3. Topics Problem Statement Define the problem Significance in context of the course Key Concepts Cloud Computing Spatial Cloud Computing Major Contributions of the paper Most significant - Why Preserve and Revise

4. Problem Statement Use of Cloud Computing to support the intensities of geospatial sciences Reason for need of platform like Cloud Computing What is Cloud Computing? Spatial Cloud Computing (SCC) SCC Scenarios/Examples Opportunities & Challenges Cloud computing has been one of the most advancing technologies recently. Utilizing it in the context of Geo-Spatial sciences can prove to be very useful.

5. Cloud Computing Advancement of Distributed Computing Provides ‘computer as a service’ for end users In ‘pay-as-you-go’ model Model: Enables convenient, on-demand network access to a shared pool of configurable computing resources Ex: networks, servers, storage, applications and services Resources can be rapidly provisioned and released With minimal management effort Or with Service provider interaction

6. Services for Cloud Computing Cloud Computing is provided through 4 services Infrastructure as a Service (IaaS) – Amazon EC2 Platform as a Service (PaaS) – MS Azure, Google Apps Software as a Service (SaaS) – Salesforce.com Data as a Service (DaaS) For Geospatial Sciences Hadoop & Map Reduce can also be used

7. Uses of Cloud Services Earth Observation (EO) Data Access: DaaS is used for fast, secure access & utilization of EO data DaaS also provides the needed Storage & Processing needs Model: IaaS gives full control of computing instances But has network bottlenecks Cloud computing can be used in complement to solve computing intensive problems Knowledge & Decision Support: Used by domain experts, managers or public SaaS provides good support Social Impact & Feedback: SaaS such as Facebook & email can be best utilized

8. Characteristics of Cloud Computing 5 characteristics that distinguish Cloud Computing from other distributed computing paradigms On-Demand Self Service For customers as needed automatically Broad Network Access For different types of network terminals Resource Pooling For consolidation of diff. types of Computing resources Rapid Elasticity For rapidly and elastically provisioning, allocating, and releasing computing resources Measured Service To support pay-as-you-go approach

9. Spatial Cloud Computing Operation of geospatial applications on cloud computing environments Cloud computing Helps geospatial sciences Can be optimized with Spatiotemporal principles Best utilize available distributed computing resources Geospatial Science Problems Have intensive Spatiotemporal constraints & Principles Best enabled if we consider general spatiotemporal rules for geospatial domains

10. Spatial Cloud Computing Framework

11. SCC Scenarios 4 scenarios given for 4 intensity problems. An Example in the PPT. Data Intensity Scenario: Data Intensity issues in Geospatial sciences characterized by 3 aspects Multi-Dimensional Massiveness Globally distributed-organizations with data holdings are distributed over entire earth Large volumes of data transferred Over fast computer networks Or collocated with processing to minimize transmitting

12. Data Intensity scenario solution: Developing DaaS Distributed inventory and portal based on SCC To enable discoverability, accessibility & utilizability of geospatial data Stores millions to billions of metadata entries With data locations & performance awareness Developed & Tested based on Microsoft Azure, Amazon EC2 & NASA Cloud Services

13. Opportunities & Challenges The grand challenges along 4 intensity problems can be solved by latest advancements in cloud computing Opportunities: Spatiotemporal principle mining & extracting Important digital earth & complex geospatial science and applications Supporting the SCC characteristics Security Citizen and Social Science

14. Major Contributions & Significant Categorization of grand challenges of Geospatial Sciences in 21 st century Good Explanations of Cloud Computing and Spatial Cloud Computing with examples Insight with examples into how cloud computing can solve 4 intensity problems Most Significant Looks ahead to see possible solutions for intensity problems

15. Preserve & Revise Revise Whole paper along recent advancements in cloud computing Examples of SCC scenarios Preserve Initial different kinds of intensity definitions Cloud Computing & SCC key concepts

16. THANK YOU