Building Scalable Virtual Communities

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Building Scalable VirtualCommunities

• Omer F. Rana
• (o.f.rana_at_cs.cardiff.ac.uk)
• School of Computer Science
• and Welsh eScience Centre
• Cardiff University
• http//www.cs.cf.ac.uk/
• http//www.wesc.ac.uk/

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Projects at WeSC
EPSRC AgentcitiesUK.net EU CoreGrid EU NUMAS (?)
DTI (GECEM)
EPSRC/DTI (CONNOISE)
EPSRC (PASOA) EPSRC (GENSS) EU (Provenance) EU
(CatNets)
G-QoSM
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Talk in One Slide
Grid Computing Models
Workflow
Integrating Workflow with Community Formation
and Management Triana LEAF G-QoSM
Observations
Outcomes
Peer-2-Peer Models
Community Management
eScience
Dynamic Communities
Communities
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What are we really attempting in eScience?

• Virtually bringing together scientists to solve
  complex problems which may often be
  multidisciplinary
• Establishing Virtual Organisations
• Managed Complexity not Ease-of-use?
• Dynamic formation of such collaborations (and
  their subsequent disbanding)
• UKRC, EU, NSF, etc funding model
• The Café/Restaurant/Pub model
• Mediating support between these individuals
  through compute, data and visualisation resources
• Resource/service challenge is secondary?
• Are we really understanding the processes?
• Where is the novelty?
• Have we abandoned the initial motivation?
• Power Grid may be a bad analogy?
• Can we find others?

Workflows Virtual Organisations ? Communities
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Outcome of eScience?

• Software should be accessible outside the Grid
  Community
• Compare
• KaZaA (file sharing) and BitTorrent (file
  sharing)
• Software should be useful outside the Grid
  community?
• Integrate different aspects of a collaboration
• Nothing yet?
• No Science focus yet

• Significant User Community
• Supports DSL-modem users and high bandwidth users
  at the same time
• Support a Rating mechanism

• Variety of other types of groupings
• (social networking)
• YahooGroups
• LinkedIn
• Orkut (Google)
• BuddySpace, etc

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Gnutella Network -- Steve G. Steinberg).
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Internet Social Networking (April 2004)
Source TrendIQ
Also see http//www.gridblog.com/
Uniyearbooks.com (Dan Crocker, Cardiff)
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Internet Social Networking (April/May 2004)
Source TrendIQ
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What does this tell us?

• Importance of small world interactions
• Some participants more active than others
• Need to identify hub points for traffic sharing
• Co-authorship networks
• File sharing networks
• Identify resource requirements of highly active
  participants

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Sounds like the Grid?

• The key issues behind the Friendster abandonment
  trend, according to users, are the service's
  inability to do anything about its habitual
  server lag problems, and its growing reputation
  for heavy-handed moral policies and unilateral
  decisions it makes on behalf of its members.
• Wired News (wired.com)
• http//www.wired.com/news/culture/0,1284,61150,00.
  html

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Workflow ( Enactment)
From Aleksander Slominski
Launch, configure And control
Orchestration Service
Workflow Engine
Workflow Instance
Workflow Instance
Workflow Instance
Resource layer 1000s of PCs -gtmassive
supercomputers and data sources
Network
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Scientific Workflows

• Triana
• Taverna/SCUFL
• GridAnt
• Condor DAG
• CoG DAG
• SWFL
• BioOpera
• BEPL4WS
• OASIS WSBPEL
• YAWL
• GSFL
• etc
• Origin (?)
• Problem Solving Environments
• (MatLab, Mathematica, SciRun, NetSolve, Ninf,
  Nimrod etc)

• What makes it different (how it is applied)?
• Support for large data flows
• Need to do parameterized execution of large
  number of jobs
• Need to monitor and control workflow execution
  including ad-hoc changes
• Need to execute in dynamic environment where
  resources are not know a priori and may need to
  adapt to changes
• Hierarchical execution with sub-workflows created
  and destroyed when necessary
• Science Domain specific requirements.

Problems with Predictability
Workflow World
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Distributed Workflow ? Community
Community
Performance Info.
WF Executor
Service Provider
Manager
Registry
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Workflows ? Communities

• Communities may be
• functional based on service(s) offered,
  applications supported
• attribute performance, security policy, trust,
  etc
• Community structure influenced by
• capability of service providers
• overall objectives/goals of community as a whole
• utility (measurable) of a provider within a
  community
• Co-operative participants
• coalition or team
• Competing participants
• markets

Community logical organisation, consisting of
a set of service providers and users working
towards some common objectives, or sharing some
common sets of beliefs
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Related Efforts

• Community Formation
• Learning based approaches -- co-operative agents
  (Sun et al.)
• Market and game theoretic approaches (Wellman et
  al.)
• Pursuit of common goals (Singh, Rao, Georgeff et
  al.)
• Joint intentions pursuit -- team oriented
  programming (Jennings et al., Tambe et al.)
• Shared Plans (Grosz and Kraus)
• Coalitions (Sandholm, Lesser et al.)
• Congregation Formation (Durfee, Vidal, Brooks et
  al.)

Other work in Sociology and Economics
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Community Structure

• Service Providers and Users
• provide or use application-specific services
• providers possess Expertise and Interests
• Community Support Services
• registry service
• event service, monitoring service, etc
• Community Manager
• community policy and goals
• manages and monitors Service Level Agreements
• access control for new providers/users

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Community, a useful idea?

