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Nov. 9, 2002
Chan-Hyun Youn
Information and Communications University
Grid Middleware Service
Int’l DataGrid Workshop
Contents• Grid and Middleware Services
• Architectural Model for Resource Management Hierarchical Resource Management Abstract Owner Market Model
• Scheduling Algorithms in Economy Grid
• Example of Application level Scheduler
• Concluding Remarks
Gri
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Grid Common Services: Standardized Services and Resources Interfaces
Toolkits: Visualization, data publish/subscribe, etc.Applications: Simulations, Data Analysis, etc.
Resources
Discipline Specific Portals andScientific Workflow Management Systems
Condor pools
networkcaches
tertiary storage national user facilities
clustersnational
supercomputer facility
high-speed networks and communications services
= Globus services
Architecture of a Grid
Source: IPG (Johnston)
Int’l DataGrid WorkshopHeterogeneous Computing:IPG Milestone Completed 10/2000
IPG managed compute and data management resources
resultsresultsresultsresultsresults
study concept
IPG Grid Common Services: Standardized services and uniform resource access
study object
1) Condor Workstation Pool mgr.
•Molecular design application for nanotechnology devices and materials
• Uses 0.5 million otherwise idle CPU hours/year scavenged from a 60-100 Sun and SGI workstations - a subset of the NAS Condor pool
•The Condor system is an IPG middleware service
2) Parameter Study Manager
- Two problem solving environments use IPG services for uniform access to heterogeneous resources.
• ILab aerospace design parameter study manager uses IPG to access distributed computing and data resources
Int’l DataGrid WorkshopOnline Instrumentation:Real-time Experiment Interaction
computersimulations
real-timecollection
multi-sourcedata analysis,
desktop & VR clients with shared controls
Unitary Plan Wind Tunnel
archival storage
real-time experiment control
Int’l DataGrid Workshop
Grid from Services View
:
:E.g.,
Applications
Resource-specific implementations of basic servicesE.g., Transport protocols, name servers, differentiated services, CPU schedulers, public keyinfrastructure, site accounting, directory service, OS bypass
Resource-independent and application-independent services authentication, authorization, resource location, resource allocation, events, accounting,
remote data access, information, policy, fault detection
DistributedComputing
Toolkit
Grid Fabric(Resources)
Grid Services(Middleware)
ApplicationToolkits
Data-Intensive
ApplicationsToolkit
CollaborativeApplications
Toolkit
RemoteVisualizationApplications
Toolkit
ProblemSolving
ApplicationsToolkit
RemoteInstrumentation
ApplicationsToolkit
Applications Chemistry
Biology
Cosmology
High Energy Physics
Environment
Int’l DataGrid Workshop
Middleware
• Layered collection of middleware services that provide to applications uniform views of distributed resource components and the mechanisms for assembling them into systems– Grid Workload Management, Data Management, Monitoring services
– Management of the Local Computing Fabric
– Mass Storage
• Services extend both “up and down” through the various layers of the computing and communications infrastructure
Int’l DataGrid Workshop
Functions in Middleware• Workload management
– The workload is chaotic – unpredictable job arrival rates, data access patterns
– The goal is maximising the global system throughput (events
processed per second)
• Data management
– Management of petabyte-scale data volumes, in an environment with
limited network bandwidth and heavy use of mass storage (tape)
– Caching, replication, synchronisation, object database model
• Application monitoring
– Tens of thousands of components, thousands of jobs and individual
users
– End-user - tracking of the progress of jobs and aggregates of jobs
– Understanding application and grid level performance
– Administrator – understanding which global-level applications were
affected by failures, and whether and how to recover
Int’l DataGrid Workshop
Middleware (in Local Fabric)
• Effective local site management of giant computing fabrics– Automated installation, configuration management, system maintenance– Automated monitoring and error recovery - resilience, self-healing– Performance monitoring– Characterisation, mapping, management of local Grid resources
• Mass storage management multi-PetaByte data storage “real-time” data recording requirement active tape layer – 1,000s of users uniform mass storage interface exchange of data and meta-data between mass storage systems
Int’l DataGrid Workshop Technical Approach in Layered Network
vBNS IDRENCampus
Internet 2GigaPop GigaPop
ESNet
Internet
LBNL
Ames
ANL
Global Middleware Services
Resource Scheduling
Network Cache
QoS Broker
Monitoring & Management
Access Control
CacheTertiary (mass)
storage
Super- Computer
Wind Tunnel
Tertiary storage
Cluster
NCAR
Applications
Applications
Applications
Applications need uniform views of resources, and middleware must deal with the fact that most “real” resources are “locally” owned
Local Services
Source: Grid’98 Workshop (Johnston)
Int’l DataGrid WorkshopOperation Model (1)
vBNS IDRENCampus
Internet 2GigaPop GigaPop
ESNet
Internet
LBNL
Ames
ANL
Network Cache
QoS Broker
Access Control
CacheTertiary (mass)
storage
Super- Computer
Wind Tunnel
Tertiary storage
Cluster
NCAR
Applications
Some services are provided in the middleware
Middleware must actually reach well !
