From deelman@ISI.EDU  Fri Aug 16 20:56:55 2002
From: deelman@ISI.EDU (Ewa Deelman)
Date: Fri, 16 Aug 2002 12:56:55 -0700
Subject: [Arch-paper] filtering services
Message-ID: <41C31855E83ED31199D300C04F57A073F1B6C9@hermes.isi.edu>

F.	Local Data Filtering Service
As the size of the data available in the data grid grows, it is ever more
important to efficiently deliver large amounts of data over the wide area.
Besides addressing the issue of high performance data transfer, we also need
to look at the ability of subsetting data being sent based on the user or
application requirements. Optimally, only the exact data requested is sent.
Users or applications do not require all the data to be available in a given
dataset or they may require that the data in the set be presented in a
certain way. 

A local data filtering service provides a means of preprocessing the data at
the server before sending it over the network.  The processing can be done
by more than one filter. Some filtering services can be applicable to many
applications, such as filtering based on spatial ranges, some are more
application specific and need to be provided by the user. The filtering
services need not be run on the server where the data is stored. They can be
run on hosts which are "near" to the data server (in terms of low network
latency and high bandwidth).  Because filters can be provided by the users
and be executed on resources that the user does not necessarily have direct
access to, the filters need to be able to run in a restrictive environment,
which would prevent them from harming the underlying execution system.


L.	Collective Data Filtering Service

In data grids it is often the case that particular data items are accessed
often at a particular time by more than one user. This can happen when a set
of data promises to have within it scientifically interesting results and is
accessed by many users in the hopes of making a discovery. This data can
then undergo analysis which, at least in the initial stages, can be common
to a group of clients. Such analysis could involve removing noise from a
signal, resampling etc.  In these situations, collective data filtering
services can be used to filter the data on the server side and place the
common filtered data products close to the requestors of the data. This
reduces the amount of computation that needs to be done by reusing the
already generated data products and with proper placement it reduces the
user's access time to the data.

-Ewa
 


Ewa Deelman, PhD
USC/Information Sciences Institute,       Phone: (310) 448-8408 
4676 Admiralty Way, Suite 1001            Fax:   (310) 823-6714 
Marina del Rey, CA 90292-6695             www.isi.edu/~deelman




From deelman@ISI.EDU  Sat Aug 17 00:19:02 2002
From: deelman@ISI.EDU (Ewa Deelman)
Date: Fri, 16 Aug 2002 16:19:02 -0700
Subject: [Arch-paper] request interpreter and concrete planner sections
Message-ID: <41C31855E83ED31199D300C04F57A073F1B6DC@hermes.isi.edu>

Hi,
I took a stab at Kurt's writeup and put some of my thoughts into it. I also
left some of Kurt's the text under "not incorporated yet", thinking it might
belong to a different section--different services.

-Ewa

 

Request Interpretation Service

At the high level, we can differentiate applications based on how they
specify their requests for data. Some can use application-specific metadata
which needs to be mapped to a set of data products or to a set of requests
for data. Other applications can already specify their requests in an
abstract form, an abstract DAG (aDAG), which defines at a logical level the
computations that need to be performed and the data needed for the
computation.  The aDAG also specifies the dependencies between the
computations. Finally, at the lowest level, the applications can specify
their requests via concrete DAGs (cDAG), which specify the computations
requested and the locations where they are to execute and the exact
locations of the input data.

Although users and applications can form requests in the three ways
mentioned above, the data grid components can also provide the functionality
to generate a cDAG based on a request containing application-specific
metadata. 

The request interpreter, which is an application-specific component that
takes a domain-specific requests and translated it into an abstract
representation (abstract DAG) of the computation (tasks) that need to be
performed to satisfy the request and the order in which they need to be
executed. This aDAG also contains information about which logical files are
needed by the computations. However, the request interpreter does not
provide any information about where the jobs need to be executed or which
storage systems need to be accessed to retrieve the data.
Some application can build their request interpreters based on metadata
catalogs, which can name the logical files which contain data with the
particular characteristics. The set of logical file names can be used to
specify the desired data product. Alternatively, the domain-specific
attributes can be mapped to an aDAG required to produce the data, if such
mapping is possible. The mapping can be done algorithmically or through the
use of Virtual Data Services [chimera] or both. 

Concrete Request Planning Service

Based on the logical execution plan, the "Concrete Request Planning Service"
produces a physical execution plan. This plan can be subject to various
optimization strategies and must adhere to the resource usage policies for a
given community and user. It can optimizes the usage of Grid resources,
optimize the execution of a specific request of a set of request.  The
latter is especially important in cases where a large number of users are
competing for limited resources. The system then needs to provide fair
treatment based on usage agreements.  

Optimization can refer to various metrics, such as performance and/or
reliability and can be carried using various system information such as
workload and features of computing and storage resources, location of data,
network load.  

The concrete request planning service consults various information services
to perform the mapping from the abstract to the concrete and to perform the
desired optimization. Among the services being consulted are services that
identify the set of available compute and storage resources, services that
provide network performance information, such as the latency and bandwidth
between grid resources, or at a higher level, expected file transfer costs
between particular resources.  Information about specific replicas of a
given set of LFNs is retrieved from the "Replica Location Service". 

On one hand, the concrete request planning service can make an exact plan of
computation based on the current information about the system. At the other
extreme, the planner can leave many decisions up to the executor, it can for
example give the executor a choice of compute platforms to use, a choice of
replicas to access etc. At the time the executor is ready to perform the
computation or data movement, the executor can consult the information
services and make local planning decisions.

The benefit of the first approach is that the planner can aim to optimize
the plan based on the entire structure of the DAG, however, because the
execution environment is very dynamic, by the time the tasks in the DAG are
ready to execute, the environment might have changed so much that the
execution is now far less optimal. 

If the decisions are left to the executor, it can use the information
services to find out about the state of the resources and the location of
the data and make a locally optimal decision. However, because the executor
does not have global information about the request it could make potentially
expensive decisions.



Not incorporated yet:

In addition to the input data, a job usually specifies some minimal
requirements for compute resources. Depending on the type of job (see use
cases), priorities or hints with respect to storage and compute resources
can be provided.

When optimizations in terms of computation and storage performance are
treated separately, We can define a "Computing Resource Broker (CRB)" as a
service that "optimizes" the compute resources for a given job. Similarly,
we can define a "Storage Resource Broker (SRB)" as a service that optimizes
the storage resources for a job. The "Concrete Request Planning Service"
needs to start a negotiation between the CRB and the SRB in order to match
between the requirements of the job and the available resources. Depending
on specific "hints", either compute resource or storage resources can be
prioritized and thus the set of candidate resources can be reduced.

One goal of the SRB is to select the optimal replicas depending on their
locations and their expected file transfer costs. The SRB also deals with
the complementary problem of minimizing the overall cost of file access on
the Grid in the ``long-term'', given a finite amount of storage resources. 


Information about access history can be collected at several levels:
- Logical level, i.e. access history about sequence of LFNs
- Physical level, i.e. access history about replicas (SFN) at specific
storage resources
Statistics may include time series about requests for LFNs/SFNs and users
who initiated the file request.

