Presentation on theme: "Spatial Cloud Computing"— Presentation transcript:
1 Spatial Cloud Computing Chaowei Phil Yang, Co-DirectorNASA/GMU Joint Center of Intelligent Spatial Computing for Water/Energy SciencesAssociate Professor, Geography and GeoInformation ScienceGeorge Mason Univ., Fairfax, VA,
2 Agenda Concept Examples How to implement Research directions Why Cloud Computing?Cloud ComputingCharacteristics of Cloud ComputingSpatial Cloud ComputingExamplesGEOSS ClearinghouseDust Storm Forecasting & VisualizationHow to implementResearch directions
3 Why Cloud Computing? Flooding We need the right information to the right place and right people almost in real time, when flooding happened.
4 Why Cloud Computing? Flooding Analyses The Hurricane Katrina response took about one week to integrate and develop relevant response geospatial information. The time is too long for responding.
5 Why Cloud Computing? What if we can Integrate all geospatial data, information, knowledge, processing in a few minutesGenerate and send the right information in real time to the people including decision makers, first responders, victimsThis dream requires a computing platform thatcan be ready in a few minutescan reach out to all people neededonly cost for the amount of computing usedwon’t cost to maintain after the emergency responseThis is exactly what cloud computing can provide
6 Cloud ComputingCloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model promotes availability and is composed of five essential characteristics, three service models, and four deployment models.The Most popular definition is developed by NISTNIST 2010
7 Cloud ComputingFive essential characteristics, which differentiate cloud computing from grid computing and other distributed computing paradigms:On-demand self-service. provision computing capabilities as needed automatically.Broad network access. available over the network and accessed through standard mechanisms.Resource pooling. computing resources are pooled with location independenceRapid elasticity. Capabilities can be rapidly and elastically provisioned.Measured Service. automatically control and optimize resourceNIST 2010
8 Cloud Computing Three service models Software as a Service (SaaSCloud), such as gmailPlatform as a Service (PaaS), such as MS AzureInfrastructure as a Service (IaaS), such as Amazon EC24. Data as a Service (DaaS)NIST 2010
9 Geospatial Science Information Workflow IT Characteristics:Data IntensityComputing IntensityConcurrent Access Intensity, andSpatiotemporal IntensityGeospatial sciences has four IT related characteristics. But all of them attribute to the last one, spatiotemporal intensity of the problem, the data resources, the end users, and the computing resources.
10 Spatial Cloud Computing Refers to the distributed computing paradigm thatEnables the geospatial science discoveries, emergency responses, education, other societal benefitsIs optimized by spatiotemporal principles.Yang C., Goodchild M., Huang Q., Nebert D., Raskin R., Xu Y., Bambacus M., Fay D., Spatial Cloud Computing: How can geospatial science use and help to shape cloud computing? International Journal on Digital Earth. 4,
11 Agenda Concept Examples How to implement Research Directions Cloud ComputingCharacteristics of CC and SCCSpatial Cloud ComputingExamplesGEOSS ClearinghouseDust Storm Forecasting & VisualizationHow to implementResearch Directions
12 Natural Hazards: Dust Storms Forecasting & Visualization ObjectivesProvide timely forecasting of dust storm for public health emergency responsesProvide an intuitive interface for decision makersEnabling Computing TechnologiesCloud Computing as an advanced cloud computing platform to support simulation and forecasting.Cloud DB as a data management tool for large volumetric data.4D/5D Vis Tool to render the data.Dust storm is a typical problem with the four characteristics. Cloud computing and 5D processing technologies are needed.
13 5D visualization from 2D to 3D space, 4D (space+time), and 5D (+phenomena, such as dust)
14 Computing IntensityThe computing is very intensive and spatiotemporal related. Lots of researches are needed to enable this. Such as this one on how to leverage the biggest number of CPUs and processes.