Resource Characteristics
Resource Scheduling
Global Middleware Services
Monitoring & Management
Most services drill down to institutional resources
Data Catalogues
Some services drill down to the various network layers
Local Services
Source: Grid’98 Workshop (Johnston)
Int’l DataGrid Workshop Operation Model (2)
vBNS IDRENCampus
Internet 2GigaPop GigaPop
ESNet
Internet
LBNL
Ames
ANL
Network Cache
QoS Broker
Access Control
CacheTertiary (mass)
storage
Super- Computer
Wind Tunnel
Tertiary storage
Cluster
NCAR
Applications
Some services are provided in the middleware
Middleware layer and infrastructure to provide the transparent access for applications !
Resource Characteristics
Resource Scheduling
Global Middleware Services
Monitoring & Management Data
Catalogues
Local Services
Proxy management for multi-site resources
Configure
Analyzer
Monitor
Re-configure
Cache
Re-configure
Re-configure
Monitor
Source: Grid’98 Workshop (Johnston)
Int’l DataGrid Workshop
Middleware Approach
• Toolkit and services addressing key technical problems
– Modular “bag of services” model
– Not a vertically integrated solution
– can be applied to many application domains
• Inter-domain issues, rather than clustering
– Integration of intra-domain solutions
Int’l DataGrid Workshop
Globus Approach
• A software toolkit addressing key technical problems
– Offer a modular bag of technologies
– Enable incremental development of grid-enabled tools and applications
– Define and standardize grid protocols and APIs
• Focus is on inter-domain issues, not clustering
– Supports collaborative resource use spanning multiple organizations
– Integrates cleanly with intra-domain services
– Creates a collective service layer
Int’l DataGrid Workshop
Globus Approach
• Focus on architecture issues
– Provide implementations of grid protocols and APIs as basic infrastructure
– Use to construct high-level, domain-specific solutions
• Design principles
– Keep participation cost low
– Enable local control
– Support for adaptation
Diverse global services
Core Globusservices
Local OS
A p p l i c a t i o n s
Int’l DataGrid Workshop
Four Key Protocols
• The Globus Toolkit centers around four key protocols– Connectivity layer:
• Security: Grid Security Infrastructure (GSI)
– Resource layer:
• Resource Management: Grid Resource Allocation Management (GRAM)
• Information Services: Grid Resource Information Protocol (GRIP)
• Data Transfer: Grid File Transfer Protocol (GridFTP)
Int’l DataGrid Workshop
Site A(Kerberos)
Site B (Unix)
Site C(Kerberos)
Computer
User
Single sign-on via “grid-id”& generation of proxy cred.
