StorCast Enterprise Storage Resource Management. What is Enterprise Storage Resource Management?
Storage Resource Broker
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Transcript of Storage Resource Broker
Storage Resource Broker Persistent Management of Distributed Data
Reagan W. MooreGeneral Atomics, Inc.
San Diego Supercomputer [email protected]
http://www.nirvanastorage.com
Topics
• Data management systems– Data collections, digital libraries
• Distributed data management– Data grids
• Persistent data management– Persistent archives
• Common infrastructure for data management
Data Collections• Astronomy
– CACR Computing Resource (NPACI)– National Virtual Observatory (NSF)– 2 Micron All Sky Survey (NPACI)– DPOSS Collection (NSF-NVO)– Hayden Planetarium
• Ecology and Environmental Sciences– CEED (NPACI)– Bionome– HyperLTER (NPACI)– Land Data Assimilation System– Knowledge Networks for BioComplexity (NSF)
• Medical Sciences– Digital Embryo (NLM)
• Molecular Sciences– JCSG, Synchrotron Data Repository (NSF)– AFCS, Alliance for Cell Signaling (NIH)
• NeuroSciences– Biomedical Information Research Network (NIH)– TeleScience Portal (NPACI)– Brain Databases (NPACI)– Brain Data Archiving (NPACI)
• Computer Science– DataStreaming (NPACI)– AppLeS, DataCutter (NPACI)
•Physics and Chemistry–PPDG, Particle Physics Data Grid (DOE)–GriPhyN (NSF)–BaBar (DOE)–GAMESS (NPACI)
•Digital Libraries and Archives–SIO Digital Libraries (NSF)–California Digital Library–ADEPT (NSF)–Stanford Digital Library Project (NSF)–National Archives and Records Administration (NARA)
•Data Grids–ROADNet, Real-time Observatories App.and Data management–E-Science at CLRC, UK Grid Starter Kit (UK)–Library of Congress data grid–DOE ASCI Data Visualization Corridor–NASA Information Power Grid–DOE SciDAC - Portal Web Services–NPACI Portal Projects
•Education–Transana (NPACI)–Digital Insight (NPACI)–NSDL National STEM Education Digital Library (NSF)
Data Collections
Data Collections
• Define the context for describing a collection of digital entities– Context specified by metadata attributes– Provenance, origin of the digital entities– Administrative, location of the digital entities– Technical, purpose of the digital entities
• Support organization of attributes as hierarchy of sub-collections
Digital Libraries
• Provide services on the data collection– Ingestion, loading of attribute values– Extensibility, definition of new attributes– Discovery, queries on attributes– Browsing, hierarchical listing– Presentation, formatting specified data models
Data Grids
• Manage data in a distributed environment– Logical name space, provide global identifier– Data access, storage system abstraction– Replication, disaster back up– Uniform access, common API across file
systems, archives, and databases– Single sign-on, authenticate across
administration domains
Persistent Archives
• Manage technology evolution– Storage system abstraction, support data
migration across storage systems– Information repository abstraction, support
catalog migration to new databases– Logical name space, support global persistent
identifier
SRB
• Integration of collection-based management of digital entities, with– Remote data access through storage system
abstraction– Catalog access through information repository
abstraction– Automation through collection-owned data
Storage Resource Broker
Capabilities
• Support legacy systems• Integrate archives with file systems• Share distributed data• Maintain persistent collection• Control data access
Digital Entities
• Digital entities are “images of reality” made of– Data, the bits (zeros and ones) put on a
storage system– Information, the attributes used to assign
semantic meaning to the data– Knowledge, the structural relationships
described by a data model• Every digital entity requires information
and knowledge to correctly interpret and display
Digital Entities
• Files– Text documents, images, spread sheets, binary files
• URLs• Database query commands• Databases• Directories
Digital Entities
• Register digital entities into a catalog• Assign metadata to describe each digital
entity• Separate management of the associated
data bits from management of the metadata
• Support manipulation of each digital entity data type
Old Storage System
New Operating System
New Application
Digital Object
Old Display SystemWrap Storage System Wrap Display System
Migrate Encoding Format
Technology Management
Preservation of Data
• Migration – Preserve the data bits– Preserve the digital entity name– Preserve the information and knowledge
content for presentation by new applications
Migration Advantages
• By migrating the digital entity encoding format to new standards, more sophisticated technologies can be applied to express the information and knowledge content inherent in collections of digital entities.