15 GEOSS Clearinghouse Objectives Share Global Earth Observation Data Among 140+ Countries to Address Global Challenges of Natural Hazards and Emergency ResponsesSupport Global End Users to Discover, Access, and Utilize EO DataProvide Responses to End Users in SecondsAdvanced Computing TechnologiesCloud Computing (EC2 & Azure) Responds to Spike Massive Concurrent End UsersCloud DB (SQLAzure) Manages Millions to Billions of Metadata RecordsWebGIS & 5D Vis Tools to Visualizes EO Data
16 The discovery, access, and utilization of data can be integrated into one platform with this open simple search. But the problems is on how to get response in time with proper accuracy, knowledge, and large volume of data.
17 This one show if the users are spatiotemporally distributed around the world.
18 Concurrent IntensityCloud can help, detailed in the first paper in references.
19 Agenda Concept Examples How to implement Research Directions Cloud ComputingCharacteristics of CCSpatial Cloud ComputingExamplesGEOSS ClearinghouseDust Storm Forecasting & VisualizationHow to implementResearch Directions
22 Agenda Concept Examples How to implement Research Directions Cloud ComputingCharacteristics of CCSpatial Cloud ComputingExamplesGEOSS ClearinghouseDust Storm Forecasting & VisualizationHow to implementResearch Directions
23 Potential Research Directions Spatiotemporal principle, thinking, and comptuingImplement important complex geospatial science and applications for best practiceSupporting the SCC characteristicsSecurityCitizen and social science issues: Trustworthy, Privacy, Ethical, etc.Many other (scholar) aspects of geospatial sciencesMany research needs to be done. One if on security, there is no silver bullets on this. Organizational research & development is to standardize the requirements and products so end user can match their security needs to providing with relevant costs.
24 IJDE Special Issue on SCC One announcement: IJDE SCC special issue
25 Spatial Cloud Computing Special Issue 4th Issue of 5th Volume of International Journal on Digital Earth, (New Journal, SCI Impact Factor 1.453)Received 25 extended abstract from field leaders around the worldSelected 13 to submit full paper for reviewLook for reviewersPleasestate your interests in reviewing the SCC full papersa one page bio of you focus on cloud computing and geospatial sciences
27 References Definition paper Yang, C., Goodchild M., Huang Q., Nebert D., Raskin R., Xu Y., Bambacus M., Fay D., 2011a, Spatial Cloud Computing: How could geospatial sciences use and help to shape cloud computing, International Journal on Digital Earth.Review & OverviewFoster, I., Zhao, Y., Raicu, Y., Lu, S., Cloud Computing and Grid Computing 360-Degree Compared, In: Grid Computing Environments Workshop, GCE IEEE, Los Alamitos. 2. Yang, C., Raskin, R., Goodchild, M.F., and Gahegan, M., 2010, Geospatial Cyberinfrastructure: Past, Present and Future, Computers, Environment, and Urban Systems, 34(4):Spatiotemporal data modelingM.F. Goodchild, M. Yuan, and T.J. Cova (2007) Towards a general theory of geographic representation in GIS. International Journal of Geographical Information Science 21(3): 239–260. (Open Access)Rey, S. J., and M. V. Janikas STARS: Space-Time Analysis of Regional Systems. Geographical Analysis, 38 (1): 67–86.Systematic researchArmbrust, M, Fox, A., Griffith R., Joseph A., Katz, R. and etc, Above the Cloud: A Berkeley View of Cloud Computing, Technical Report No. UCB/EECS (Open Access)Wang S. and Armstrong M., A theoretical approach to the use of cyberinfrastructure in geographical analysis, International Journal of Geographical Information Science 23(2), 169 – 193. (Open Access)Yang C., Wu H., Li Z., Huang Q., Li J., 2011, Spatial Computing: Utilizing Spatial Principles to Optimize Distributed Computing for Enabling Physical Science Discoveries, Proceedings of National Academy of Sciences, doi: /pnas (Open Access)Examplar applicationsWang, S., and Liu, Y TeraGrid GIScience Gateway: Bridging Cyberinfrastructure and GIScience. International Journal of Geographical Information Science, 23 (5):Evangelinos C., Hill C., Cloud Computing for parallel Scientific HPC Applications: Feasibility of running Coupled Atmosphere-Ocean Climate Models on Amazon’s EC2, CCA-08 October 22–23, 2008.