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12

store all your parcels in one central database formulate a grid over the USA made of squares N feet on a side, where N is such that the number of parcels that fit within N will not blow out the memory on one of your nodes create a table in your database with one row per grid square, an id column a geometry column and a status column each node runs a small ...


11

Cloud computing is basically the act of moving data or computations to servers that are distributed all over the world instead of a computer that is tied to one physical location. You then use a client, such as a web browser, to access your data/computing power from anywhere that has an internet connection. Think of it as the difference between owning a ...


9

Assuming you are looking for a web mapping with hosting managed for you and various sorts of vector query then one option might be CartoDB. It is backed by a postgres/postgis DB and lets you do various sorts of visualization and mapping without having to setup any services yourself. It includes free options for small tables but you might find you are ...


8

There were an interesting slot on FOSS4G in September in Barcelona about this: http://2010.foss4g.org/presentations_show.php?id=3584 It became more of a panel discussion than a presentation. In the middle of this blog post Paul Ramsey gives some kind of summary from that.


8

It really depends on the size of the datasets you are talking about and the complexity of your queries. I for example run pretty happily on a GoGrid server /PostGIS / Windows 2008 (32-bit) running IIS, a mix of PHP/.NET homegrown webservices with 2GIG ram/ dual core. The main spatial table I query has about 6 million records I think of mostly California ...


7

you should check out following cloud based slutions. Qgis Cloud - Publish your own maps directly from the desktop! It's free to get started and sign up is instant. Publish your first map within minutes. Amazon Web Services - Amazon EC2 provides an ideal environment for running your ArcGIS Server applications. Amazon EC2 allows you to quickly configure ...


7

This is a viciously broad question. It depends heavily on what your resources are, and what your goals are. On the simple end, if you're just looking to be able to query GIS data, you could simply load it into a desktop application like QuantumGIS along with a generic basemap (if you need it). On the other hand, If you're trying to build a web application ...


7

Dropbox/Google Drive work on the principle that when a file gets modified, it will upload the file into the cloud. Then when your on your other machine, it will download the latest copy. This works great for small files. GIS data can often be large filesizes. If I edit one feature attribute in a layer that is 2GB big, there will be a lot of ...


7

I have done several projects in this regard, but at the end they always ended up being custom solutions that basically separated the problem in grids did the processing in each individual node and copied the result to a temp table / data store merged all the solutions to a single result table and optionally handled boundary conditions. Handling boundary ...


6

Here is a page with answers to common questions: Questions and Answers about ArcGIS Server on Amazon EC2 And here's a recorded training seminar: Running ArcGIS Server on Amazon EC2


6

stored in file geodatabases File geodatabases are the enemy of open source - if you change this to PostGIS or shapefiles, or similar, you'll have more luck. Otherwise you're looking for a ton of features. You'll have some luck with GeoServer, but otherwise you might want to reconsider the scope of what you're looking for.


5

A VM in the cloud gives you a quicker, lower-cost startup. You can get running immediately with no machine purchase costs. Also there are fewer system maintenance issues. If you're short on IT skills or assistance then that's something to consider; esp for 24/7 coverage. Instant scalability is another advantage. But obviously the initial costs of your own ...


4

My suggestion would be to use the osgeo stack. Specifically, I have used this stack in the Amazon Cloud (AWS) to serve out large raster and vector data sets. Postgresql with postgis stores my vector data Geoserver / Geowebcache servers the vector data and tiles those large datasets for serving. Everything runs through the browser using OpenLayers. I ...


3

I've been in discussion with esri. If you are loooking to learn, but not deploy commercially. They allow to "bring your own license" with the EDN (ESRI developer network for a couple of k). Otherwise you have to either pay for the AMIs they have or bring your own license "commercial". There is no open sandbox so to speak. After that it is "just" like ...


