[Esip-cloud] book chapter review invitation for spatial cloud comptuing

[Chaowei Yang]

Dear All, 

We are writing a book for spatial cloud computing and would like to seek review from potential readers with various background. You don't have to be a cloud computing expert to review the chapters and each chapter is about 20 pages double spaced. 

If interested, please check from the following list of chapters to select two to four chapters that you wish to review. We will offer a free copy of the book to who reviewed for over two chapters. We expect a two week review cycle for the book chapters. 


Spatial Cloud Computing: A Practical Approach
This book is to bridge cloud computing and geospatial science applications with practical examples from several aspects including a) cloud computing services, b) cloud enable geoscience applications, c) how cloud supports geosciences and applications, and d) how to utilize the principles from geosciences and applications to optimize cloud computing. 

Part I Introduction to Cloud Computing for Geosciences
This part introduce cloud computing, requirements from the domains of geoscience applications for cloud computing, and the demands, concepts, enabling technologies  of cloud computing. 

Chapter 1 Why Cloud Computing
Cloud computing is a new generation distributed computing and utility computing by sharing and pooling computing resources for dynamic demands of computing resources by many 21st century challenges. 
References

Chapter 2 Cloud Computing Concepts, Characteristics and Architecture
Cloud computing refers to a computing model that pools and shares computing resources (network, storage, computing, software, and others) among a variety of communities ranges from local to global. 
References

Chapter 3 Enabling Technologies
Several key technologies have contributed to the emergence of cloud computing and includes Web x.0, on-demand deployment, Internet delivery of services and open source software, utility/ubiquitous computing, and virtualization. 
References

Part II Cloud Computing Deployment
This part introduces deployment considerations and the general procedures when migrating geoscience applications onto cloud computing services. 

Chapter 4 How to use cloud computing 
Using a very simple web application, this chapter demonstrates how to deploy applications to the two most popular cloud services of Amazon EC2 and Microsoft Azure.
References

Chapter 5 Cloud Enable Applications
The common procedure for how to deploy different types of applications onto the cloud services includes analyzing applications, designing appropriate cloud strategy, selecting the right services, and deploying the application.  
References

Chapter 6 How to choose cloud Computing: Towards a Cloud Computing Cost Model 
This chapter discusses some general cloud computing factors/measurement criteria, several cloud computing cost models, and a cloud solution recommendation system for adopting cloud computing.
References

Part III Cloud Enabling Geoscience Projects
This part demonstrates how to deploy different applications onto cloud platforms using three different geoscience applications as examples

Chapter 7 ArcGIS in the Cloud 
This chapter introduces how to use ArcGIS in the cloud.
References

Chapter 8 Cloud-Enable GEOSS Clearinghouse 
This chapter will introduces how to use Cloud Computing to support GEOSS Clearinghouse including introduction, installations onto cloud services, spatial data handling, and concurrent requests optimization.
References

Chapter 9 Cloud-Enable Climate at Home 
This chapter discusses the development of Climete at Home project with a primary focus on the utilization of cloud computing techniques to support the efficient management and utilization of data and computing resources. 
References

Chapter 10 Cloud-Enable Dust Storm Forecasting 
This chapter introduces how to use loosely coupled and spatiotemporal principles to support the simulation by enabling the nested executions of dust storm models with the elasticity of cloud computing. 
References

Part IV Cloud Computing Status and Readiness
This part examines the readiness of cloud computing to support geoscience applications using open source cloud software solutions and commercial cloud computing services.
References

Chapter 11 Commercial Cloud Computing Platforms 
This chapter introduces and compares three cloud computing services including EC2, Azure, and Nebula. 
References

Chapter 12 Readiness of Cloud Computing Platforms 
This chapter introduces the readiness of cloud computing platforms using a series of cloud computing testing with the three applications described in part III and three services described in chapter 11. 
References

Chapter 13 Open Source Cloud Computing Solutions 
This chapter introduces several major Cloud Computing Open Source solutions including Cloudstack, Eucalpytus, Nimbus, and OpenNebula. 
References

Chapter 14 Readiness of Open Source Cloud Computing Solutions 
This chapter tests and compares with the traditional computing resources the performance and readiness of different Open Source solutions introduced in chapter 13. 
References

Chapter 15 GeoCloud Initiative 
This chapter presents the background and architecture design of GeoCloud, which is a cross-agency initiative to define common operating system and software suites for geoscience applications, explore deployment and management strategies on clouds, and monitor usage and costing of Cloud services. In addition, this chapter introduces the security strategies for sharing and protecting data among different agencies through lessons learnt from the GeoCloud project.

References

Part V Future Directions
This part reviews the future research and developments for cloud computing.
Chapter 16 Cloud Computing Research 
This chapter introduces future research needs on resource management, scheduling, cloud computing cost models, interoperability, security and regulations, and other social and physical science issues. 
References

Chapter 17 Handling of Data, Computing, Concurrent and Spatiotemporal Intensities 
This chapter introduces the intensities of data, computing, concurrent, spatiotemporal and discusses potential solutions for addressing the challenges with cloud computing.
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Chapter 18 Integrating Knowledge to Enable Geosciences Knowledge reasoning 
This chapter discusses how to represent and integrate knowledge into cloud computing, and how to utilize the integrated cloud knowledge system to enable geoscience knowledge reasoning. 
References

Chapter 19 Towards Spatial Cloud Computing 
This chapter envisions the future of cloud computing that is able to provide the right information to the right people at the right place and right time from the examples of deep geoscience explorations, environmental policy making, and geoscience education perspectives. 
References


Best Regards,
Phil
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Utilize cloud computing to support dust storm forecasting
http://www.tandfonline.com/eprint/ZIZNbu76shUGVGEcds5t/full
Chaowei Phil Yang, Ph.D., Associate Professor, GMU
http://cpgis.gmu.edu/homepage/
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