Ewa Deelman, PhD
USC/Information Sciences Institute,       Phone: (310) 448-8408 
4676 Admiralty Way, Suite 1001            Fax:   (310) 823-6714 
Marina del Rey, CA 90292-6695             www.isi.edu/~deelman




From annc@ISI.EDU  Sat Aug 17 00:54:12 2002
From: annc@ISI.EDU (Ann Chervenak)
Date: Fri, 16 Aug 2002 16:54:12 -0700
Subject: [Arch-paper] my sections
Message-ID: <5.1.0.14.2.20020816163615.00aa7520@tnt.isi.edu>

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Replica Location Service

A replica location service (RLS) is a system that maintains and provides 
access to information about the physical locations of copies of data 
items.  In data grids, it is often desirable to create remote replicas of 
data elements to reduce access latency, improve data locality, and increase 
the robustness, scalability and performance of distributed applications.  A 
replica location service registers the existence of replicas and answers 
queries about replicas.  Typically, the RLS provides mappings between 
logical names for data items and one or more physical locations for copies 
of the item on storage systems.  Alternatively, the RLS may provide a 
mapping between a logical name for a data item and another level of logical 
names for replicas, for example, a site-specific name that does not specify 
a particular physical location for the replica.  This latter scheme allows 
a site or storage system to move the data item internally without informing 
the RLS.

The RLS must scale both in size and performance to meet the needs of the 
data grid.  An RLS might be required to register the existence of millions 
of logical data items and thousands of replicas per item.  Update and query 
rates requirements for the RLS will depend on the patterns of data 
creation, replication and access generated by the application community.

The information stored in the Replica Location Service is one type of 
metadata, or descriptive information about data items.  In some data grids, 
rather than having a separate RLS, the replica location metadata may be 
merged with other types of metadata and stored in a general Metadata Service.

Reliable Replication Service

A Reliable Replication Service (RRS) uses two lower-level services:  the 
Replica Location Service (RLS) and the Reliable File/Object Transfer 
Service (RFT).  The purpose of the Reliable Replication Service is reliably 
to create replicas of existing files or data objects and register them with 
the RLS.  This service uses the Reliable File/Object Transfer Service to 
copy a data item from a source to a destination storage system.  Only when 
the copy operation is complete is the data item registered in the RLS.  If 
the data copy operation or the RLS registration operation fails for any 
reason, then the Reliable Replication Service must make sure that the state 
of the RLS remains unchanged, if necessary, rolling back any state changes.

The types of rollback operations that are required depend on the 
application.  Consider a failed data transfer operation that copies only a 
portion of a data object to the destination storage system.  Recovery from 
the failure might require that the partial data object be deleted from the 
destination storage system.  Conversely, an application might hope to retry 
the copy operation in the future and would like to preserve the bytes that 
have already been transferred to the destination storage system.  Another 
failure scenario occurs when a data item has been successfully copied to 
the destination storage system, but the RLS registration operation 
fails.  In some instances, a rollback operation might require that the file 
be deleted from the destination storage system, while in others it is 
sufficient that the state of the RLS be unchanged.

A Reliable Replication Service may allow certain pre-processing operations 
to be specified and performed prior to registering the new data object with 
the RLS.  Some examples of post-processing operations include registering 
the new data object with a local database service, performing a checksum on 
the data contents, or performing data compression or decompression.  The 
exact types of post-processing operations allowed by an RRS depend on the 
implementation.  The RRS must be able to roll back any state changes made 
by post-processing operations if failures occur.

Metadata Service

A Metadata Service provides a mechanism for storing and accessing metadata, 
which is information that describes data items.  Typically, a Metadata 
Service (MS) provides the ability to query based on metadata attributes 
rather than by names of data items.  In addition, the MS may provide 
management of logical collections data items and of containers that consist 
of small data items that are stored, moved and replicated together. The MS 
must maintain strict consistency over its contents.  Inaccuracies in the 
metadata database potentially result in incorrect identification of data 
items, which would produce incorrect analyses.  The Metadata Service may be 
used by data browsing and visualization applications to identify desired 
data.  The MS is also used by higher-level data grid components such as the 
Request Planner to identify the logical data items needed to perform a 
desired computation.

There are various types of metadata, including logical and physical 
metadata.  Which types of metadata are included in a particular Metadata 
Service depends on the application domain and on the existence of other 
services, for example, whether there is a separate Replica Location Service 
in the data grid.  Physical metadata relates to the actual location of the 
data item and the characteristics of a given storage system.  Examples of 
physical metadata include data item size, access permissions for the data 
item on a storage system, and last modification time of the data.  Physical 
metadata is generally maintained on storage systems (for example, as part 
of a file system) and may also be replicated in a Metadata Service.

Logical metadata describes the contents of a data item independent of the 
location of a specific physical instance of the data item.  One example of 
logical metadata is information about how data items were created or 
modified (e.g., the name and description of the logical data item's creator 
or modifier, what experimental apparatus and input conditions produced the 
data item, or what simulation or analysis software was run on which 
computational engine with which input parameters).  Another example of 
logical metadata is a description of what the data item represents (e.g., 
precipitation measurements over a certain region during a certain time 
interval, or collisions in a particle collider recorded during a specified 
interval).

While some metadata attributes will be generally useful across a variety of 
applications, each application domain is likely to adopt domain-specific 
metadata conventions and schema.  Thus, data grid Metadata Services must be 
customizable and extensible.  These services may actually consist of a 
federation of metadata catalogs or databases that, used in combination, 
provide data descriptions required by application software and other data 
grid components.

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Content-Transfer-Encoding: quoted-printable

<html>

<dl><font face=3D"Arial, Helvetica">
<dd>Replica Location Service <br><br>

</dl>A <i>replica location service (RLS)</i> is a system that maintains
and provides access to information about the physical locations of copies
of data items.&nbsp; In data grids, it is often desirable to create
remote replicas of data elements to reduce access latency, improve data
locality, and increase the robustness, scalability and performance of
distributed applications.&nbsp; A replica location service registers the
existence of replicas and answers queries about replicas.&nbsp;
Typically, the RLS provides mappings between logical names for data items
and one or more physical locations for copies of the item on storage
systems.&nbsp; Alternatively, the RLS may provide a mapping between a
logical name for a data item and another level of logical names for
replicas, for example, a site-specific name that does not specify a
particular physical location for the replica.&nbsp; This latter scheme
allows a site or storage system to move the data item internally without
informing the RLS.<br><br>
The RLS must scale both in size and performance to meet the needs of the
data grid.&nbsp; An RLS might be required to register the existence of
millions of logical data items and thousands of replicas per item.&nbsp;
Update and query rates requirements for the RLS will depend on the
patterns of data creation, replication and access generated by the
application community.<br><br>
The information stored in the Replica Location Service is one type of
metadata, or descriptive information about data items.&nbsp; In some data
grids, rather than having a separate RLS, the replica location metadata
may be merged with other types of metadata and stored in a general
Metadata Service.&nbsp; <br><br>

<dl>
<dd>Reliable Replication Service<br><br>

</dl>A Reliable Replication Service (RRS) uses two lower-level
services:&nbsp; the Replica Location Service (RLS) and the Reliable
File/Object Transfer Service (RFT).&nbsp; The purpose of the Reliable
Replication Service is reliably to create replicas of existing files or
data objects and register them with the RLS.&nbsp; This service uses the
Reliable File/Object Transfer Service to copy a data item from a source
to a destination storage system.&nbsp; Only when the copy operation is
complete is the data item registered in the RLS.&nbsp; If the data copy
operation or the RLS registration operation fails for any reason, then
the Reliable Replication Service must make sure that the state of the RLS
remains unchanged, if necessary, rolling back any state changes.&nbsp;
<br><br>
The types of rollback operations that are required depend on the
application.&nbsp; Consider a failed data transfer operation that copies
only a portion of a data object to the destination storage system.&nbsp;
Recovery from the failure might require that the partial data object be
deleted from the destination storage system.&nbsp; Conversely, an
application might hope to retry the copy operation in the future and
would like to preserve the bytes that have already been transferred to
the destination storage system.&nbsp; Another failure scenario occurs
when a data item has been successfully copied to the destination storage
system, but the RLS registration operation fails.&nbsp; In some
instances, a rollback operation might require that the file be deleted
from the destination storage system, while in others it is sufficient
that the state of the RLS be unchanged.&nbsp; <br><br>
A Reliable Replication Service may allow certain pre-processing
operations to be specified and performed prior to registering the new
data object with the RLS.&nbsp; Some examples of post-processing
operations include registering the new data object with a local database
service, performing a checksum on the data contents, or performing data
compression or decompression.&nbsp; The exact types of post-processing
operations allowed by an RRS depend on the implementation.&nbsp; The RRS
must be able to roll back any state changes made by post-processing
operations if failures occur.&nbsp; <br><br>