Or: retrieval of proxy cred.from online repository
User ProxyProxy
credential
Computer
Storagesystem
Communication*
GSI-enabledFTP server
AuthorizeMap to local idAccess file
Remote fileaccess request*
GSI-enabledGRAM server
GSI-enabledGRAM server
Remote processcreation requests*
* With mutual authentication
Process
Kerberosticket
Restrictedproxy
Process
Restrictedproxy
Local id Local id
AuthorizeMap to local idCreate processGenerate credentials
Grid Security Infrastructure in Action
Int’l DataGrid Workshop
Resource Management
• The Grid Resource Allocation Management (GRAM) protocol and client API allows programs to be started on remote resources, despite local heterogeneity
• Resource Specification Language (RSL) is used to communicate requirements
• A layered architecture allows application-specific resource brokers and co-allocators to be defined in terms of GRAM services
– Integrated with Condor, MPICH-G2, …
Int’l DataGrid Workshop
Resource Management Issues for Grid Computing• Site autonomy
– Resources owned by different organizations, in different administrative domains
– Local policies for use, scheduling, security• Heterogeneous substrate
– Different local resource management systems• Policy extensibility
– Local sites need ability to customize their resource management policies
• Co-allocation– May need resources at several sites– Mechanism for allocating multiple resources, initiating
computation, monitoring and managing• On-line control
– Adapt application requirements to resource availability
Int’l DataGrid Workshop
GRAM GRAM GRAM
LSF EASY-LL NQE
Application
RSL
Simple ground RSL
Information Service
Localresourcemanagers
RSLspecialization
Broker
Ground RSL
Co-allocator
Queries& Info
Resource Management Architecture
Int’l DataGrid Workshop
Local Resource Managers
• Implemented with Globus Resource Allocation Manager (GRAM)– Processing RSL specifications representing resource requests
• Deny request
• Create one or more processes (jobs) that satisfy request
– Enable remote monitoring and management of jobs
– Periodically update MDS information service with current availability and capabilities of resources
• GRAM is responsible for– Parsing and processing RSL
– Job monitoring
– MDS update
Int’l DataGrid Workshop
Grid Information Services
• System information is critical to operation of the grid and construction of applications
– What resources are available?
• Resource discovery
– What is the “state” of the grid?
• Resource selection
– How to optimize resource use
• Application configuration and adaptation?
• We need a general information infrastructure to answer these questions
Int’l DataGrid Workshop
GIS Architecture
A A
Customized Aggregate Directories
R RR R
Standard Resource Description Services
Registration
Protocol
Users
Enquiry
Protocol
Int’l DataGrid Workshop
A Model Architecture for Data Grids
Metadata Catalog
Replica Catalog
Tape Library
Disk Cache
Attribute Specification
Logical Collection and Logical File Name
Disk Array Disk Cache
Application
Replica Selection
Multiple Locations
NWS
SelectedReplica
GridFTP Control ChannelPerformanceInformation &Predictions
Replica Location 1 Replica Location 2 Replica Location 3
MDS
GridFTPDataChannel
Int’l DataGrid Workshop
GridFTP: Basic Approach
• FTP protocol is defined by several IETF RFCs
• Start with most commonly used subset
– Standard FTP: get/put etc., 3rd-party transfer
• Implement standard but often unused features
– GSS binding, extended directory listing, simple restart
• Extend in various ways, while preserving interoperability with existing servers
– Striped/parallel data channels, partial file, automatic & manual TCP buffer setting, progress monitoring, extended restart
Int’l DataGrid Workshop
Striped GridFTP Server
Parallel File System (e.g. PVFS, PFS, etc.)
MPI-IO
…
Plug-in
Control
GridFTP Server Parallel BackendGridFTPservermaster
mpirun
GridFTPclient
Plug-in
Control
Plug-in
Control
Plug-in
Control…MPI (Comm_World)
MPI (Sub-Comm)
To Client or Another Striped GridFTP Server
Controlsocket
GridFTP Control Channel GridFTP Data Channels
Int’l DataGrid Workshop
What is Condor?• Condor converts collections of distributively
owned workstations and dedicated clusters into a distributed high-throughput computing facility.