• Connection Problem Finding suitable partners to
  interact with
• Intentions so far have been different
• problem solving capability preferred
• Community Stability an important concern
• dependent on environment (and its variability)
• What impact does community formation have on
  scalability?
• Reduce time to search for partners
• Reduce time to co-ordinate (reduce message
  exchanges)

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Types of Communities

• Competing Communities (identical Expertise)
• participants offer similar services
• competition between providers
• Cooperative Communities (different Expertise)
• participants need services of other providers to
  function
• mutual dependence between providers
• Goal Oriented Communities (based on Interests)
• similar to cooperative community
• differs in that goal may change over time, but
  Expertise may not
• new providers allowed only if they posses the
  right Expertise to achieve goal
• Ad Hoc Communities (based on Interests)
• Short term interactions between providers and
  users
• Domain-Oriented Communities (based on
  Interests)
• Interaction based on Interests music sharing
  community, open-source community, etc

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Utility

• Payoff function
• assess behaviour of a particular action (reward
  signal)
• Analysis tool
• relationship between local utility vs. utility of
  the community
• Cost function
• success w.r.t. a particular task
• Trust measure
• measure of trust in a particular participant

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Utility Optimisation
Expected Utility E(x)
0ltglt1

Finite Horizon
Infinite Horizon
U may be negative
Long term rewards less useful
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Community Building Kit LEAF
Four core concepts LEAF agents LEAF utility
functions ESNs LEAF tasks
Provides support for JESS based policy
description Reinforcement learning
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Assigning Utility in LEAF  
Performance and Functional Utility
P
Speed of execution, number of tasks, CPU usage
etc.
Decision making, learning -- high level behaviour.
F
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Performance Utility

• Provides a utility measure based on performance
  engineering related aspects
• Comms metrics
• number of messages exchanged, size of message,
  response time
• Execution metrics
• execution time, time to convergence, queue time
• Memory and I/O metrics
• Memory access time, disk access time
• The effect of implementation decisions
  (algorithms languages) and deployment decisions
  (platforms networks), can be assessed.

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Functional Utility

• Utility based on problem solving capability
• Statically defined
• related to service properties (capability based)
• degree of match between task properties and
  service capability
• syntax match (exact match)
• range match
• semantic match (subsumption/subclass)
• Dynamically defined
• related to execution output (MSE)

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Utility Function Implementation

• Extend the LocalUtilityFunction abstract class.
• Implement the compute() method.
• Functions have access to remote parameters and
  observable properties.

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LEAF Learning Agent FIPA-Compliant Community
Toolkit  

• Coordination utility functions are assigned to
  agents by an Environment Service Node.

ESN
f2
f1
Community
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LEAF Learning Agent FIPA-Compliant Community
Toolkit  
Multiple utility functions can be assigned
ESN
ESN
f3
f2
f1
sum f2,f3
Community b
Community a
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LEAF Learning Agent FIPA-Compliant Community
Toolkit  
LEAF Learning Agent FIPA-Compliant Community
Toolkit  

• Utility functions can have parameters that are
  not available locally to the agent.

ESN
O
R
f1
Community
O observable properties R remote parameters
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Access to utility functions

• double computeFunctionalUtility()
• Computes the sum of all currently assigned
  functional utility functions.
•  
• double computePerformanceUtility()
• Computes the sum of all currently assigned
  performance utility functions.
•  
• String getFunctionalUtilityRequiredProperties(
  )
• Returns the observable properties required to
  compute the agents functional utility functions.
•  
• String getPerformanceUtilityRequiredProperties
  ()
• Returns the observable properties required to
  compute the agents performance utility
  functions.
• Others
• UpdateTimeperiod,
• removePerformanceUtilityFunction,
• ESNConnect
•  
•  

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Via Community Manager
Community
Performance Info.
WF Executor
Service Provider
Manager
Registry
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Simulation Four types of Communities

• Task categories Compute, Visualisation,
  Instrumentation and Storage
• Mainly performance utility evaluated
• Utility rate of job completions (of those
  submitted, how many are completed)
• Need cooperation (process locally or send to
  another provider)

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Utility Functions
Global Utility (G) Si Local Utility (Ui) U
(jobs of type X processed)/(jobs of type X
submitted) U 1/(idle time)
where Aa is the number of applications processed
by user a, and Ja is the total resource usage
time used by a. c1,c2 are constants
where Tr is the number of tasks processed by
resource provider r, and idler is the total time
spent idle by the provider. c1,c2 are constants
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computational community
Utility
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Co-operative Community
storage community
Utility
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How to kill a (Grid) Mammoth
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More Info.

• Triana
• http//www.trianacode.org/
• http//www.gridlab.org/
• http//www.gridoned.org/
• LEAF
• http//www.cs.cf.ac.uk/User/S.J.Lynden/leaf/
• G-QoSM
• http//www.cs.cf.ac.uk/User/Rashid/
• http//www.wesc.ac.uk/projects/uddie/

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Thanks to

• Steven Lynden, Newcastle University
• Ian Taylor, Matt Shields, Ian Wang, Ali
  Shaikhali, Shalil Majithia, Asif Akram, Rashid
  Al-Ali and David W. Walker, Cardiff University
• Luc Moreau, Southampton University
• Kaizar Amin and Gregor von Laszewski, Argonne
  National Lab
• Jose Cunha, Fernanda Barbosa and Cecilia Gomes,
  New University of Lisbon