Shelter from the Storm: Building a Safe Archive in a Hostile World.
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ABSTRACT: As is becoming commonly known, there is an explosion happening in the amount of scientific data that is publicly available. One challenge is how to make productive use of this data. This talk will discuss some parallel and distributed computing projects, centered around virtual astronomy, but also including other scientific data-oriented realms. It will look at some specific projects from the past, including Montage(1), Grist(2), OurOcean(3), and SCOOP4, and will discuss the distributed computing, Grid, and Web-service technologies that have successfully been used in these projects.ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS 2006: COOPIS, DOA, GADA, AND ODBASE PT 2, PROCEEDINGS; 01/2006
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ABSTRACT: Grid computing has emerged as a promising area for solving complex problems and sharing resources among a large number of institutions. On the other hand, GADA workshops have arisen as a forum for researchers in grid computing, and more specifically in data management and analysis on grids. This paper analyses the works presented in GADA workshops, with the aim of evaluating the current research and foreseeing the evolution of this discipline in the near future.
Conference Proceeding: Visualizing Katrina - Merging Computer Simulations with Observations.[show abstract] [hide abstract]
ABSTRACT: Hurricane Katrina has had a devastating impact on the US Gulf Coast, and her effects will be felt for many years. Forecasts of such events, coupled with timely response, can greatly reduce casualties and save billions of dollars. We show how visualizations from storm surge and atmospheric simulations, were used to understand the predictions of how strong, where, and when flooding would occur in the hours leading up to Katrina's landfall. Sophisticated surface, flow and volume visualization techniques show these simulation results interleaved with actual observations, including satellite cloud images, GIS aerial maps and LIDAR showing the 3D terrain of New Orleans. The sheer size and complexity of the data in this application also motivated research in efficient data access mechanisms and rendering algorithms. Our goals were to use the resulting animation as a vehicle for raising awareness in the general populace to the true impact of the event, to create a scientifically accurate representation of the storm and its effects, and to develop a workflow to create similar visualizations for future and simulated hurricanes. Screenings of the animation have been well received, both by the general public and by scientists in the field.Applied Parallel Computing. State of the Art in Scientific Computing, 8th International Workshop, PARA 2006, Umeå, Sweden, June 18-21, 2006, Revised Selected Papers; 01/2006
Shelter from the Storm: Building a Safe Archive
in a Hostile World
Jon MacLaren, Gabrielle Allen, Chirag Dekate, Dayong Huang,
Andrei Hutanu, and Chongjie Zhang
Centre for Computation and Technology,
Louisiana State University, Baton Rouge, LA 70803.
Abstract. The storing of data and configuration files related to scien-
tific experiments is vital if those experiments are to remain reproducible,
or if the data is to be shared easily. The prescence of historical (observed)
data is also important in order to assist in model evaluation and devel-
opment. This paper describes the design and implementation process for
a data archive, which was required for a coastal modelling project.
The construction of the archive is described in detail, from its design
through to deployment and testing. As we will show, the archive has
been designed to tolerate failures in its communications with external
services, and also to ensure that no information is lost if the archive
itself fails, i.e. upon restarting, the archive will still be in exactly the
The Southeastern Coastal Ocean Observing and Prediction (SCOOP) Program’s
Coastal Model Project , is an ongoing collaboration between the modeling
research community and operational agencies, such as the National Oceanic and
Atmospheric Administration (NOAA). The project aims to take today’s cutting-
edge activities from the research community, and develop these so they can form
the basis for tomorrow’s operational systems.
Part of this project’s work involves the regular execution of coastal modeling
codes, such as ADCIRC  and SWAN , for various geographical regions.
Additional runs of some codes are performed to predict the path and effects of
ongoing tropical storms and hurricanes; the results from these runs are passed to
groups involved in evacuation planning. The project also tries to verify the ac-
curacy of the coastal models by verifying the predictions the codes make against
real-world observed data.
To support this work, a data archive was required which would store:
– atmospheric model outputs (wind data),
– results generated by the hydrodynamic models, which use the atmospheric
model outputs for input (wage/surge data), and
– observational data to be used for verification of model results (sensor data).
The archive would therefore form a backbone for the research efforts of the
project, and as such, have to be both highly available, and reliable.
To meet this need, a data archive was constructed at the Center for Compu-
tation and Technology. Although supporting the SCOOP Coastal Model Project
was our prime objective, we wanted to be able to re-use most of the archive’s
functionality, and code, for other efforts with data storage requirements, e.g. our
group’s numerical relativity work.