3

Thinkgeo seems to have some info. aws.amazon.com There also seems to be an AMI ready built. geonetwork Standard Instances Small Instance (Default) 1.7 GB of memory, 1 EC2 Compute Unit (1 virtual core with 1 EC2 Compute Unit), 160 GB of local instance storage, 32-bit platform Large Instance 7.5 GB of memory, 4 EC2 Compute Units (2 virtual cores with 2 ...


3

From Experience the cloud option outweighs your own dedicated server. Why Scaleable - not days or weeks but done in minutes. It can also be downscaled in the future. (go from 10gb to 1tb - 4 core to 16 cores) As CDBrown mentions - Uptime and very rarely downtime. 99.98% This alone outweighs your own server. (when is goes down 4.59pm on Friday afternoon) ...


3

As I see it here are some things to consider. For Amazon Cloud - offsite virtual environment - security and scalable up time - 0 downtime - admin available where ever you are Against Amazon Cloud - need to place expensive software on someone else's machine - need to place possibly sensitive data on someone else's machine - need to spend a lot of time ...


3

One of the key benefits of cloud computing is scalability and cost. In a cloud-based setup, you might have 1 virtual server running your GIS application (e.g. a web application showing flood events across the country). As demand for the application rises, new virtual machines switch on/off (automatically if thats how you set things up). In the middle of ...


3

What you want can all be done with several different open source components. Nevertheless, your requirements are too ambitious, and you will not find a single package/installer that is a turn-key solution. Host it at AWS. Look at Geoserver. Store it in PostGIS. Custom build with Django. These things are Open Source, so it means you have different ...


2

Regarding GIS and cloud computing in its current state I think the biggest deciding factors would be how many users you have and where they are located. If the end users who will be accessing the services and data you place in the cloud are from various independent locations with no common network infrastructure then cloud computing might be for you. While ...


2

One big pro of having your own physical machine (... that you can physically access!) is sneakernet data loads. This is less of an issue if you don't host your own data - but if you have gigabytes or terabytes of data and are constantly updating it, you're going to have to invest time and money [bandwidth] transmitting it "into the cloud". However, if you ...


2

You might want to give Appistry a look. It purports to enable migrating of existing applications to private cloud infrastructures. There may be other projects with a similar aim: rather than figuring out again and again for every application the very complex nut of breaking down and distributing tasks to parallel processing, make a library or platform which ...


2

The old school parallel programming methodology is to just store a state + the parcels that touch it on each processor then it is embarrassingly easy to parallelize. But given the variation in size of US states you'd get better performance by splitting the country up into grid cells (again with the touching halo of parcels) and sending each grid cell to ...


2

The first thing to be concerned about with this problem is what data is needed where and when. To do so, I usually start with the stupid, serial version of the problem. Find all parcels valued over x $/acre that are within y feet of another parcel that is valued at less than z $/acre. foreach p in parcels { if value(p) > x { foreach q in parcels { ...


2

OpenGeo (stack built around GeoServer and PostGIS) have an AMI available and a quick intro to AWS. It worked well for me, with a little tweaking. It's fairly straightforward to get up and running and you can save your own AMI to Amazon S3 once the server's set up the way you want it. The Firefox add-ins for AWS are very handy for managing S3 and EC2 (s3 ...


2

There was a very good webinar put on this topic that gave a case study. It only took them 7 hours to move their application to EC2. It sounded like they had a very successful experience. Here is a link to the slides: http://www.slideshare.net/dbouwman/arcgis-server-in-ec2 During this webinar esri announced they are planning to offer a 60 trial version ...


2

Google offers some nice tools. Check out google drive, fusion tables and shpescape.com (one of several sites that lets you import gis shapefiles directly to fusion tables) There's a whole api built around this so you won't have to roll any of the client/server stuff yourself and I am only guessing, but i'd imagine being a google tool that it scales.


2

Amazon EC2 will be a good solution for your Geodatabases (though can get expensive being ESRI) Scalable on demand—If you need more computing power, you can launch additional EC2 instances, which you can think of as virtual servers on Amazon's cloud that are all created from the same parent AMI. Creating new instances can even be done ...



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