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WW Grid
Economic Models for Management of Resources in Peer-to-Peer (P2P) and Grid
Computing
R. Buyya, H.Stockinger, J.Giddy, D.Abramson
Melbourne, Australia Switzerland
buyya.com/ecogrid
ITCOM 2001, Denver, Aug 19-24, 2001
2
3
Agenda
A quick glance at today’s Grid computing Resource Management challenges for next
generation Grid computing A Glance at Approaches to Grid computing Grid Architecture for Computational Economy Economic Models for Resource Management Nimrod/G -- Grid Resource Broker Deadline and Budget Constrained (DBC)
Scheduling Experiments on World Wide Grid testbed
Conclusions
Scheduling Economics
Grid
EconomyGrid
4
2100
2100 2100 2100 2100
2100 2100 2100 2100
Desktop SMPs or SuperComputers
LocalCluster
GlobalCluster/Grid
PERFORMANCE
Inter PlanetaryGrid!
•Individual•Group•Department•Campus•State•National•Globe•Inter Planet•Universe
Administrative Barriers
EnterpriseCluster/Grid
?
Scalable HPC: Breaking Administrative Barriers & new challenges
5
Why Grids? Large Scale Explorations need them—Killer
Applications. Solving grand challenge applications using modeling, simulation and analysis
Life Sciences
CAD/CAM
Aerospace
Military ApplicationsDigital Biology Military ApplicationsMilitary Applications
Internet & Ecommerce
6
7
What is Grid ?
An infrastructure that logically couples distributed resources:
Computers – PCs, workstations, clusters, supercomputers, laptops, notebooks, mobile devices, PDA, etc;
Software – e.g., ASPs renting expensive special purpose applications on demand;
Catalogued data and databases – e.g. transparent access to human genome database;
Special devices – e.g., radio telescope – SETI@Home searching for life in galaxy.
People/collaborators. and presents them as an integrated global resource. It enables the creation of virtual enterprises (VEs)
for resource sharing.
Widearea
data archives
8
P2P/Grid Applications-Drivers
Distributed HPC (Supercomputing): Computational science.
High-Capacity/Throughput Computing: Large scale simulation/chip design & parameter studies.
Content Sharing (free or paid) Sharing digital contents among peers (e.g., Napster)
Remote software access/renting services: Application service provides (ASPs) & Web services.
Data-intensive computing: Virtual Drug Design, Particle Physics, Stock Prediction...
On-demand, realtime computing: Medical instrumentation & Mission Critical.
Collaborative Computing: Collaborative design, Data exploration, education.
Service Oriented Computing (SOC): Computing as Utility: New paradigm and new industries.
9
Building and Using Grids require
Services that make our systems Grid Ready! Security mechanisms that permit resources
to be accessed only by authorized users. (New) programming tools that make our
applications Grid Ready!. Tools that can translate the requirements of
an application/user into the requirements of computers, networks, and storage.
Tools that perform resource discovery, trading, selection/allocation, scheduling and distribution of jobs and collects results.
Globus
?
10
Players in Grid Computing
11
What users want ?Users in Grid Economy &
Strategy Grid Consumers
Execute jobs for solving varying problem size and complexity
Benefit by selecting and aggregating resources wisely Tradeoff timeframe and cost
Strategy: minimise expenses Grid Providers
Contribute (“idle”) resources for executing consumer jobs Benefit by maximizing resource utilisation Tradeoff local requirements and market opportunity
Strategy: maximise return on investment
12
Agenda
A quick glance at today’s Grid computing Resource Management challenges for next
generation Grid computing A Glance at Approaches to Grid computing Grid Architecture for Computational Economy Economic Models for Resource Management Nimrod-G -- Grid Resource Broker Deadline and Budget Constrained (DBC)
Scheduling Experiments on World Wide Grid testbed
Conclusions
Scheduling Economics
Grid
EconomyGrid
13
Sources of Complexity in Resource Management for World Wide Grid
Computing Size (large number of nodes, providers, consumers) Heterogeneity of resources (PCs, Workstations, clusters, and
supercomputers, instruments, databases, software) Heterogeneity of fabric management systems (single system image OS,
queuing systems, etc.) Heterogeneity of fabric management polices Heterogeneity of application requirements (CPU, I/O, memory, and/or
network intensive) Heterogeneity in resource demand patterns (peak, off-peak, ...) Applications need different QoS at different times (time critical results). The
utility of experimental results varies from time to time. Geographical distribution of users & located different time zones Differing goals (producers and consumers have different objectives and
strategies) Unsecure and Unreliable environment
14
Traditional approaches to resource management & scheduling are NOT useful
for Grid ? They use centralised policy that need
complete state-information and common fabric management policy or decentralised consensus-based
policy. Due to too many heterogenous parameters in the Grid it is impossible to
define/get: system-wide performance matrix and common fabric management policy that is acceptable to all.