This paper describes the construction of this archive in detail. Section 2
briefly discusses data storage requirements, then describes the design of the
archive service; Section 3 describes the archive’s implementation. Section 4 de-
scribes how APIs and tools were developed to allow easy access to the archive,
and Section 5 explains how good engineering practices were used to ensure reli-
ability and code re-use. Finally, Section 6 explains some ideas for future work,
and Section 7 gives our conclusions.
2Design and Architecture
The data storage requirements for the SCOOP Project are simple. The files to
be stored are small (no more than a few MB at most) so they can be easily
moved to the archive.1In addition, there was no requirement to provide any
kind of access control.
To complement the archive, a Metadata Catalog would be provided, which
would store information about the model configurations used to generate the
stored data. This catalog should be the first port of call for people looking for
data outputs from the project, and can provide references to the location of the
data, in response to users’ searches. As the catalog is not the subject of this
paper, it is not described here, although interactions between the archive and
the catalog are.
The architecture for the archive is shown in Figure 1. In more detail, the
steps for uploading files to the archive are as follows:
U1 The client contacts the archive, providing a list of files which they wish to
upload to the archive. The archive decides where each file will be located
within the archive.2The archive’s response groups the original files into one
or more transactions, each of which is associated with: a location in the
storage area (specified by a set of URLs for various scheme names); a subset
of the list of files; and an identifier which the client uses in later interactions.
1At the time we began construction of the archive, it was not clear to us what volume
of data would be generated by the project each day, nor was it clear how long
data needed to be kept for. We have since discovered that the project generates
approximately 1 TB of data per month.
2Within the SCOOP Project, there is a File Naming Convention, allowing the archive
to deduce metadata from the names of the files, and thus determine the location of
each file within the archive’s directory structure. Files belonging to the output of a
single run of a model code will be stored in the same directory. New directories for
new code runs are created automatically.
D1. Initial Query
D3. Retrieve Real
file via a URL
D2: Get URLs for
U2. Upload files directly
to storage area
U3. Inform service
U5. Inform Catalog
of new files
Fig.1. Basic architecture for the SCOOP Archive, showing steps for Uploading
and Downloading files.
The following steps are then carried out for each of the transactions.
U2 The client uploads the files to the archive storage with some third-party
software, e.g. GridFTP [8,2], and a URL given to it by the archive.
U3: request After the client has uploaded the files to the location, it informs
the archive that the upload is complete (or aborted), using the identifier.
U4 The archive contructs Logical File Names (LFNs) for the files which have
been uploaded, and adds mappings to Logical File Catalog that link the
LFNs to various URLs that can be used to access the physical files.
U5 The archive informs the catalog that there are new files available in the
archive, providing the LFNs.
U3: response The archive returns the LFNs to the client.
The steps for downloading a file from the archive are as follows:
D1 A client queries the Metadata Catalog to discover interesting data, e.g.
ADCIRC Model output for the Gulf of Mexico region, during June 2005.
Some Logical File Names (LFNs) are returned as part of the output, together
with a pointer to the Archive’s Logical File Catalog.
D2 The client chooses some LFNs that they are interested in, and contacts the
Logical File Catalog service to obtain the files’ URLs.
D3 The client picks URLs (based on scheme name, e.g. gsiftp for GridFTP)
and downloads the files directly from the Archive Storage.
Note that this simply describes the sequence of interactions that are exchanged
in order to achieve these tasks. We will later show that the clients indicated in
the diagram can be either command-line tools, or a portal web-page.
3Implementing the Archive Service
The architecture was refined into a message sequence diagram, and implemented
using Web Services. Early on, we chose to use the Grid Application Toolkit
(GAT) , developed as part of the GridLab project , to help with file move-
ment, and also to provide access to Logical File services. The GAT wraps dif-
ferent underlying technologies (using “adaptors”), and so provides consistent
interfaces. Here, the underlying Logical File Catalog is a Globus RLS, but this
could be replaced with a similar component, without changing the archive’s
code. Our desire to use the GAT led us to select C++ as the language to use for
implementing the service, which in turn led to us using the Web Service tool-
ing provided by gSOAP [6,7]. Following the advice from the WS-I Basic Profile
1.1 [5, Sec. 4.7.4], we avoided using RPC/Encoded style3for our services. Instead
we chose Document/Literal style, first designing the XML messages that would
be exchanged, then producing XML Schema and WSDL definitions. From these
definitions, the gSOAP tooling was used to automatically generate code stubs.
During the upload process, the archive passes back URLs for a staging area,
rather than allowing clients to write directly to the Archive Storage. This also
makes it simpler to prevent additional (i.e. unauthorized) files from being in-
serted into the archive. A distinct staging directory is created for each transac-
tion identified by the archive.