Resource finder Batch queue manager Scheduler Checkpoint/Restart Process migration Remote system calls
All jobs
Jobs linked
with the Condor
library
Int’l DataGrid Workshop
Layered Design
ResourceResource
Access ControlAccess Control
Match-MakingMatch-Making
Request AgentRequest Agent
Application RMApplication RM
ApplicationApplication
Con
dor
Resource OwnerResource Owner
SystemSystem AdministratorAdministrator
Customer/UserCustomer/User
Int’l DataGrid Workshop
Unique Mechanisms
• Checkpointing– Enables Preemptive Resume Resource Allocation (essential
in an opportunistic environment)
• Remote I/O – Enables computation across administrative domains
(essential for HTC)
• ClassAds– Enables flexible resource matchmaking (essential in a
distributively owned environment)
Int’l DataGrid Workshop
Condor System Structure
Submit Machine Execution Machine
Collector
CA[...A]
[...B]
[...C]
CN
RA
Negotiator
Customer Agent Resource Agent
Central Manager
Int’l DataGrid Workshop
Job Submission Machine
Job Execution Site
Job
Condor-G GridManager
GASS Server
Condor-G Scheduler
Persistant Job Queue
End User Requests
Condor Shadow
Process for Job X
Condor-G Collector
Globus Daemons +
Local Site Scheduler
[See Figure 1]
Condor Daemons
Job X
Condor System Call
Trapping & Checkpoint Library
Resource
Information
Transfer Job X
Redirected System Call
Data
Int’l DataGrid Workshop
TENT• A distributed workflow management and
integration system for engineering applications developed by
– German Aerospace Center (DLR), Simulation and Software Technology (SISTEC) http://www.sistec.dlr.de
– German National Research Center for Information Technology (GMD), Institute for Algorithms and Scientific Computing (SCAI) http://www.gmd.de/scai
Int’l DataGrid Workshop
Typical Grid Computing Environment
Grid Resource Broker
Resource Broker
Application
Grid Information Service
Grid Resource Broker
databaseR2R3
RN
R1
R4
R5
R6
Grid Information Service
Int’l DataGrid Workshop
Sources of Complexity in Grid Resource Management• No single administrative control.• No single ownership policy:
– Each resource owner has their own policies or scheduling
mechanisms
– Users must honour them (particularly external Grid users)
• Heterogeneity – resources : PCs, Workstations, clusters, supercomputers, instruments,
databases, software …
– fabric management systems and
management policies
– application requirements
• Dynamic availability – may appear and disappear…
Int’l DataGrid Workshop
Sources of Complexity in Grid Resource Management
• Unreliable resource – disappear from view
• No uniform cost model - varies from one user’s resource to another and from time of day.
• No single access mechanism – Web, custom
interfaces, command line…
Int’l DataGrid Workshop
Grid Resource Management Issues
•Authentication (once).
•Specify (code, resources, etc.).
•Discover resources.
•Negotiate authorization, acceptable
use, Cost, etc.
•Acquire resources.
•Schedule Jobs.
•Initiate computation.
•Steer computation.
•Access remote data-sets.
•Collaborate with results.
•Account for usage.
•Discover resources.
•Negotiate authorization,
acceptable use, Cost, etc.
•Acquire resources.
•Schedule jobs.
•Initiate computation.
•Steer computation.
Domain 2
Domain 1
Rajkumar Buyya (Monash Univ.)
Int’l DataGrid Workshop
Data Access for Resource Management
Grid StatusRegistryManager
Grid SpaceManager
Data Disseminator
RequestRouter/
Allocator (1)
RequestRouter/
Allocator (2)
GridspaceGrid Status
Registry
GridespaceCache
Status update message in
Gridspace update message in
Resource request message in
Update message out
Route or Allocation message out
Route or allocation with single choice
Int’l DataGrid Workshop
Architectural Models for RM
MODEL REMARKS Systems
Hierarchical It captures model followed in most contemporary systems.
Globus, Legion, CCS, Apples, NetSolve, Ninf.
Abstract Owner (AO) Order and delivery model and focuses on long term goals.
Expected to emerge and most peer-2-peer computing systems likely to be based on this.
Market Model It follows economic model for resource discover, sharing, & scheduling.
GRACE, Nimrod/G, JavaMarket, Mariposa.
Int’l DataGrid WorkshopHierarchical RM
Connection control
Connection control
Global Scheduler
Global Scheduler
Access/AdmissionControl Agent
Global Scheduler
Global Scheduler
Global Scheduler
monitor
DeploymentAgent
Domain Resource manager
or control agent
Control domaintask
Local Scheduler
resource
Grid information
service
PersistentJ ob controlagent
user
Int’l DataGrid Workshop
Resource Management in Globus
• The Grid Resource Allocation Management (GRAM) protocol and client API allows programs to be started on remote resources, despite local heterogeneity
• Resource Specification Language (RSL) is used to communicate requirements
• A layered architecture allows application-specific resource brokers and co-allocators to be defined in terms of GRAM services
– Integrated with Condor, MPICH-G2, …
Int’l DataGrid Workshop
GRAM GRAM GRAM
LSF EASY-LL NQE
Application
RSL
Simple ground RSL
Information Service
Localresourcemanagers
RSLspecialization
Broker
Ground RSL
Co-allocator
Queries& Info
Resource Management Architecture in Globus
Int’l DataGrid Workshop
Local Resource Managers
• Implemented with Globus Resource Allocation Manager (GRAM)– Processing RSL specifications representing resource requests
• Deny request
• Create one or more processes (jobs) that satisfy request
– Enable remote monitoring and management of jobs
– Periodically update MDS information service with current availability and capabilities of resources
• GRAM is responsible for– Parsing and processing RSL
– Job monitoring
– MDS update
Int’l DataGrid Workshop
Globus/MPICH-G2 components
Globus SecurityInfrastructure
Globus-job-manager
Client API calls to request resource allocation
and process creation.
