduction to Open-Source Cloud Computing Solutions CloudStack Eucalyptus OpenNebula Nimbus Open-Source Benchmarking Considerations Conclusion Summary Problems References How to Test the Readiness of Open-Source Cloud Computing SolutionsIntroduction Test Environment Tests of Cloud Operations Tests of Virtual Computing Resources Cloud Readiness Test for GEOSS Clearinghouse Cloud Readiness Test for Dust Storm Forecasting Summary Problems Appendix 14.1 Ubench Patch File (Ubench-Patch.Txt) References GeoCloud initiative Introduction GeoCloud Architecture GeoCloud Activities GeoCloud Security Operational Cost in the Cloud Discussion Summary Problems References Future DirectionsHandling Intensities of Data, Computation, Concurrent Access, and SPATIOTEMPORAL PATTERNS Introduction Big Data Computing Intensity Concurrent Intensity Spatiotemporal Intensity Summary Problems References Cloud Computing Research for Geosciences and Applications Evolving 21st Century Vision for Geoscience Applications Technological Advancements Synergistic Advancement of Social Science and Cloud Computing Summary Problems References Index

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