<dl>
<dd>Metadata Service<br><br>

</dl>A Metadata Service provides a mechanism for storing and accessing
metadata, which is information that describes data items.&nbsp;
Typically, a Metadata Service (MS) provides the ability to query based on
metadata attributes rather than by names of data items.&nbsp; In
addition, the MS may provide management of logical collections data items
and of containers that consist of small data items that are stored, moved
and replicated together. The MS must maintain strict consistency over its
contents.&nbsp; Inaccuracies in the metadata database potentially result
in incorrect identification of data items, which would produce incorrect
analyses.&nbsp; The Metadata Service may be used by data browsing and
visualization applications to identify desired data.&nbsp; The MS is also
used by higher-level data grid components such as the Request Planner to
identify the logical data items needed to perform a desired
computation.&nbsp; <br><br>
There are various types of metadata, including logical and physical
metadata.&nbsp; Which types of metadata are included in a particular
Metadata Service depends on the application domain and on the existence
of other services, for example, whether there is a separate Replica
Location Service in the data grid.&nbsp; Physical metadata relates to the
actual location of the data item and the characteristics of a given
storage system.&nbsp; Examples of physical metadata include data item
size, access permissions for the data item on a storage system, and last
modification time of the data.&nbsp; Physical metadata is generally
maintained on storage systems (for example, as part of a file system) and
may also be replicated in a Metadata Service. <br><br>
Logical metadata describes the contents of a data item independent of the
location of a specific physical instance of the data item.&nbsp; One
example of logical metadata is information about how data items were
created or modified (e.g., the name and description of the logical data
item=92s creator or modifier, what experimental apparatus and input
conditions produced the data item, or what simulation or analysis
software was run on which computational engine with which input
parameters).&nbsp; Another example of logical metadata is a description
of what the data item represents (e.g., precipitation measurements over a
certain region during a certain time interval, or collisions in a
particle collider recorded during a specified interval).<br><br>
While some metadata attributes will be generally useful across a variety
of applications, each application domain is likely to adopt
domain-specific metadata conventions and schema.&nbsp; Thus, data grid
Metadata Services must be customizable and extensible.&nbsp; These
services may actually consist of a federation of metadata catalogs or
databases that, used in combination, provide data descriptions required
by application software and other data grid components.<br>
</font></html>

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From annc@ISI.EDU  Sat Aug 17 01:06:02 2002
From: annc@ISI.EDU (Ann Chervenak)
Date: Fri, 16 Aug 2002 17:06:02 -0700
Subject: [Arch-paper] draft.v1
Message-ID: <5.1.0.14.2.20020816165557.025c51d8@tnt.isi.edu>

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Hi,

I've put together all (I think) of the contributions I have received so 
far.  Let me know if anything you sent me is missing.

You will see this is a very rough draft at this point.  First priority is 
to cut down the sections that are way over the length limit.  (These are 
identified by **blue text**.)

Laura (who was asked recently to join as our security author) and Bill told 
me they would be a bit delayed with their sections.

I haven't received input from Carl or Peter on their assigned sections.

Thanks for the good work so far.  I can only promise much more work ahead!  :-)

Have a nice weekend.

Ann

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From Heinz.Stockinger@cern.ch  Mon Aug 19 07:57:24 2002
From: Heinz.Stockinger@cern.ch (Heinz Stockinger)
Date: Mon, 19 Aug 2002 08:57:24 +0200 (MET DST)
Subject: [Arch-paper] Re: more contributions
In-Reply-To: <5.1.0.14.2.20020813111331.02126790@tnt.isi.edu>
Message-ID: <Pine.GSO.3.95a.1020819085714.2100F-100000@suncms66.cern.ch>

Okay, I'll do so.
Heinz

On Tue, 13 Aug 2002, Ann Chervenak wrote:

> 
> Heinz,
> 
> Thanks for the contributions.  However, the descriptions you have submitted 
> are a bit long.  If you'll remember, we agreed that we would limit the 
> project descriptions (EDG, DataTag) to one or two sentences and the 
> component descriptions (GDMP) to half a page.  If you can cut these down, 
> that would be ideal.  Otherwise, I'll try to do so, but I imagine that you 
> would prefer the result of your own editing to mine.
> 
> Ann
> 
> At 11:21 AM 8/13/2002 +0200, Heinz Stockinger wrote:
> >Hi Ann,
> >
> >We started our "extended" assignments (;-) a wrote a part on GDMP as well
> >as short paragraphs on EDG and DataTAG.
> >
> >I'm looking forward to seeing a first draft and hope our fellow co-authors
> >are in time :-)
> >
> >cheers,
> >Heinz
> >
> >
> >~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
> >Heinz Stockinger, CERN, European Organization for Nuclear Research
> >  CMS Experiment/Computing Group
> >  Bat. 40-3A-24, CH-1211 Geneva 23
> >  phone: +41-22-767-1608, fax: +41-22-767-8940
> >http://www.cern.ch/hst/
> >European DataGrid Project (http://www.edg.org)
> >
> >The main aim of the European DataGrid (EDG) project is to produce
> >production quality Grid middleware ranging from workload and data
> >management to Grid monitoring and local fabric management. The project
> >has a diverse scientific user community: High Energy Physics,
> >Bioinformatics and Earth Observation. Software developed within the
> >project is deployed on a testbed that spans over 30 sites in Europe.
> >
> >DataTAG Project (http://cern.ch/datatag)
> >
> >DataTag, as a spin off from EDG, aims to create a large-scale
> >intercontinental testbed for data-intensive Grids by leveraging
> >technologies developed within EDG as well as U.S. Grid projects. The
> >focus is on two aspects: advanced networking techniques in gigabit
> >networks and interoperability issues between different Grids.
> >
> >
> >
> >
> >
> >
> >Grid Data Mirroring Package (GDMP)
> >==================================
> >
> >The GDMP client-server software system is a generic file replication tool that
> >replicates files securely and efficiently from one site to another
> >in a Data Grid environment using several Globus Grid tools. In addition,
> >it manages replica catalogue entries for file replicas and thus
> >maintains a consistent view on names and locations of replicated
> >files. Files to be transferred can be of any particular file format
> >and GDMP treats them all in the same way. However, for Objectivity
> >database files a particular plug-in exists. All files are assumed to
> >be read-only.
> >
> >The GDMP [1] project (originally called Grid Data Management Pilot)
> >was started in early 2000 as a pilot project to evaluate the Globus
> >toolkit (tm), take useful features for a file replication system and
> >produce a prototype to be evaluated in a real production environment.
> >
> >The driving force for the research and development on GDMP was
> >twofold: on the one hand, at CERN - the European Organization for
> >Nuclear research located near Geneva in Switzerland - first efforts
> >for the European DataGrid project EDG were under way and first
> >state-of-the-art studies in Grid computing needed to be done. On the
> >other hand, the CMS experiment, one of four next generation High
> >Energy Physics (HEP) experiments at CERN, required data transfer tools
> >for the distributed production of simulated data, in particular for
> >the High Level Trigger studies. Once the DataGrid project was kicked
> >off in January 2001, the experience gained from GDMP was used and the
> >current version of the software system is part of the DataGrid
> >software and in use in the first DataGrid testbed. Currently, the
> >software development process is well advanced and the project is now a
> >collaboration between the European DataGrid (in particular the Data
> >Management work package) and the Particle Physics Data Grid (PPDG).
> >
> >With respect to Data Grid architecture, GDMP is a replica manager with
> >additional high-level, application specific functionalities like
> >integration of Objectivity database files to an Objectivity
> >federation, a notification system for remote sites and an interface to
> >mass storage systems.  GDMP offers a set of client applications to
> >register new files to a local catalogue, publish a set of newly
> >created files to subscribed hosts, start the actual file replication
> >process, and subscribe to a remote GDMP server. In addition, the
> >software package contains a few other administration tools.
> >
> >GDMP is currenly in use in the EDG testbed as well as in PPDG and the
> >GriPhyN project. A follow on project called Reptor (see below) will
> >take over some of the functionality of GDMP and will replace it for
> >some use cases.
> >
> >
> >[1] Heinz Stockinger, Asad Samar, Shahzad Muzaffar, and Flavia
> >Donno. Grid Data Mirroring Package (GDMP). Scientific Programming
> >Journal - Special Issue devoted to Grid Computing, in print, 2002.
> 
> 