MDS client API callsto locate resources
Query current statusof resource
Launch
RSL Library
Parse
Request Allocate &create processes
Process
ProcessMonitor &
control
Local siteboundary
MPI Apps MDS: Grid Index Info Server
Globus Gatekeeper
MDS: Grid Resource Info Server
Globus Resource Manager
MDS client API callsto get resource info
Provide state changecallbacks to client
Process MPImessages
MPICH-G2
Int’l DataGrid Workshop
High throughput workload management system architecture (simplified design)
GRAM
CONDOR
GRAM
LSF
GRAM
PBS
globusrun
Site1Site2 Site3
condor_submit(Globus Universe)
Condor-G
Master GISSubmit jobs(using Class-Ads)
ResourceDiscovery
Information on characteristics andstatus of local resources
Condor Globus Universe
Int’l DataGrid Workshop
AO General Model
Abstract Owner
Resource Manager
Physical Resource
Order window
PickupWindow
(a) External view of AO model
Order window
PickupWindow
(b) AO is Resource Owner
Manager
Sales Rep. Delivery Rep.
AO1
AO2
AO3
Order window
PickupWindow
(c ) AO is broker
Job shop(Estimator & Execution)
AO for Grid
J ob Result
(d) Job scheduling step AO
Estimator Executorlist
(e) Job Shop
Int’l DataGrid Workshop
Order Pickup
AO is owner or broker• User negotiates with AO through “order window”• That AO may own some resources, and/or it may broker with other AOs for those resources• After negotiation, resources are delivered through “pickup window”
OrderWindow
PickupWindow
PhysicalResource
UserRequests Resources
AO
Order Pickup
ResourceManager
AO1
Manager
DeliverySales
AO2
AO3
Int’l DataGrid Workshop
AO Resources• Resources are objects
• Classes are
– Instrument
• Data source, sink, transform
• e.g. programs, people, files,
data collection devices
– Channel
• Moves data among instruments
– Complexes of above
• Attributes define sizes, times,
connections, etc.
Instrument(File)
Instrument(Program)
Instrument(File)
Instrument(Program)
Channels
Instrument(Telescope)
Instrument(Person)
Int’l DataGrid Workshop
Negotiating with an AOMake dummy resource
(with attributes set to constants, variables, or
“don’t care”)
+ bid + delivery plan+ variable constraints
Resource candidates(values for variables/attributes
+ asking price for each)
Pick one,Try again,Or give up
DeliveryWindow
Resource
Order Window
Assign tasksto resource,use, relinquish
Perhapslater...
USER
AO
Int’l DataGrid Workshop
Economic Models for Trading
• Commodity Market Model• Posted Prices Models• Bargaining Model• Tendering (Contract Net) Model• Auction Model • Proportional Resource Sharing Model• Shareholder Model• Partnership Model
Int’l DataGrid Workshop
Economy Grid = Globus + GRACEApplications
MDS
GRAMGlobus Security Interface
Heartbeat MonitorNexus
Local Services
LSF
Condor GRD QBank
PBS
TCP
SolarisIrixLinux
UDP
High-level Services and Tools
DUROC globusrunMPI-G Nimrod/GMPI-IO CC++
GlobusView Grid Status
GASS
GRACE-TS
GARA
GridFabric
GridApps.
GridMiddleware
GridTools
GBankGMD
eCash
JVM
DUROC
Core Services
Science
Engineering Commerce Portals ActiveSheet……
Source: Rajkumar Buyya (Monash Univ.)