4 Archive Interfaces and Tools
We have provided two complementary mechanisms for clients to download data,
– Command-line tools, e.g. getdata; and
– A portal interface, built using GridSphere , an open-source portal frame-
work,4, also an output from the GridLab project , which uses JSR 168
compliant portlets .
The getdata tool has a simple syntax, encapsulating the client side of the mes-
sage exchanges with the Logical File Service and the download from the Archive
Storage, and can choose between different protocols for downloading the data.
This was achieved using the GAT, making getdata easily extensible if new proto-
cols need to be added. Currently, GridFTP and https downloads are supported.
Through the portal interface, users can access the same functionality as with
the command-line tools. Users can search for files, and download them, either
3Restriction R2706 (which also appeared in Basic Profile 1.0) states: “A
wsdl:binding in a DESCRIPTION MUST use the value of “literal” for the
use attribute in all soapbind:body, soapbind:fault, soapbind:header and
4Available for download from http://www.gridsphere.org/ at time of writing.
through the browser, or perform a third-party file transfer via GridFTP. The
portal interface, shown in Figure 2, integrates this and other capabilities, such
as Grid monitoring, Job Submission and Visualization into a single interface.
Fig.2. Screen capture from the SCOOP Portal, showing a typical search.
In order to simplify the construction of clients, a two-layered C++ client API
was written and, like the service, was based on gSOAP. The first level of the API
neatly encapsulates each of the two message exchanges, labeled U1 and U3 in
Figure 1, into two calls start upload and end upload.
A higher-level API with a single call, upload, is also provided. This encap-
sulates the entire process, including the uploading of the files themselves. The
upload call has the following signature:
bool upload(std::vector<std::string>& uploadFiles,
The provision of such a layered API makes the construction of tools far simpler.
Currently, files can only be uploaded via a command-line tool, upload, which
allows a variety of transport mechanisms to be used to copy files into the archive.
Even though the interactions with the archive service are more complicated than
for downloading files, the command-line syntax remains trivial.
upload -gsiftp -done rm SSWN*.asc
This example will upload all “.asc” files in the current directory starting “SSWN”
(produced using the SWAN code), transferring the files with GridFTP (GridFTP
uses URLs with the scheme name “gsiftp”) and will remove the files if they are
successfully uploaded (specified by “-done rm”).
5 Ensuring Stable, Robust, Re-usable Code
A key challenge when building distributed systems is tolerating problems with
connectivity to external services. However, it would also be reckless to assume
that our archive service would be perfectly reliable. No feasible amount of testing
is sufficient to remove all the bugs from even a moderately sized program. In
addition to the archive code, we are also relying upon the GAT and gSoap, (not
to mention the Linux C library, compilers and operating system).
We have employed a number of techniques while designing the archive to
make it as reliable as possible. These techniques, plus other “good practices”
that we have employed, are described below.
5.1 Tolerating Failure in Remote Services
In the architecture shown in Figure 1, the Metadata Catalog is clearly a distinct
component. However, in our implementation, from the perspective of the Archive
Service component of the Archive, both the Metadata Catalog and the Logical
File Catalog are remote components; only the Storage component is physically
co-located with the Archive Service.
As stated earlier, remote components may become unavailable temporarily,
only to return later. These partial failures are not encountered in “local”
computing. If you lose contact with a program running on your own system,
it is clear that some sort of catastrophic failure has occured; this is not the
case in a distributed system. For an excellent discussion on partial failures and
other inherent differences between local and distributed computing, the reader
is directed to .
Here, we have tried to insulate ourselves from partial failure as far as possible.
Following the advice in , we have made the partial failure explicit in the
archive service interface. In the response part of interaction U3, when the user
is returned the set of logical files corresponding to the newly uploaded files, they
are told which of these logical files have been successfully stored in the Logical
File Catalog.5The user knows that they need take no further action, and that
the logical files will be uploaded to the Logical File Catalog when it becomes
5Similarly, they are informed of whether or not the files have been registered with the
5.2Recovering from Failures in the Archive
Interactions with the Archive are not stateless. Transaction IDs are created,
and associated with areas in the Archive Storage, and with files that are to be
uploaded. These IDs are used in later interactions and must be remembered by
the Archive if it is to function correctly.
Given what was stated earlier about the reliability of our own programming,
and our operating environment, we chose to place all such state into a database
located on the machine with the Archive Service. The “pending” insertions for
the Logical File Catalog and Metadata Catalog (described in the previous sec-
tion) are also stored in this database. Thus, if the service terminates for some
reason, and restarted, it is able to pick up from exactly where it left off.
Note that we can also correctly deal with partial failure in the case where
a transaction might be completed, but the response fail to reach the client.