From Kurt.Stockinger@cern.ch  Mon Aug 19 08:15:37 2002
From: Kurt.Stockinger@cern.ch (Kurt Stockinger)
Date: Mon, 19 Aug 2002 09:15:37 +0200
Subject: [Arch-paper] RE: compute sections
In-Reply-To: <5.1.0.14.2.20020816104159.00aae198@tnt.isi.edu>
Message-ID: <CCEDJICNEOAHIPPIFKHNAENMCEAA.Kurt.Stockinger@cern.ch>

Hi Ann,

I would quite agree with Doug about where he placed the RB. However, I could
certainly write half a page on it, if it's still needed. Ann, please let me
know.

Kurt

---
Kurt Stockinger
Database Group, Information Technology Division
European Organization for Nuclear Research (CERN)
Building 31/3-025                                 Tel: ++ 41 22 767 4578
1211 Geneva 23                                    Fax: ++ 41 22 767 7155
Switzerland
http://nicewww.cern.ch/~kurts/index.htm


> -----Original Message-----
> From: Ann Chervenak [mailto:annc@ISI.EDU]
> Sent: Friday, August 16, 2002 7:43 PM
> To: Kurt Stockinger; Douglas Thain
> Cc: arch-paper@mailman.isi.edu; arch-paper@ISI.EDU
> Subject: RE: compute sections
>
>
>
> Kurt,
>
> Where are you suggesting that the resource broker be described?  in the
> current technologies section?  If you want this to be included,
> then please
> write up a description (maximum 1/2 page).
>
> Thanks.
>
> Ann
>
> At 03:30 PM 8/16/2002 +0200, Kurt Stockinger wrote:
> >Hi Doug,
> >
> > > > Kurt: Please also mention the Resource Broker of EDG-WP1 which
> > > sits on top
> > > > of Condor
> > > > and does additional match making with respect to data locality
> > > of required
> > > > input files.
> > > > The sytem is deployed on the EDG-testbed.
> > >
> > > Are you suggesting that this go under "other systems" or
> under "collective
> > > resource management" ?  I assume the latter.  I'm aware of
> this component,
> > > but I don't know of any publications that describe it.  Could
> you suggest
> > > some?
> >
> >Yes, collective resource management could be a good term. Please find an
> >early design document of WP1 at:
> >
> >http://server11.infn.it/workload-grid/deliverable.html
> >
> >Some things might have changed over the last few months but it might give
> >you a good idea to get started with.
> >
> >Kurt
>
>


From Kurt.Stockinger@cern.ch  Mon Aug 19 08:15:37 2002
From: Kurt.Stockinger@cern.ch (Kurt Stockinger)
Date: Mon, 19 Aug 2002 09:15:37 +0200
Subject: [Arch-paper] RE: compute sections
In-Reply-To: <5.1.0.14.2.20020816104159.00aae198@tnt.isi.edu>
Message-ID: <CCEDJICNEOAHIPPIFKHNAENMCEAA.Kurt.Stockinger@cern.ch>

Hi Ann,

I would quite agree with Doug about where he placed the RB. However, I could
certainly write half a page on it, if it's still needed. Ann, please let me
know.

Kurt

---
Kurt Stockinger
Database Group, Information Technology Division
European Organization for Nuclear Research (CERN)
Building 31/3-025                                 Tel: ++ 41 22 767 4578
1211 Geneva 23                                    Fax: ++ 41 22 767 7155
Switzerland
http://nicewww.cern.ch/~kurts/index.htm


> -----Original Message-----
> From: Ann Chervenak [mailto:annc@ISI.EDU]
> Sent: Friday, August 16, 2002 7:43 PM
> To: Kurt Stockinger; Douglas Thain
> Cc: arch-paper@mailman.isi.edu; arch-paper@ISI.EDU
> Subject: RE: compute sections
>
>
>
> Kurt,
>
> Where are you suggesting that the resource broker be described?  in the
> current technologies section?  If you want this to be included,
> then please
> write up a description (maximum 1/2 page).
>
> Thanks.
>
> Ann
>
> At 03:30 PM 8/16/2002 +0200, Kurt Stockinger wrote:
> >Hi Doug,
> >
> > > > Kurt: Please also mention the Resource Broker of EDG-WP1 which
> > > sits on top
> > > > of Condor
> > > > and does additional match making with respect to data locality
> > > of required
> > > > input files.
> > > > The sytem is deployed on the EDG-testbed.
> > >
> > > Are you suggesting that this go under "other systems" or
> under "collective
> > > resource management" ?  I assume the latter.  I'm aware of
> this component,
> > > but I don't know of any publications that describe it.  Could
> you suggest
> > > some?
> >
> >Yes, collective resource management could be a good term. Please find an
> >early design document of WP1 at:
> >
> >http://server11.infn.it/workload-grid/deliverable.html
> >
> >Some things might have changed over the last few months but it might give
> >you a good idea to get started with.
> >
> >Kurt
>
>


From Kurt.Stockinger@cern.ch  Mon Aug 19 08:17:19 2002
From: Kurt.Stockinger@cern.ch (Kurt Stockinger)
Date: Mon, 19 Aug 2002 09:17:19 +0200
Subject: [Arch-paper] RE: request interpreter
In-Reply-To: <41C31855E83ED31199D300C04F57A073F1B6B5@hermes.isi.edu>
Message-ID: <CCEDJICNEOAHIPPIFKHNEENMCEAA.Kurt.Stockinger@cern.ch>

Ewa,

> So what do you actually give the request interpreter---I was thinking
> application-specific attributes.  In my mind a job is not just a 
> set of LFNs
> but rather a DAG which describes how to produce the data.

> 
> How does the abstract planner work in your view? How does it generate the
> plan---what is its input, what information does it use?

