Reputation Management in Grid-based Virtual Organisations

1
Reputation Management in Grid-based Virtual
Organisations

• Benjamin Aziz(e-Science Centre, STFC Rutherford
  Appleton Laboratory, UK)
• Joint work with Alvaro Arenas (STFC RAL, UK)and
• Gheorghe Silaghi (Babes-Bolyai University,
  Romania)
• The International Conference on Security and
  Cryptography (SECRYPT 2008) Special Session on
  Trust in Pervasive Systems and Networks26-29
  July 2008, Porto, Portugal

2
Content

• Introduction on Grid Computing and Reputation
• Objectives
• A Utility-based Reputation Model
• Reputation Management in Grids
• Analysis of the Model
• Conclusion and Future Work

3
A Model of Grid Computing

• The resource providers in a VBE
• adhere to common operating principles and
  technical infrastructure
• have common goals and an objective of
  participating in potential VOs
• In a VO,
• The VO Owner decides on VO policy
• The VO Manager manages the formation, operation
  and evolution of the VO
• Trust and Security Services provide the usual
  desirable trust and security properties for
  resource and information sharing across
  organisational boundaries. These include
  reputation as a measure of trust

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What is Reputation?

• The overall quality or character as seen or
  judged by people in general reputation can be
  considered as a collective measure of
  trustworthiness (in the sense of reliability)
  based on the referrals or ratings from members in
  a community. (Jøsang, 2007)
• The expectation about future behaviour of a
  person or agent.
• (Abdul-RahmanHailes, 2000)

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Direct vs. Indirect Reputation

• Reputation can be formed either directly or
  indirectly
• Direct Reputation a consumer interacts with a
  service, after which it reports its satisfaction
  with the results to a reputation service
• Indirect Reputation a consumer enquires from
  another consumer about past interactions, after
  which it forms an opinion and reports it to the
  reputation service

6
Why Do We Need Reputation?
Error frequency 1/1000000 error/hr
?
Error frequency 1/100 error/hr
7
Objectives

• Design a reputation management system for
  Grid-based VOs
• The system can qualify both users and resource
  providers
• The system can provide reputation management in
  contexts like
• Fine-grained access and usage control of Grid
  resources
• Resource brokering for setting-up VOs
• Capable of running as both in centralised and
  decentralised modes

8
A Utility-based Reputation Model

• The model is based on the concepts of Consumers,
  Entities, Organisations and VOs
• Entities have issues of interest to be monitored
• Example QoS levels and acceptable usage policies
  for services
• Consumers have expectations about issues of
  interest related to entities they interact with
• Example SLA between services and their clients

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A Utility-based Reputation Model

• A utility function reflects the satisfaction
  (value in 1,0) consumers perceive from
  consuming an entity
• models the traditional client feedback needed to
  build reputation and can be either provided by
  the consumer or taken from a library
• For example, for a variable x and its value v
  returned by some service
• utility(x,v) 1 if v?? SLA(x)
• utility(x,v) v/SLA(x) otherwise
• The environment provides a trusted third party
  monitoring service that supplies events about
  entity-consumer interaction results/performance

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A Utility-based Reputation Model

• The reputation of an entity w.r.t. to an issue of
  interest and from the perspective of a consumer
  is calculated by applying the utility function to
  values reported by the monitoring service
• Example Disk A was found to have only 55 of its
  advertised data transfer speed by client X
• Aggregating over all consumers yields the
  reputation of the entity w.r.t. to that issue of
  interest in general
• Example In general, Disk A has only 85 of its
  advertised data transfer speed
• Aggregating over all issues of interest yields
  the overall reputation of an entity
• Example In general, Disk A achieves only 70 of
  its advertised specifications

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Reputation Management in Grids