Int’l DataGrid Workshop
Grid Node N
Grid Architecture for Computational Economy
Grid User
Application
Grid Resource Broker
Grid Service Providers
Grid Explorer
Schedule Advisor
Trade Manager
Job ControlAgent
Deployment Agent
Trade Server
Resource Allocation
ResourceReservation
R1
Misc. services
Information Server(s)
R2 Rm…
Pricing Algorithms
Accounting
Grid Node1
…
Grid Middleware Services
…
…
HealthMonitor
Grid Market Services
JobExec
Info ?
Secure
Trading
QoS
Storage
Sign-on
Source: Rajkumar Buyya (Monash Univ.)
Int’l DataGrid Workshop
GRACE components
• A resource broker (e.g., Nimrod/G)• Various resource trading protocols for different economic
models• A mediator for negotiating between users and grid service
providers (Grid Market Directory)• A deal template for specifying resource requirements and
services offers• Grid Trading Server• Pricing policy specification• Accounting (e.g., QBank) and payment management
(GridBank, not yet implemented)
Int’l DataGrid WorkshopFlow Diagram for Pricing, Accounting, Allocations and Job Scheduling
QBankQBank
Resource Manager44
IBM-LL/PBS/….
00
55 88
66 77
Compute Resourcesclusters/SGI/SP/...
0. Make Deposits, Transfers, Refunds, Queries/Reports1. Clients negotiates for access cost.2. Negotiation is performed per owner defined policies. 3. If client is happy, TS informs QB about access deal.4. Job is Submitted5. Check with QB for “go ahead”6. Job Starts7. Job Completes8. Inform QB about resource resource utilization.
Trade Server 3311
Pricing PolicyPricing Policy22
DB@Each SiteDB@Each Site
GRID BankGRID Bank(digital transactions)(digital transactions)00
Rajkumar Buyya (Monash Univ.)
Int’l DataGrid Workshop
• A resource broker for managing, steering, and executing task farming (parametric sweep/SPMD model) applications on Grid based on deadline and computational economy.
• Based on users’ QoS requirements, our Broker dynamically leases services at runtime depending on their quality, cost, and availability.
• Key Features– A single window to manage & control experiment– Persistent and Programmable Task Farming Engine– Resource Discovery– Resource Trading – Scheduling & Predications– Generic Dispatcher & Grid Agents– Transportation of data & results– Steering & data management– Accounting
Nimrod/G : A Grid Resource Broker
Source: Rajkumar Buyya (Monash Univ.)
Int’l DataGrid WorkshopA Glance at Nimrod-G Broker
Grid Middleware
Nimrod/G Client Nimrod/G ClientNimrod/G Client
Grid Information Server(s)
Schedule Advisor
Trading Manager
Nimrod/G Engine
GridStore
Grid Explorer
GE GISTM TS
RM & TS
Grid Dispatcher
RM: Local Resource Manager, TS: Trade Server
Globus, Legion, Condor, etc.
G
G
CL
Globus enabled node.Legion enabled node.
GL
Condor enabled node.
RM & TSRM & TS
C L
Source: Rajkumar Buyya (Monash Univ.)
Int’l DataGrid Workshop
Nimrod/G Interactions
Grid InfoServer
ProcessServer
UserProcess
File accessFileServer
Grid Node
NimrodAgent
Compute NodeUser Node
GridDispatcher
Grid Trade Server
GridScheduler
Local Resource Manager
Nimrod-G Grid Broker
TaskFarmingEngine
Grid ToolsAnd
Applications
Do this in 30 min. for $10?
Source: Rajkumar Buyya (Monash Univ.)
Int’l DataGrid Workshop
Discover Discover ResourcesResources
Distribute JobsDistribute Jobs
Establish Establish RatesRates
Meet requirements ? Remaining Meet requirements ? Remaining Jobs, Deadline, & Budget ?Jobs, Deadline, & Budget ?
Evaluate & Evaluate & RescheduleReschedule
Discover Discover More More
ResourcesResources
Adaptive Scheduling Steps
Compose & Compose & ScheduleSchedule
Source: Rajkumar Buyya (Monash Univ.)
Int’l DataGrid Workshop
Concluding Remarks• Restriction in Grid Middleware
– Difficulties in distributed computing and resource management policy
– Difficulties of middleware implementation required for heterogeneous systems in meta-computing infrastructure
• Globus, Condor, TENT, PARIS, Cactus, ….
• Difficulties of Resource Management in Grid Computing
• Models for Grid resource management architecture
– Hierarchical, AO, and Market-model ….