I don't understand your questions here - I wrote all this up already. ;-)

Kurt

From Heinz.Stockinger@cern.ch  Mon Aug 19 14:15:23 2002
From: Heinz.Stockinger@cern.ch (Heinz Stockinger)
Date: Mon, 19 Aug 2002 15:15:23 +0200 (CEST)
Subject: [Arch-paper] token
In-Reply-To: <CCEDJICNEOAHIPPIFKHNAENMCEAA.Kurt.Stockinger@cern.ch>
Message-ID: <Pine.LNX.3.95a.1020819151412.598B-100000@lxplus021.cern.ch>

Hi All,

I now take the token for the paper and update the GDMP and consistency
sections (cut them down). I'll end out a version 1.1 of the paper later
today or tomorrow.

Heinz


From Erwin.Laure@cern.ch  Tue Aug 20 08:54:14 2002
From: Erwin.Laure@cern.ch (Erwin Laure)
Date: Tue, 20 Aug 2002 09:54:14 +0200
Subject: [Arch-paper] draft.v1
References: <5.1.0.14.2.20020816165557.025c51d8@tnt.isi.edu>
Message-ID: <3D61F5A6.C13E469D@cern.ch>

This is a multi-part message in MIME format.
--------------A2E54226790E59DF7CA459FF
Content-Type: text/plain; charset=us-ascii
Content-Transfer-Encoding: 7bit

Hi Ann, 

Heinz and I have cut down our contributions on 
Consistency (now 3 pages), GDMP, and Reptor
(now 1/2 page each). 
The current version of the paper is attached. 

We tried to stick more closely on the initial layout
but still have the feeling that things like master copies,
versioning service, verification service, ect. should
be discussed under the umbrella 'consistency management'. 
Also, we added the lifetime management service which was
not present in the original layout. 

What do you, and others, think?

Cheers, 

-- Erwin
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From allcock@mcs.anl.gov  Tue Aug 20 15:23:32 2002
From: allcock@mcs.anl.gov (William E. Allcock)
Date: Tue, 20 Aug 2002 09:23:32 -0500
Subject: [Arch-paper] My sections
Message-ID: <JCEDIJDPMKCHLOILFOFKGEALDHAA.allcock@mcs.anl.gov>

This is a multi-part message in MIME format.

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Sorry for being late.  I ran a little over my allotted page, but not much.
At that, I feel the description is woefully inadequate (I assume everyone
feels that way about their sections).

As I wrote it a few issues came up that we should probably discuss:

1) Is this paper the right place to discuss protocols and interoperability?

2) We are discussing an application/middleware transport protocol which
rides atop a network transport protocol (Due to space constraints that is
not clear in my section)

3) The transport protocol SHOULD be independent of data access semantics
(GridFTP violates this).  For instance, I ignore such things as partial file
access and such since the transport should just be moving buffers around.  I
did put in a pitch for length and offset since this is required "metadata"
to allow parallelism and out of order reception.

I will be on vacation next week, so I will make any changes that are sent
before Friday before I leave, or will work on it as best as possible the
following week while I am in Budapest at the EDG meeting.

Bill

--------------------------------------------
William (Bill) E. Allcock
Argonne National Laboratory
Bldg. 221, Office C-115A
9700 S. Cass Ave
Argonne, IL 60439-4844
E-Mail: allcock@mcs.anl.gov
Office: 630-252-7573
Mobile: 630-854-2842

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From Arie Shoshani <arie@lbl.gov>  Wed Aug 21 05:53:59 2002
From: Arie Shoshani <arie@lbl.gov> (Arie Shoshani)
Date: Tue, 20 Aug 2002 21:53:59 -0700 (PDT)
Subject: [Arch-paper] Re: Fwd: Items we talk about
Message-ID: <200208210453.g7L4rxq01517@postal1.lbl.gov>

Again, I appologize for the slow response due to my vacation.

Ian,

You are correct in that even for the opportunistic model you need to have
policies for deciding how to grant requests, and perhaps charging policies
as well.  The point is that in the opportunistic model the resource providers 
do not have to respond to resource allocation requests based on 
pre-assignment of capabilities to users, but rather they are based on local 
policies only.  That's what makes it a lot simpler to implement.  Also, 
reservation based policies may require negotiations, where the client asks 
for resources, but may be offered a lesser amount, etc.

I'll try to clarify this point in the writeup.

Thanks, Arie.


>With regard to this comment: I agree with Arie's comments on opportunistic 
>vs. reservation, with one nitpick, which is that I think the issues he 
>raises relating to "currency" etc. are independent of reservation vs. 
>opportunistic. Regardless of whether or not reservations are supported (in 
>network-speak, "regardless of whether you support only immediate 
>reservations or also advance reservations"), you need a policy for 
>deciding which requests are granted--a policy that may be based on 
>charging--and you may also want mechanisms for reporting on actual usage.
>
>Ian.
>
>
>At 11:45 AM 8/13/2002 -0700, Ann Chervenak wrote:
>>4.  The opportunistic model is a lot easier to support.  It basically
>>needs reasonable local policies, such as quota per user and lifetime of
>>temporary reservations.  The reservation-based model has to have
>>resource allocation coordination, a currency to charge the client (even
>>if resource is not in use), negotiation of resource usage, reporting of
>>actual usage, co-allocation algorithms, and bin-packing type algorithms.
>
>_______________________________________________________________
>Ian 
>Foster                                      http://www.mcs.anl.gov/~foster 


From foster@mcs.anl.gov  Wed Aug 21 07:17:24 2002
From: foster@mcs.anl.gov (Ian Foster)
Date: Wed, 21 Aug 2002 01:17:24 -0500
Subject: [Arch-paper] Re: Fwd: Items we talk about
In-Reply-To: <200208210453.g7L4rxq01517@postal1.lbl.gov>
Message-ID: <5.1.0.14.2.20020821011439.04fee818@localhost>

Arie:

I still think you are mixing different issues together that are quite separate:

* do you have advance reservations or not -- and certainly reservations 
introduce problems of various sorts

* do you invoke solely local policy when making decisions about immediate 
or advance reservations (=opportunistic or reservation requests in your 
terminology?), or allow for community policy as well -- again, there are 
obvious pros and cons of each approach

Ian.

At 09:53 PM 8/20/2002 -0700, Arie Shoshani wrote:
>You are correct in that even for the opportunistic model you need to have
>policies for deciding how to grant requests, and perhaps charging policies
>as well.  The point is that in the opportunistic model the resource providers
>do not have to respond to resource allocation requests based on
>pre-assignment of capabilities to users, but rather they are based on local
>policies only.  That's what makes it a lot simpler to implement.  Also,
>reservation based policies may require negotiations, where the client asks
>for resources, but may be offered a lesser amount, etc.

_______________________________________________________________
Ian 
Foster                                      http://www.mcs.anl.gov/~foster 

Math & Computer Science Div.            Dept of Computer Science
Argonne National Laboratory             The University of Chicago
Argonne, IL 60439, U.S.A.               Chicago, IL 60637, U.S.A.
630 252 4619 (fax 5986)                  773 702 3487 (fax 8487)


From Heinz.Stockinger@cern.ch  Wed Aug 21 10:48:37 2002
From: Heinz.Stockinger@cern.ch (Heinz Stockinger)
Date: Wed, 21 Aug 2002 11:48:37 +0200 (MET DST)
Subject: [Arch-paper] My sections
In-Reply-To: <JCEDIJDPMKCHLOILFOFKGEALDHAA.allcock@mcs.anl.gov>
Message-ID: <Pine.GSO.3.95a.1020821114313.3536B-100000@suncms66.cern.ch>

Hi Bill,

A few comments: 

- use "Data Grid" instead of "DataGrid"

- your general intro on key characteristics might go into the overall
design goals section.