• Using our utility-based reputation model we want
  to
• Provide reputation values for Grid
  resources/resource providers based on the QoS
  values produced by resources
• QoS is formalised through SLAs
• Provide reputation values for VO Users based on
  their resource usage behaviour
• Usage behaviour is formalised through policies
  and penalties for breaking those policies
• Perform reputation-aware resource brokering when
  forming a VO or when replacing some of its members

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Reputation Management for Resource Providers
ResourceProvider
Resource QoSMonitoring Service
Resources
User
PerformReputationUpdates
ReputationService
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Reputation Management for Resources

• The reputation updates are as follows
• Apply the Utility Function (constant w.r.t. the
  SLA) to the QoS monitoring information
• Update the VO User, QoS, VO resource reputation
  value
• Update the QoS, VO resource reputation value
• Update the VO resource reputation value
• Update the VBE resource reputation value

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Reputation Management for Resource Providers

• Additionally, the Reputation System calculates
  the following reputation values for the resource
  providers
• The reputation value of the resource provider in
  a VO as an aggregation of the reputation of all
  its resources in that VO
• The reputation value of the resource provider in
  a VBE as an aggregation of its reputation in all
  VOs

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Reputation Management for VO Users
ResourceProvider
Resource UsageMonitoring Service
Resources
User
PerformReputationUpdates
Reputation Service
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Reputation Management for VO Users

• The reputation updates are as follows
• Apply the Utility Function (constant w.r.t. the
  Usage Policy/Penalty Function) to the usage
  monitoring information
• Update the VO resource, Usage, VO user
  reputation value
• Update the Usage, VO user reputation value
• Update the VO user reputation value
• Update the VBE user reputation value

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Reputation-based Resource Brokering
ResourceBrokeringService
VBE
VOOwner/ Manager
Reputation Service
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Decentralised vs. Centralised Reputation Systems
Decentralised Case
VO
VO
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Decentralised vs. Centralised Reputation Systems
Centralised Case
VO
VO
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Analysis of the Model

• We performed simulations using the SimGrid
  toolkit (http//simgrid.gforge.inria.fr/)
• Various set-ups were used
• VOs with reputation-rated resource providers
• VOs with both reputation-rated resource providers
  and users

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VOs with Reputation-rated Resource Providers

• Assumes 20 of resources produce QoS values
  ranging between 85-105 of the SLA-agreed value
• Total job completion time was improved by 25
  using reputation-based scheduling over
  non-reputation-based scheduling (FIFO)
• Total welfare (sum of all utilities acquired by
  the users for their jobs) was also improved by
  25 over non-reputation-based scheduling

22
VOs with Reputation-rated Resource Providers
Completion time vs. VO Load Factor
Total Welfare vs. VO Load Factor
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VOs with Reputation-rated Resource Providers and
Users

• Most (least) reputable resource providers get
  jobs from most (least) reputable users
• User satisfaction is improved since reputable
  users are scheduled first
• Reliable resources are used more effectively
  since they get trusted tasks scheduled on them

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VOs with Reputation-rated Resource Providers and
Users
Total Welfare vs. time
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Conclusion

• We defined a utility-based reputation system for
  Grid-based VOs, which should provide a measure of
  trust in performing Grid computational tasks
• The model is general as it can rate both VO
  resource providers and users and it can be used
  in both centralised and decentralised scenarios
  in the contexts of usage control and resource
  brokering
• The model constitutes the basis for the design of
  a reputation service in the EU FP6 project
  GridTrust (www.gridtrust.eu)
• First prototype to be released this September

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Future Work

• Consider trade-offs in the model, for example
• Introduce the concept of cost and the effect of
  pricing resources on welfare
• Reliability of monitoring service, which affects
  the certainty of reputation values (also known as
  confidence level or probability)
• Dealing with multi-user jobs (VO job submission
  to another VO)
• Carry out further simulations in order to
  understand better the models behaviour
• Discover more scenarios in which the model is
  used
• E.g. sabotage tolerance in peer-to-peer systems

27
Thank You

• Questions?