• Requires the ability to associate data model with digital entity
Uniform API
• Provide common access semantics• Map from the interface preferred by your
application to the interfaces required by legacy storage systems
ArchivesHPSS, ADSM,UniTree, DMF
File SystemsUnix, NT,Mac OSX
AccessAPIs
Servers
PrimeServer
Unix Shell
Java, NTBrowsers
WebWSDL
GridFTP
DatabasesDB2, Oracle,
Postgres
Application
Storage AbstractionCatalog AbstractionDatabases
DB2, Oracle, Sybase
C, C++, Libraries
Logical Name Space
LatencyManagement
DataTransport
MetadataTransport
Consistency Management / Authorization-Authentication
Linux I/O
DLL /Python
SRB and MCATUniform APIs
HRM
Discovery Transparencies
• Naming transparency - find a data set without knowing its name– Map from attributes to a global file name
• Location transparency - access a data set without knowing where it is– Map from global file name to local file name
• Access transparency - access a data set without knowing the type of storage system– Federated client-server architecture
Servers
Unix Shell
Java, NTBrowsers
WebWSDL
GridFTP
ArchivesHPSS, ADSM,UniTree, DMF
DatabasesDB2, Oracle,
Postgres
File SystemsUnix, NT,Mac OSX
Application
HRM
AccessAPIs
Storage AbstractionCatalog Abstraction
DatabasesDB2, Oracle, Sybase
C, C++, Libraries
Logical Name Space
LatencyManagement
DataTransport
MetadataTransport
Consistency Management / Authorization-AuthenticationPrimeServer
Linux I/O
DLL /Python
SRB and MCATTransparencies
Persistent Collection
• Maintain authenticity– Authenticate all accesses– Assign roles for access control lists (curation,
write, annotate, read)– Manage audit trails of all operations
• Collection-owned data– All accesses through the data management
system
AccessAPIs
Servers
PrimeServer
Unix Shell
Java, NTBrowsers
WebWSDL
GridFTP
ArchivesHPSS, ADSM,UniTree, DMF
DatabasesDB2, Oracle,
Postgres
File SystemsUnix, NT,Mac OSX
Application
HRM
Storage AbstractionCatalog Abstraction
DatabasesDB2, Oracle, Sybase
C, C++, Libraries
Logical Name Space
LatencyManagement
DataTransport
MetadataTransport
Consistency Management / Authorization-Authentication
Linux I/O
DLL /Python
SRB and MCATPersistency
• Name transparency– Find a file by attributes (map from attributes to global
name) • Location transparency
– Access a file by a global identifier (map from global to local file name)
• Access transparency– Use same API to access data in archive or file cache
• Authenticity– Disaster recovery, replicate data across storage systems– Audit and process management
Preservation
(Similar requirements to a data grid)
AccessAPIs
Servers
PrimeServer
Unix Shell
Java, NTBrowsers
WebWSDL
GridFTP
ArchivesHPSS, ADSM,UniTree, DMF
DatabasesDB2, Oracle,
Postgres
File SystemsUnix, NT,Mac OSX
Application
HRM
Storage AbstractionCatalog Abstraction
DatabasesDB2, Oracle, Sybase
C, C++, Libraries
Logical Name Space
LatencyManagement
DataTransport
MetadataTransport
Consistency Management / Authorization-Authentication
Linux I/O
DLL /Python
SRB & MCATPreservation
Technology Convergence
• Data grids as basis for distributed data management– Federation of distributed resources– Creation of logical name space to automate discovery
• Distributed data collections– Discovery based on attributes– Distributed data storage systems
• Digital libraries– Development of services for manipulating, viewing data
• Persistent archives– Management of technology evolution
Data Naming Ontologies
Attributes that describe data structure
Data model
Local file nameArchive / file systems
Discipline attributesCollection
Global IdentifierData grid
Discipline conceptsConcept space
Knowledge Creation
• Knowledge syntax (consensus)
– RDF, XMI, Topic Map• Knowledge management (recursive operations)
– Oracle parallel database• Knowledge manipulation (spatial/procedural rules)
– Generation of inference rules and mapping to data models• Knowledge generation (scalable inference engine)
– Application of inference rules in inference engine
AttributesSemantics
Knowledge
Information
Data
Ingest Services
Management AccessServices
(Model-based Access)
(Data Handling System - SRB)M
CA
T/H
DF
Grid
s
XM
L D
TD
SD
LIP
XTM
DTD
Rul
es -
KQ
L
InformationRepository
Attribute- based Query
Feature-basedQuery
Knowledge orTopic-Based Query / Browse
KnowledgeRepository for Rules
RelationshipsBetweenConcepts
FieldsContainersFolders
Storage(Replicas,Persistent IDs)
Knowledge-based Data Grid
Reagan W. MooreGeneral Atomics
San Diego Supercomputer Center
[email protected]://www.nirvanastorage.com