Spatial Cloud Computing:Usage in Geo-Spatial Sciences

TopicsProblem Statement

Define the problemSignificance in context of the course

Key ConceptsCloud ComputingSpatial Cloud Computing

Major Contributions of the paper Most significant - Why

Preserve and Revise

Problem StatementUse of Cloud Computing to support the

intensities of geospatial sciencesReason for need of platform like Cloud ComputingWhat is Cloud Computing?Spatial Cloud Computing (SCC)SCC Scenarios/ExamplesOpportunities & 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.

Cloud ComputingAdvancement 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

servicesResources can be rapidly provisioned and released

With minimal management effort Or with Service provider interaction

Services for Cloud ComputingCloud Computing is provided through 4

servicesInfrastructure as a Service (IaaS) – Amazon

EC2Platform as a Service (PaaS) – MS Azure,

Google AppsSoftware as a Service (SaaS) – Salesforce.comData as a Service (DaaS) For Geospatial

SciencesHadoop & Map Reduce can also be used

Uses of Cloud ServicesEarth 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 instancesBut has network bottlenecksCloud computing can be used in complement to solve

computing intensive problemsKnowledge & Decision Support:

Used by domain experts, managers or publicSaaS provides good support

Social Impact & Feedback:SaaS such as Facebook & email can be best utilized

Characteristics of Cloud Computing5 characteristics that distinguish Cloud Computing

from other distributed computing paradigmsOn-Demand Self Service

For customers as needed automaticallyBroad Network Access

For different types of network terminalsResource Pooling

For consolidation of diff. types of Computing resourcesRapid Elasticity

For rapidly and elastically provisioning, allocating, and releasing computing resources

Measured Service To support pay-as-you-go approach

Spatial Cloud ComputingOperation of geospatial applications on cloud

computing environmentsCloud computing

Helps geospatial sciencesCan be optimized with Spatiotemporal

principles Best utilize available distributed computing

resourcesGeospatial Science Problems

Have intensive Spatiotemporal constraints & Principles

Best enabled if we consider general spatiotemporal rules for geospatial domains

Spatial Cloud Computing Framework

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 earthLarge volumes of data transferred

Over fast computer networks Or collocated with processing to minimize

transmitting

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

Opportunities & ChallengesThe grand challenges along 4 intensity

problems can be solved by latest advancements in cloud computing

Opportunities:Spatiotemporal principle mining & extractingImportant digital earth & complex geospatial

science and applicationsSupporting the SCC characteristicsSecurityCitizen and Social Science

Major Contributions & SignificantCategorization of grand challenges of

Geospatial Sciences in 21st centuryGood Explanations of Cloud Computing and

Spatial Cloud Computing with examplesInsight with examples into how cloud

computing can solve 4 intensity problems Most Significant Looks ahead to see possible solutions for intensity

problems

Preserve & ReviseRevise

Whole paper along recent advancements in cloud computing

Examples of SCC scenarios

PreserveInitial different kinds of intensity definitionsCloud Computing & SCC key concepts

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