“Economics” paradigm proved to effective institution in managing decentralization and heterogeneity that is present in human economies!
Fall of USSR & Emergence of US as world superpower! (monopoly?) So, we propose/advocate the use of computational economics principles
in management of resources and scheduling computations on world wide Grid.
Think locally and act globally approach to grid computing!
15
Benefits of Computational Economies
It provides a nice paradigm for managing self interested and self-regulating entities (resource owners and consumers)
Helps in regulating supply-and-demand for resources. Services can be priced in such a way that equilibrium is maintained.
User-centric / Utility driven: Value for money! Scalable:
No need of central coordinator (during negotiation) Resources(sellers) and also Users(buyers) can make their own decisions and try to
maximize utility and profit. Adaptable It helps in offering different QoS (quality of services) to different applications
depending the value users place on them. It improves the utilisation of resources It offers incentive for resource owners for being part of the grid! It offers incentive for resource consumers for being good citizens There is large body of proven Economic principles and techniques available, we can
easily leverage it.
16
New challenges of Computational Economy
Resource Owners How do I decide service prices ? (economic models?) How do I specify them ? How do I enforce them ? How do I advertise & attract consumers ? How do I do accounting and handle payments? …..
Resource Consumers How do I decide expenses ? How do I express QoS requirements ? How I trade between timeframe & cost ? ….
Any tools, traders & brokers available to automate the process ?
17
Agenda
A quick glance at today’s Grid computing Resource Management challenges for next
generation Grid computing A Glance at Approaches to Grid computing Grid Architecture for Computational Economy Economic Models for Resource Management Nimrod-G -- Grid Resource Broker Deadline and Budget Constrained (DBC)
Scheduling Experiments on World Wide Grid testbed
Conclusions
Scheduling Economics
Grid
EconomyGrid
18
mix-and-match
Object-oriented
Internet/partial-P2P
Network enabled Solvers
Market/Computational Economy
19
Many Testbeds ? & who pays ?,
who regulates supply and demand ?
GUSTO (decommissioned)
Legion Testbed
NASA IPG
World Wide Grid
WW Grid
20
Agenda
A quick glance at today’s Grid computing Resource Management challenges for next
generation Grid computing A Glance at Approaches to Grid computing Grid Architecture for Computational Economy Economic Models for Resource Management Nimrod-G -- Grid Resource Broker Deadline and Budget Constrained (DBC)
Scheduling Experiments on World Wide Grid testbed
Conclusions
Scheduling Economics
Grid
EconomyGrid
21
Building an Economy Grid(Next Generation Grid
Computing!)
To enable the creation and promotion of:Grid Marketplace (competitive)
ASPService Oriented Computing
. . .And let users focus on their own work (science, engineering, or commerce)!
22
Grid Node N
GRACE: A ReferenceGrid 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
Grid Bank
See PDPTA 2000 paper!
23
GridFabric
GridApps.
GridMiddleware
GridTools
Networked Resources across Organisations
Computers Clusters Data Sources Scientific InstrumentsStorage Systems
Local Resource Managers
Operating Systems Queuing Systems TCP/IP & UDP
…
Libraries & App Kernels …
Distributed Resources Coupling Services
Security Information … QoSProcess
Development Environments and Tools
Languages Libraries Debuggers … Web toolsResource BrokersMonitoring
Applications and Portals
Prob. Solving Env.Scientific …CollaborationEngineering Web enabled Apps
Resource Trading
Grid Components
Market Info
24
Economy Grid = Globus + GRACE
Applications
MDS
GRAMGrid Security Interface
Heartbeat MonitorNexus
Local Services
LSF
Condor GRD QBank
PBS
TCP
SolarisIrixLinux
UDP
High-level Services and Tools
DUROC globusrunMPI-G Nimrod/GCC++
Grid Status
GASS
GRACE-TS
GARA
GridFabric
GridApps.
GridMiddleware
GridTools
GBankGMD
eCash
JVM
DUROC
Core Services
Science
Engineering Commerce Portals ActiveSheet……
See IPDPS HWC 2001 paper!