- I think a little section on GridFTP might be added to point out a
reference implementation. We might also add bbcp and bbftp references for
completeness.

cheers,
Heinz

On Tue, 20 Aug 2002, William E. Allcock wrote:

> Sorry for being late.  I ran a little over my allotted page, but not much.
> At that, I feel the description is woefully inadequate (I assume everyone
> feels that way about their sections).
> 
> As I wrote it a few issues came up that we should probably discuss:
> 
> 1) Is this paper the right place to discuss protocols and interoperability?
> 
> 2) We are discussing an application/middleware transport protocol which
> rides atop a network transport protocol (Due to space constraints that is
> not clear in my section)
> 
> 3) The transport protocol SHOULD be independent of data access semantics
> (GridFTP violates this).  For instance, I ignore such things as partial file
> access and such since the transport should just be moving buffers around.  I
> did put in a pitch for length and offset since this is required "metadata"
> to allow parallelism and out of order reception.
> 
> I will be on vacation next week, so I will make any changes that are sent
> before Friday before I leave, or will work on it as best as possible the
> following week while I am in Budapest at the EDG meeting.
> 
> Bill
> 
> --------------------------------------------
> William (Bill) E. Allcock
> Argonne National Laboratory
> Bldg. 221, Office C-115A
> 9700 S. Cass Ave
> Argonne, IL 60439-4844
> E-Mail: allcock@mcs.anl.gov
> Office: 630-252-7573
> Mobile: 630-854-2842
> 


From allcock@mcs.anl.gov  Wed Aug 21 13:06:21 2002
From: allcock@mcs.anl.gov (William E. Allcock)
Date: Wed, 21 Aug 2002 07:06:21 -0500
Subject: [Arch-paper] My sections
In-Reply-To: <Pine.GSO.3.95a.1020821114313.3536B-100000@suncms66.cern.ch>
Message-ID: <JCEDIJDPMKCHLOILFOFKIEBPDHAA.allcock@mcs.anl.gov>


>-----Original Message-----
>From: Heinz Stockinger [mailto:Heinz.Stockinger@cern.ch]
>Sent: Wednesday, August 21, 2002 04:49
>To: William E. Allcock
>Cc: arch-paper@mailman.isi.edu
>Subject: Re: [Arch-paper] My sections
>
>
>Hi Bill,
>
>A few comments:
>
>- use "Data Grid" instead of "DataGrid"
Will do

>
>- your general intro on key characteristics might go into the overall
>design goals section.
That's fine, I can then just reference "the key characteristics noted above"

>
>- I think a little section on GridFTP might be added to point out a
>reference implementation. We might also add bbcp and bbftp references for
>completeness.
I believe there is a half pages section on implementations, where I will do
this.

Thanks,

Bill
>
>cheers,
>Heinz
>
>On Tue, 20 Aug 2002, William E. Allcock wrote:
>
>> Sorry for being late.  I ran a little over my allotted page, but
>not much.
>> At that, I feel the description is woefully inadequate (I assume everyone
>> feels that way about their sections).
>>
>> As I wrote it a few issues came up that we should probably discuss:
>>
>> 1) Is this paper the right place to discuss protocols and
>interoperability?
>>
>> 2) We are discussing an application/middleware transport protocol which
>> rides atop a network transport protocol (Due to space constraints that is
>> not clear in my section)
>>
>> 3) The transport protocol SHOULD be independent of data access semantics
>> (GridFTP violates this).  For instance, I ignore such things as
>partial file
>> access and such since the transport should just be moving
>buffers around.  I
>> did put in a pitch for length and offset since this is required
>"metadata"
>> to allow parallelism and out of order reception.
>>
>> I will be on vacation next week, so I will make any changes that are sent
>> before Friday before I leave, or will work on it as best as possible the
>> following week while I am in Budapest at the EDG meeting.
>>
>> Bill
>>
>> --------------------------------------------
>> William (Bill) E. Allcock
>> Argonne National Laboratory
>> Bldg. 221, Office C-115A
>> 9700 S. Cass Ave
>> Argonne, IL 60439-4844
>> E-Mail: allcock@mcs.anl.gov
>> Office: 630-252-7573
>> Mobile: 630-854-2842
>>
>


From Kurt.Stockinger@cern.ch  Thu Aug 22 14:34:02 2002
From: Kurt.Stockinger@cern.ch (Kurt Stockinger)
Date: Thu, 22 Aug 2002 15:34:02 +0200 (CEST)
Subject: [Arch-paper] Workload Management System (WMS)
In-Reply-To: <JCEDIJDPMKCHLOILFOFKGEALDHAA.allcock@mcs.anl.gov>
Message-ID: <Pine.LNX.3.95a.1020822152518.27619A-100000@lxplus048.cern.ch>

Hi,

Please find below my contribution of EDG-WP1's Workload Management System.
This is a superset of the Resource Broker that Doug already cited in
his contribution on "Collective Compute Scheduling".

This WMS could go in IX. Proposed Technologies

Kurt

EDG-Workload Management System (WMS)

The goal of EDG's Workload Management System (WMS) is to manage Grid
resources conveniently, efficiently and effectively \cite{EDG-WP1} based
on the following components: the User Interface , the Resource Broker, the
Job Submission Service, and the Logging and Bookkeeping Service. 

The user interacts with the WMS via a User Interface that allows, among
others, to submit jobs, control the execution of a job, and retrieve a
job's output. A job is represented by a certain Job Description that is
expressed via a Job Description Language (JDL). 

The task of the Resource Broker is to find the best match between the
requirements of the jobs and the available Grid resources. In order to
perform this optimization, the Resource Broker consults the Replica
Manager Service (GDMP or Reptor), about the location of required input
files and the Information Service about the current load of the computing
and storage resources. The result of the optimisation is a matching
computing resource where the executing job has access to all resources
specified in the Job Description, such as data or storage space. 

The actual job submission to the identified computing resource is
performed by the Job Submission Service. The execution of the job is
monitored in order to react in case of job failures.

Finally, the Logging and Bookkeeping Service collects further information
on the job such a resource consumption which can be used for accounting
purposes.
 


@misc{EDG-WP1,
	author = {WP1 - Workload Management},
	title = {{Definition of Architecture, Technical Plan and
Evaluation Criteria for Scheduling, Resource Management, Security and Job
Description}},
	howpublished = {EU DataGrid Project. Deliverable D1.2},
	month = {September},
	year = {2001},
	note = {}
}



---
Kurt Stockinger 
European Organization for Nuclear Research
IT Division, Database Group, 1211 Geneva, Switzerland
http://nicewww.cern.ch/~kurts/index.htm



From annc@ISI.EDU  Wed Aug 28 15:19:55 2002
From: annc@ISI.EDU (Ann Chervenak)
Date: Wed, 28 Aug 2002 07:19:55 -0700
Subject: [Arch-paper] revisions of sections on consistency
Message-ID: <5.1.0.14.2.20020828070629.021b0cd0@tnt.isi.edu>

--=====================_2562084==_.ALT
Content-Type: text/plain; charset="us-ascii"; format=flowed



Hi,

I've spent some time revising the section that Heinz and Erwin submitted on 
consistency management.  I think the right way to present this is as a 
collection of services that are related to consistency, are discussed 
abstractly as separate services, and may be implemented in combination.