The client can safely retry the complete/abort transaction operation until they
receive a response. If they receive a message stating that the complete/abort has
succeeded, then they have just now terminated the transaction. If they receive
a message stating that the transaction is unknown, then a previous attempt to
complete/abort the transaction must have succeeded.
5.3Keeping Domain-Specific Code Separate
Although the archive was primarily created for use in the SCOOP project, we
have tried to keep project-specific functions separate from generic functions.
Specifically, SCOOP uses a strict file naming convention, from which some of
the file’s metadata may be extracted. The filename therefore dictates where the
file should be stored, etc. To keep the project-specific code separate, methods
on a FilingLogic object are used to decide where to place all incoming files.
Different subclasses of the FilingLogic class can be implemented for different
“flavours” of archives.6
Through extensive testing, we have determined that the archive is stable. During
initial trials, we used multiple clients to simultaneously upload files in rapid suc-
cession. Over one weekend, 20,000 files were successfully uploaded. The archive
remained operational for a further three weeks (inserting a further 10,000 files),
until a change to the code necessitated that it be manually shutdown.
During this time, we monitored the size of the Archive Service process. It
seems that the program does leak a small amount of memory. After a number of
months, this would likely cause the process to fall over. To prevent this happen-
ing, we have chosen to manually shut the service down every 14 days, and then
6Undoubtedly when the archive is first applied to a new project, there will be new
requirements, and the FilingLogic interface will change. Nonetheless, this transition
will be greatly simplified by the existence of this boundary.
restart. This “preventative maintenance” ensures that the archive does not fail
Although we have strived to make the archive as reliable as possible, there is
a limit to how much we can improve the availability of the archive while it still
resides on a single machine. The hardware in the archive machine is not perfect,
nor are we using an Uninterruptable Power Supply (UPS). The campus network
also causes periodic failures.
It seems that replicating the data archive would yield the biggest improve-
ments in reliability.
This first version of the archive provides us with a useful basis for future de-
velopment. There are a number of ways in which we want to extend the basic
functionality described above, the two most important of which are explained
6.1Transforming Data on Upload/Download
Currently, the archive stores data in the form in which it is uploaded; download-
ing clients receive the data in this same format. We wish to support the following
– The compression of large ASCII-based files when they enter the archive, and
their decompression when they are downloaded (preferably after they have
reached the client).
– The partial retrieval of a dataset. Some of the data stored in the archive is in
NetCDF format , which supports retrieval of subsets of variables, ranges
of timesteps, etc.
– Retrieval of data in different formats, e.g. retrieving single precision data
from a double precision file.
To support this type of operation, we are proposing to associate a specification
with each file that specifies the current format which the file is in, the type of
compression, etc. Specifications are used at upload and download time; files may
be transformed by the archive upon arrival.
One of the key goals of the SCOOP Project is to improve responsiveness to
storm events, such as hurricanes, which are relatively common in the Southern
7If for some reason, the archive needed to remain operational during the scheduled
maintenance time, this could easily be moved or canceled (provided many successive
shutdowns are not canceled).
United States. When a hurricane advisory arrives at the archive, it should trigger
high-priority forecasts for the current location of the storm.
To support this work, we have recently implemented a simple interface that
can be built upon to perform sophisticated patterns of notification. When a
file is ingested into the archive, a message is sent to the FilingLogic object.
The SCOOP implementation of this executes a script (forked to run in the
background, so as to not affect the archive’s performance), passing the Logical
and Physical File Names as parameters.
6.3Lifetime Management for Data
Currently, data is removed from the archive automatically after a fixed time.
It should be possible for uploading clients to request storage for a particular
duration. It should also be possible for this lifetime to be altered by other,
We have described the construction of a reliable data archive, constructed to
satisfy storage requirements from a coastal modeling project. A number of tech-
niques were employed, from the design phase through to the final testing, to
We also showed how the archive was designed so that it could be re-used in
other projects. In particular, we endeavoured to keep all project-specific code
separate from the generic code, and provided an internal API which allows new
project-specific code to be easily provided.
It is likely that future versions of the archive will rely on other systems
for backend data storage. The most obvious candidate is the Storage Resource
Broker (SRB) from SDSC , which provides excellent support for managing
highly distributed data stores, and which would also satisfy some of our new
requirements from Section 6, e.g. the retrieval of subsets of data.
This work was made possible by funding from the Office of Naval Research and
the National Oceanic and Atmospheric Association, received through Louisiana
State University’s participation in the Southeastern Universities Research Asso-
ciation (SURA) Southeastern Coastal Ocean Observing and Prediction (SCOOP)
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