……
25
Agenda
A quick glance at today’s Grid computing Resource Management challenges for next
generation Grid computing A Glance at Approaches to Grid computing Grid Architecture for Computational Economy Economic Models for Resource Management Nimrod-G -- Grid Resource Broker Deadline and Budget Constrained (DBC)
Scheduling Experiments on World Wide Grid testbed
Conclusions
Scheduling Economics
Grid
EconomyGrid
26
Economic Models
Price-based: Supply,demand,value, wealth of economic system
Commodity Market Model Posted Price Model Bargaining Model Tendering (Contract Net) Model Auction Model
English, first-price sealed-bid, second-price sealed-bid (Vickrey), and Dutch (consumer:low,high,rate; producer:high, low, rate)
Proportional Resource Sharing Model Monopoly (one provider) and Oligopoly (few players)
consumers may not have any influence on prices. Bartering
Shareholder Model Partnership Model
27
Grid Open Trading Protocols
Get Connected
Call for Bid(DT)
Reply to Bid (DT)
Negotiate Deal(DT)
Confirm Deal(DT, Y/N)
….
Cancel Deal(DT)
Change Deal(DT)
Get Disconnected
Trade Manager Trade Server
Pricing Rules
DT - Deal Template - resource requirements (BM) - resource profile (BS) - price (any one can set) - status - change the above values - negotiation can continue - accept/decline - validity period
API
28
Various Criteria for Judging Effectiveness of Economic Models
Social Welfare global good of all
Pareto Efficiency global perspective
Individual Rationality better off by participating in negotiation
Stability mechanisms that cannot be manipulated
Computational Efficiency protocols should not consume too much of time
Distribution and Communication Efficiency communication overhead to capture a desirable global
solution
29
A Commodity Market Model
“Solve this in5hrs for $20”
Grid Market Directory (GMD)
ResourceBroker
Grid Info. Service
GTS
GTS
(Grid Service Provider)
GTS
GTS GTS
“register me as GSP”
“Give me list of GSPs & price?”
“service available?”
(GTS - Grid Trade Server)
(GSP)
“service available?”“service availab
le?”
(RB selects GSPs)
30
How to decide Price ?
Fixed price model (like today’s Internet) Dynamic/Demand and Supply (like tomorrow’s Internet) Usage Period Loyalty of Customers (like Airlines favoring frequent flyers!) Historical data Advance Agreement (high discount for corporations) Usage Timing (peak, off-peak, lunch time) Calendar based (holiday/vacation period) Bulk Purchase (register 100 .com domains at once!) Voting -- trade unions decide pricing structure Resource capability as benchmarked in the market! Academic R&D/public-good application users can be offered at
cheaper rate compared to commercial use. Customer Type – Quality or price sensitive buyers. Can be Prescribed by Regulating (Govt.) authorities
31
Posted Price Model
“Solve this bynext day for $5”
Grid Market Directory (GMD)
ResourceBroker
“2hrs SP2, $5”
Grid Info. Service
GTS
GTS
(Grid Service Provider)
GTS
GTS GTS
“T3E, $9/hr, Sunday”
“Free for Genome”“10% discount today”
“Any SP2/T3E? offers”“Free or < $2/hr clusters+matlab”
“5MB free”
(GTS - Grid Trade Server)
(GSP)
32
Bargaining Model
“Solve this in5hrs for $20”
Grid Market Directory (GMD)
ResourceBroker
Grid Info. Service
GTS
GTS
(Grid Service Provider)
GTS
GTS GTS
“register me as GSP”
“Give me list of GSPs”
“access price ?, 2, 3 ?”
(GTS - Grid Trade Server)
(GSP)
“access price ?”“access p
rice ?”(RB negotiates for the best price)
33
Tender/Contract-Net Model
“Solve this in15hrs for $10”
Grid Market Directory (GMD)
ResourceBroker
Grid Info. Service
GTS
GTS
(Grid Service Provider)
GTS
GTS GTS
“Any Ads for service tenders”
“Post: call for tenders”
(GTS - Grid Trade Server)
(GSP)
(GSPs bid)
“gsp1 bid”
“gsp3 bid?”
“gsp2 bid?”
“g
sp
N b
id?”
Closed Reverse Auction ?Buyers name their price and supplies compete to bid the lowest price.Eg: GotFrom.com
34
Auction Model
Grid Market Auctioneer (GMA)
ResourceBroker
“SP2 time, 9pm-8am”
Grid Info. Service
GTS
GTS
(Grid Service Provider)
GTS
GTS GTS
“Post: auction T3E service”
“Solve this in20 hrs for $5”
(GTS - Grid Trade Server)
(GSP)
ResourceBroker
….