While I've kept all the earlier sections, I'm not very happy with the 
section on Lifetime Management.  Exactly what this service does is not 
actually very clear.  Is it invoked by applications to extend a 
lifetime?  By a storage system to reduce a lifetime?  Is there a separate 
"subscription" service where users can register their interest in a 
replica, or is that function also provided by the Lifetime Management 
Service?  The original description of this service seemed to mix up the 
functionality of managing lifetime information with actually deleting 
replicas once their lifetime expires.  It is not clear that deleting items 
should be a function of this service, or whether that should be left for 
local or collective storage resource managers to do.

Comments on the new text are welcome.

Ann



T.  Services Related to Consistency Management (Heinz, Erwin, Ann)

Consistency requirements for Data Grids vary widely.  At one extreme, a 
data grid may make no guarantees about consistency of data items registered 
as replicas in a data grid.  At the other extreme, a data grid could 
provide strict consistency with synchronous, transactional semantics for 
updating replicas.

Data grids that require high levels of consistency among replicas must be 
able to detect inconsistencies among them.  Potential causes of 
inconsistencies among replicas include: changes to a replica due to 
authorized updates; replica corruption due to hardware defects, system 
failures or attacks; and deletion of replicas due to lifetime expiration or 
storage management.  In addition to detecting inconsistencies, data grids 
that guarantee high levels of consistency must define appropriate actions 
and rules for dealing with, and possibly repairing, inconsistencies among 
replicas. In this section, we describe several services that may be 
included in a data grid to provide different levels and types of 
consistency management, including master copy management, a file update 
service, a file versioning service, a data verification service and a 
lifetime management service.  While we describe these as logically separate 
services, in practice, they may be implemented in combination.

T.1. Master Copy Management

Many applications require the ability to designate that a particular 
replica of a data item is a master copy. The exact semantics of the 
designation of a master copy will differ by virtual organization. Useful 
semantics may include that the master copy is the only replica that may be 
modified, is the only replica from which new replicas may be created, 
and/or must not be deleted.

If there is a single master copy defined for a data item and the master 
copy becomes unavailable, then (depending on the master copy semantics 
supported by the data grid) it may not be possible to create new replicas 
or modify the file until the master copy again becomes available.  To avoid 
the master copy becoming a single point of failure, some systems may 
support the designation of multiple master copies for a data 
item.  However, such multiple masters must be kept tightly synchronized, 
typically using a distributed locking mechanism.

Master copy management may be implemented as a dedicated service or by 
using the replica location or metadata services to designate certain 
replicas as "master" copies.

T.2. Data Item Update Service

Data grids may provide read-only access to data items or may allow data 
items to be updated.  If updates are allowed, then the data grid must 
provide a mechanism for propagating data item updates to all existing 
replicas.

There are various mechanisms by which these updates may be propagated.  The 
option that provides the strictest consistency is the use of synchronous 
updates, where all replicas of a data item are locked and updated before 
changes to any replica are committed.  In highly dynamic grid environments, 
which are characterized by long wide area access latencies and frequent 
network and component failures, such synchronous updates are difficult to 
support, particularly as the number of replicas grows 
large.  Alternatively, updates may be propagated asynchronously, with all 
replicas eventually receiving the updates.   With asynchronous updates, 
there is a period of inconsistency among replicas while changes are 
propagating through the data grid.

Another approach to updating replicas relates to the master copies 
discussed in the last section.  In this scheme, updates can only be 
performed on data items that are specified as master copies.  Once updates 
are committed on the master copy or copies, those updates are propagated 
synchronously or asynchronously to the remaining replicas.  In contrast to 
systems that allow any replica to be updated at any time, the master copy 
update scheme allows changes only to master copies, which may become 
performance or reliability bottlenecks.

T.3  Data Item Versioning Service

Some data grids do not support arbitrary updates of existing data items but 
do support versions, which are new data items created by modifying existing 
data items. A Versioning Service preserves existing data items, allows 
creation of new versions, and maintains information about the relationships 
among versions.

Versioning Services may enforce a variety of policies for whether and how 
to distribute new versions of existing data items to storage systems that 
hold previous versions.  These policies are likely to depend on the needs 
of the application community.  In some cases, users or applications may 
want to access the latest version of the data item, deprecating all 
previous versions.  In other instances, applications may require consistent 
use of a particular version, regardless of whether later versions are 
created.  If new versions must be distributed to storage systems, then as 
discussed in the previous section, these updates may occur either 
synchronously to all locations or, more likely in grid environments, 
asynchronously, with some delay in storage systems receiving copies of the 
new versions.

The versioning service will likely interact with the Replica Location 
Service and the Metadata Service to record the existence of new versions 
and their attributes.

T.4  Data Quality Verification Service

There are many possible sources of data item corruption in a grid, 
including storage system bit errors, hardware and software failures and 
malicious attacks.  Data Verification Services are responsible for 
detecting and possibly correcting data item corruption.  These services can 
use a variety of techniques from simple checksums to complex error 
detection and correction algorithms. In addition to using error correction 
algorithms to recover the correct version of a data item, the Verification 
Service can replace a corrupted data item by creating a copy of an 
uncorrupted replica, if one is available.  Finally, if the Verification 
Service is unable to restore a corrupted data item, it may delete the data 
item and remove references to it from other grid services, such as the 
Replica Location Service and Metadata Service.

The Data Verification Service may be proactive or reactive. In the 
proactive case, the service might continuously or periodically check the 
contents of stored data items to verify their correctness.  A reactive 
Verification Service might be invoked upon access to a data item or in 
response to specific conditions or requests.

The Verification Service is likely to interact with the Replica Location 
Service and the Meta Data Service to store and retrieve information, such 
as data item checksums, necessary for error detection and correction and to 
identify a correct replica of a corrupted data item, such as a designated 
master copy.


T.5 Lifetime Management Service

While some data items may be stored indefinitely in a data grid, other data 
items may have limited lifetimes, after which the data items may be deleted 
from a storage system. A Lifetime Management Service is responsible for 
managing lifetime information associated with data items.  Once the 
lifetime of a stored data item has expired, the data item may be removed 
from a storage system either by the Lifetime Management Service or by Local 
or Collective Storage Resource Managers.

Lifetimes of data items may be set or modified based on several 
factors.  If Storage Resource Managers need to free space on a storage 
system, they may reduce the lifetimes associated with data 
items.  Conversely, end user quality of service requirements may extend a 
data item's lifetime to force a replica to exist at least for a given 
length of time. The data grid may also support a subscription model, where 
users or applications register an interest in the existence of a replica 
along with the lifetime of this interest. In this model, a replica may only 
be purged if no active subscription exists.  The Lifetime Management 
Service must resolve conflicting requests for limiting and extending data 
item lifetimes.

A Lifetime Management Service may be implemented as a proactive service 
that periodically checks the lifetime of replicas and indicates that 
replicas with expired lifetimes may be purged.  The Lifetime Management 
Service will likely interact with the Replica Location Service and the 
Metadata Service to store and retrieve lifetime information.