“$2, gsp
1”
“$4,
gsp
1”
“$2,
gsp
2”
“Solve this in1 hrs for $35”
(RBs bid)
35
Auction Types
English Auction - first-price open-cry each bidder free to raise his bid and highest bidder
wins at his bid price. First-price sealed bid
each bidder submits one bid and highest bidder wins at his bid price.
Vickrey Auction- Second-price sealed bid each bidder submits one bid and highest bidder
wins at the price of second highest bid. Dutch (descending) Auction
seller continuously lowers the price until one of the bidders’ bids.
36
Proportional Resource Sharing Model
Grid Market Directory (GMD)
ResourceBroker
“SP2 time, 9pm-8am”
Grid Info. Service
GTS
GTS
(Grid Service Provider)
GTS
GTS GTS
“Post: auction T3E service”
“Solve this in20 hrs for $5”
(GTS - Grid Trade Server)
(GSP)
ResourceBroker
….
“RB1: $2”
“Solve this in1 hrs for $50”
(RBs bid)
“Give me list of GSPs”
“RBn: $4”
Resource Share ?Bid/(sum of all bids).E.g., RB1 share = 1/3 RB n share - 2/3
37
Bartering: Partnership/Shareholder
A group of organizations pool in resources (money) together or govt. funded.
APAC (Australian Partnership for Advance Computing)
VPAC (Victorian PAC) - VIC unis and govt. NPACI in US
Allocation proportional to contribution. When in demand: follow proportional resource
sharing strategy & QoS. A group of individuals pool in resources (idle
cycles) like in Condor pool. Contribute for public good/fame (SETI@Home
or distributed.net)
38
Agenda
A quick glance at today’s Grid computing Resource Management challenges for next
generation Grid computing A Glance at Approaches to Grid computing Grid Architecture for Computational Economy Economic Models for Resource Management Nimrod-G -- Grid Resource Broker Deadline and Budget Constrained (DBC)
Scheduling Experiments on World Wide Grid testbed
Conclusions
Scheduling Economics
Grid
EconomyGrid
39
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
40
Parametric Processing
Multiple RunsSame ProgramMultiple Data Killer Application for the Grid!
ParametersAge Hair
23 CleanAge Hair
23 Clean23 Beard28 Goatee
Age Hair23 Clean23 Beard
Age Hair23 Clean23 Beard28 Goatee28 Clean
Age Hair23 Clean23 Beard28 Goatee28 Clean19 Moustache
Age Hair23 Clean23 Beard28 Goatee28 Clean19 Moustache10 Clean
Age Hair23 Clean23 Beard28 Goatee28 Clean19 Moustache10 Clean
-4000000 Too much
Courtesy: Anand Natrajan, University of Virginia
Magic Engine
See IPDPS 2000 paper!
41
Parameter Processing on the Grid
Aggregate Job SubmissionAggregate View
0
10
20
30
40
50
60
70
80
90
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
East
West
North
South
Submit & Play!
42
A 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 LSee HPCAsia 2000 paper!
43
A Nimrod/G Monitor
A Nimrod/G Monitor
CostCostDeadlineDeadline
Legion hosts
Globus Hosts
Bezek is in both Globus and Legion Domains
Arlington
Alexandria
Richmond
HamptonNorfolk
Virginia BeachChesapeakePortsmouth
Newport News
Roanoke
Ap p om a toxRive r
Ja m esRive r
Shena nd oa hRive r
Ra p p a ha nnoc kRive r
Potom a cRive r
VIRGINIA77
81
64
64
66
85
44
User Requirements: Deadline/Budget User Requirements: Deadline/Budget
45
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 SchedulingAlgorithms
Execution Time (not beyond deadline)
Execution Cost (not beyond budget)
Time Minimisation Minimise Limited by budgetCost Minimisation Limited by deadline MinimiseNone Minimisation Limited by deadline Limited by budget
Adaptive Scheduling Algorithms
Compose & Compose & ScheduleSchedule
See HPDC AMS 2000 paper!
46
Agenda
A quick glance at today’s Grid computing Resource Management challenges for next
generation Grid computing A Glance at Approaches to Grid computing Grid Architecture for Computational Economy Economic Models for Resource Management Nimrod-G -- Grid Resource Broker Deadline and Budget Constrained (DBC)
Scheduling Experiments on World Wide Grid testbed
Conclusions
Scheduling Economics
Grid
EconomyGrid
47
Experiment Setup
Workload (Hypothetical Application): 165 jobs, each need 5 minute of CPU time
Deadline: 2 hrs. and budget: 396000 units (G$)
Strategy: minimise time / cost Execution Cost with cost optimisation
Optimise Cost: 115200 (G$) (finished in 2hrs.) Optimise Time: 237000 (G$) (finished in 1.25 hr.) In this experiment: Time-optimised scheduling run
costs double that of Cost-optimised. Users are able to trade-off between Time Vs. Cost
depending on QoS requirements.
48
Globus+LegionGRACE_TS
Australia
Monash Uni.:
Linux cluster
Solaris WS
Nimrod/G
Globus +GRACE_TS
Europe
ZIB/FUB: T3E/Mosix Cardiff: Sun E6500Paderborn: HPCLineLecce: Compaq SCCNR: ClusterCalabria: Cluster CERN: ClusterPozman: SGI/SP2
Globus +GRACE_TS
Asia/Japan
Tokyo I-Tech.:ETL, Tuskuba
Linux cluster
Globus/LegionGRACE_TS
North America
ANL: SGI/Sun/SP2USC-ISI: SGIUVa: Linux ClusterUD: Linux clusterUTK: Linux cluster
Internet
World Wide Grid (WWG)
Globus +GRACE_TS South America
Chile: Cluster
WW Grid
WW Grid
49
Resources Selected & Price/CPU-sec.
Cost_Opt.Time_Opt
4
5
1
1
1
153
378Globus, GTS, ForkSGI-ISI, LA, US
42
9
6
7
64
No. of Jobs Executed
7Globus, GTS, ForkSun-ANL, Chicago,US
3Globus, GTS, ForkSolaris/Ultas2
TITech, Tokyo, Japan
4Globus, GTS, ForkLinux-Barbera-CNR, Pisa, Italy
3Globus, GTS, ForkLinux-Prosecco-CNR, Pisa, Italy
2Globus, GTS, Condor
Linux Cluster-Monash, Melbourne, Australia
Cost/CPU sec.in G$
Grid services & Fabric
Resource & Location
Total Experiment Cost (G$) 237000 115200
Time to Complete Exp. (Min.) 70 119
50
DBC Scheduling for Time Optimization
0
2
4
6
8
10
12
Time (in Minute)
No.
of
Tas
ks i
n E
xecu
tion
Condor-Monash Linux-Prosecco-CNR Linux-Barbera-CNR
Solaris /Ultas2-TITech SGI-ISI Sun-ANL
51
DBC Scheduling for Cost Optimization
0
2
4
6
8
10
12
14
Time (in Minute)
No.
of
Tas
ks i
n E
xecu
tion
Condor-Monash Linux-Prosecco-CNR Linux-Barbera-CNR
Solaris /Ultas2-TITech SGI-ISI Sun-ANL
52
Agenda
A quick glance at today’s Grid computing Resource Management challenges for next
generation Grid computing A Glance at Approaches to Grid computing Grid Architecture for Computational Economy Economic Models for Resource Management Nimrod-G -- Grid Resource Broker Deadline and Budget Constrained (DBC)
Scheduling Experiments on World Wide Grid testbed
Conclusions & Pointers
Scheduling Economics
Grid
EconomyGrid
53
Summary and Conclusions P2P and Grid Computing is emerging as a next generation
computing platform for solving large scale problems through sharing of geographically distributed resources.
Resource management is a complex undertaking as systems need to be adaptive, scalable, competitive,…, and driven by QoS.
We proposed a framework based on “computational economies” and discussed several economic models for resource allocation and for regulating supply-and-demand for resources.
Scheduling experiments on World Wide Grid demonstrate our Nimrod-G broker ability to dynamically lease or rent services at runtime based on their quality, cost, and availability depending on consumers QoS requirements.
Economics paradigm for QoS driven resource management is essential to push P2P/Grids into mainstream computing!
54
Thank You… Any ??
Thank You… Any ??
55
Download Software & Information
Nimrod & Parameteric Computing: http://www.csse.monash.edu.au/~davida/nimrod/
Economy Grid & Nimrod/G: http://www.buyya.com/ecogrid/
Virtual Laboratory/Virtual Drug Design: http://www.buyya.com/vlab/
Grid Simulation (GridSim) Toolkit (Java based): http://www.buyya.com/gridsim/
World Wide Grid (WWG) testbed: http://www.buyya.com/ecogrid/wwg/ Looking for new volunteers to grow
Please contact me to barter your & our machines!
Want to build on our work/collaborate: Talk to me now or email: [email protected]