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Hi,<br><br>
I've spent some time revising the section that Heinz and Erwin submitted
on consistency management.&nbsp; I think the right way to present this is
as a collection of services that are related to consistency, are
discussed abstractly as separate services, and may be implemented in
combination.&nbsp; <br><br>
While I've kept all the earlier sections, I'm not very happy with the
section on Lifetime Management.&nbsp; Exactly what this service does is
not actually very clear.&nbsp; Is it invoked by applications to extend a
lifetime?&nbsp; By a storage system to reduce a lifetime?&nbsp; Is there
a separate &quot;subscription&quot; service where users can register
their interest in a replica, or is that function also provided by the
Lifetime Management Service?&nbsp; The original description of this
service seemed to mix up the functionality of managing lifetime
information with actually deleting replicas once their lifetime
expires.&nbsp; It is not clear that deleting items should be a function
of this service, or whether that should be left for local or collective
storage resource managers to do.&nbsp; <br><br>
Comments on the new text are welcome.<br><br>
Ann<br><br>
<br><br>
<font size=3D4><b>T.&nbsp; Services Related to Consistency Management
(Heinz, Erwin, Ann)<br><br>
</b></font>Consistency requirements for Data Grids vary widely.&nbsp; At
one extreme, a data grid may make no guarantees about consistency of data
items registered as replicas in a data grid.&nbsp; At the other extreme,
a data grid could provide strict consistency with synchronous,
transactional semantics for updating replicas.<br><br>
Data grids that require high levels of consistency among replicas must be
able to detect inconsistencies among them.&nbsp; Potential causes of
inconsistencies among replicas include: changes to a replica due to
authorized updates; replica corruption due to hardware defects, system
failures or attacks; and deletion of replicas due to lifetime expiration
or storage management.&nbsp; In addition to detecting inconsistencies,
data grids that guarantee high levels of consistency must define
appropriate actions and rules for dealing with, and possibly repairing,
inconsistencies among replicas. In this section, we describe several
services that may be included in a data grid to provide different levels
and types of consistency management, including master copy management, a
file update service, a file versioning service, a data verification
service and a lifetime management service.&nbsp; While we describe these
as logically separate services, in practice, they may be implemented in
combination.&nbsp; <br><br>
<font size=3D4><b>T.1. Master Copy Management<br><br>
</b></font>Many applications require the ability to designate that a
particular replica of a data item is a <i>master copy</i>. The exact
semantics of the designation of a master copy will differ by virtual
organization. Useful semantics may include that the master copy is the
only replica that may be modified, is the only replica from which new
replicas may be created, and/or must not be deleted.&nbsp; <br><br>
If there is a single master copy defined for a data item and the master
copy becomes unavailable, then (depending on the master copy semantics
supported by the data grid) it may not be possible to create new replicas
or modify the file until the master copy again becomes available.&nbsp;
To avoid the master copy becoming a single point of failure, some systems
may support the designation of multiple master copies for a data
item.&nbsp; However, such multiple masters must be kept tightly
synchronized, typically using a distributed locking mechanism. <br><br>
Master copy management may be implemented as a dedicated service or by
using the replica location or metadata services to designate certain
replicas as =93master=94 copies.&nbsp; <br><br>
<font size=3D4><b>T.2. Data Item Update Service<br><br>
</b></font>Data grids may provide read-only access to data items or may
allow data items to be updated.&nbsp; If updates are allowed, then the
data grid must provide a mechanism for propagating data item updates to
all existing replicas.&nbsp; <br><br>
There are various mechanisms by which these updates may be
propagated.&nbsp; The option that provides the strictest consistency is
the use of synchronous updates, where all replicas of a data item are
locked and updated before changes to any replica are committed.&nbsp; In
highly dynamic grid environments, which are characterized by long wide
area access latencies and frequent network and component failures, such
synchronous updates are difficult to support, particularly as the number
of replicas grows large.&nbsp; Alternatively, updates may be propagated
asynchronously, with all replicas eventually receiving the
updates.&nbsp;&nbsp; With asynchronous updates, there is a period of
inconsistency among replicas while changes are propagating through the
data grid.<br><br>
Another approach to updating replicas relates to the master copies
discussed in the last section.&nbsp; In this scheme, updates can only be
performed on data items that are specified as master copies.&nbsp; Once
updates are committed on the master copy or copies, those updates are
propagated synchronously or asynchronously to the remaining
replicas.&nbsp; In contrast to systems that allow any replica to be
updated at any time, the master copy update scheme allows changes only to
master copies, which may become performance or reliability
bottlenecks.&nbsp; <br><br>
<font size=3D4><b>T.3&nbsp; Data Item Versioning Service<br><br>
</b></font>Some data grids do not support arbitrary updates of existing
data items but do support versions, which are new data items created by
modifying existing data items. A Versioning Service preserves existing
data items, allows creation of new versions, and maintains information
about the relationships among versions.&nbsp; <br><br>
Versioning Services may enforce a variety of policies for whether and how
to distribute new versions of existing data items to storage systems that
hold previous versions.&nbsp; These policies are likely to depend on the
needs of the application community.&nbsp; In some cases, users or
applications may want to access the latest version of the data item,
deprecating all previous versions.&nbsp; In other instances, applications
may require consistent use of a particular version, regardless of whether
later versions are created.&nbsp; If new versions must be distributed to
storage systems, then as discussed in the previous section, these updates
may occur either synchronously to all locations or, more likely in grid
environments, asynchronously, with some delay in storage systems
receiving copies of the new versions.&nbsp; <br><br>
The versioning service will likely interact with the Replica Location
Service and the Metadata Service to record the existence of new versions
and their attributes.&nbsp; <br><br>
<font size=3D4><b>T.4&nbsp; Data Quality Verification Service<br><br>
</b></font>There are many possible sources of data item corruption in a
grid, including storage system bit errors, hardware and software failures
and malicious attacks.&nbsp; Data Verification Services are responsible
for detecting and possibly correcting data item corruption.&nbsp; These
services can use a variety of techniques from simple checksums to complex
error detection and correction algorithms. In addition to using error
correction algorithms to recover the correct version of a data item, the
Verification Service can replace a corrupted data item by creating a copy
of an uncorrupted replica, if one is available.&nbsp; Finally, if the
Verification Service is unable to restore a corrupted data item, it may
delete the data item and remove references to it from other grid
services, such as the Replica Location Service and Metadata
Service.&nbsp; <br><br>
The Data Verification Service may be proactive or reactive. In the
proactive case, the service might continuously or periodically check the
contents of stored data items to verify their correctness.&nbsp; A
reactive Verification Service might be invoked upon access to a data item
or in response to specific conditions or requests.&nbsp;&nbsp; <br><br>
The Verification Service is likely to interact with the Replica Location
Service and the Meta Data Service to store and retrieve information, such
as data item checksums, necessary for error detection and correction and
to identify a correct replica of a corrupted data item, such as a
designated master copy.&nbsp; <br><br>
<br>
<font size=3D4><b>T.5 Lifetime Management Service<br><br>
</b></font>While some data items may be stored indefinitely in a data
grid, other data items may have limited lifetimes, after which the data
items may be deleted from a storage system. A Lifetime Management Service
is responsible for managing lifetime information associated with data
items.&nbsp; Once the lifetime of a stored data item has expired, the
data item may be removed from a storage system either by the Lifetime
Management Service or by Local or Collective Storage Resource
Managers.&nbsp; <br><br>
Lifetimes of data items may be set or modified based on several
factors.&nbsp; If Storage Resource Managers need to free space on a
storage system, they may reduce the lifetimes associated with data
items.&nbsp; Conversely, end user quality of service requirements may
extend a data item=92s lifetime to force a replica to exist at least for a
given length of time. The data grid may also support a subscription
model, where users or applications register an interest in the existence
of a replica along with the lifetime of this interest. In this model, a
replica may only be purged if no active subscription exists.&nbsp; The
Lifetime Management Service must resolve conflicting requests for
limiting and extending data item lifetimes.&nbsp; <br><br>
A Lifetime Management Service may be implemented as a proactive service
that periodically checks the lifetime of replicas and indicates that
replicas with expired lifetimes may be purged.&nbsp; The Lifetime
Management Service will likely interact with the Replica Location Service
and the Metadata Service to store and retrieve lifetime information.
<br>
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