Slide No' 1

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Reputation-based Semantic Service Discovery

• Ali Shaikh Ali
• Shalil Majitha
• Omer F. Rana
• David W.Walker

ETNGRID 2004Presented on 14th June 2004
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Agenda

• Motivating Example
• The Research Problem
• The Traditional Approaches
• A better Approach

Framework Framework Overview Matchmaker and
Service Composer Reputation Management
Conclusions Future Studies
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Motivating Example

• Mr Screen Bean is looking for a reliable Toyota
  Saloon Car selling Service.

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Available Services
S1
S2
S3
Sells Toyota Cars
Sells Toyota Cars
Sells Saloons Cars
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Service Discovery The traditional approaches

• Use of UDDI

ltfind_service generic"2.0" xmlns"urnuddi-orgap
i_v2"gt ltnamegtToyotaCarSellingServicelt/namegt
ltcategoryBaggt ltkeyedReference
tModelKey21525-25365-2589-2
keyNameautomobile" keyValuecar" /gt
lt/categoryBaggt lt/find_servicegt
?
S1(ToytaCarService) S2S1(ToytaCarService)
FindService ServiceName Category
services
UDDI
Limitations
UDDI cannot help automatically locate services
based on service capabilities and behaviours
(i.e. Trust).
?
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Service Discovery The traditional approaches

• Use of Semantic Matchmaking

ltprofileProfile rdfID"RequestToyotaSellService
"gt ltinputgt ltprofileParameterDescription
rdfID"Price_Input"gt ltprofileparameterNamegtPrice
lt/profileparameterName"gt ltprofilerestrictedTo
rdfresource"Concepts.damlPrice"\gt lt/profilePar
ameterDescriptiongt lt/inputgt ltoutputgt ltprofilePara
meterDescriotion rdfID"Car_Output"gt ltprofilepar
ameterNamegtToyotaSaloonlt/profileparameterName"gt lt
profilerestrictedTo rdfresource"Vehicle.damlTo
yotaSaloon"\gt lt/profileParameterDescriptiongt lt/ou
tputgt lt/profileProfilegt
S1(ToytaCarService) S2 (ToytaCarService) S3(Sa
loonCarService)
FindService Ontology
services
Matchmaker
Limitations
Matchmakers cannot help automatically locate
services based on service behaviours (i.e.
Trust).
?
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Service Discovery A better Approach

• A better approach would enable users to
• Easily and efficiently discovered a reputable
  service that is more suitable to users needs.
• Focus on the conceptual basis of their
  experiments rather than understanding the low
  level details of locating services.
• Easy create and share high quality complex
  workflows.

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Relationship with Grid Computing

• Grid computing efforts adopt Web services
  technologies, i.e. Web Services Resource
  Framework.
• Our approach is relevant for deployment with
  WSRF.

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Agenda

• Motivating Example
• The Research Problem
• The Traditional Approaches
• A better Approach

• Framework
• Framework Overview
• Matchmaker and Service Composer
• Reputation Management

Conclusions Future Studies
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Framework Overview
Discovery Manger Service
Matchmaker Service
Composer Service
Reputation Manger Service
Service Repository
Rulebase
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Matchmaker

• Compares service request with service
  advertisements.
• Ensures the reputation metrics of the advertised
  service meet the requirements of the request.
• Implementation is based on the Paoluccis
  algorithm.

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Matchmaker (cont.)
Paoluccis algorithm overview
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Service Composer

• Discovery Manager Service (DMS) requests the
  Service Composer (SC) if the Matchmaker is unable
  to retrieve a service.
• SC puts together combination of services that can
  provide the required functionality and match the
  requested reputation metric.
• CS uses a dynamic adaptive algorithm using two
  different sources of information
• Rule base CS queries a rule base to retrieve a
  rule which can provide a composition template.
• Chaining Services CS attempts to create a chain
  of services that when put together can fulfil the
  user objective.

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Service Composer (con.)

• Rule base CS queries a rule base to retrieve a
  rule which can provide a composition template.
• CS attempts to semantically match the inputs and
  outputs of each element in the template with
  services in the repository.
• If matching does not succeed, CS attempts to find
  another rule that can decompose the template
  further (recursively).
• CS will then query the service repository to
  ascertain if any service match the rule.
• Services are connected together into a workflow
  graph based on the control constructs specified
  in the rule.

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Reputation Manager Service

• What constitute good reputation is a subjective
  criterion.
• Users may want services that have good reputation
  rating in multiple contexts
• Contexts accessibility, or reliability (or both)
• Three phases are involved in computing the
  reputation of a service
• Reputation Interrogation Phase (RIP).
• Reputation Rating Phase (RRP).
• Reputation Computation Phase (RCP).

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Service Composer (con.)

• Chaining Services CS attempts to create a chain
  of services that when put together can fulfill
  the user objective.

• Algorithm
• For each service available, find a service that
  matches the output of the service requested. Let
  one such service be Sn.
• Ascertain the input of Sn. Find a service that
  can generate the input for Sn. Let this service
  be S(n -1)
• This process is iterated until the input of the
  service S(n-x) matches the input of the service
  requested.
• Create the workflow which specifies the order of
  execution of the components S1 to Sn.

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Reputation Manager Service

• Three Phases are involved

• A user requests service reputation from a RMS.
• The reputation request can either be
• A request for the overall reputation score of a
  service
• The reputation score of a service within a
  particular context
• The aggregation of a set of contexts.

• A user rates a service based on his observations
  about the service capability.
• The rating is then published to the RMS.
• Relying on the service users to provide feedback
  to themselves unlink the P2P reputation
  mechanisms.

• RMS computes the reputation of a service by
  evaluating several ratings from other users that
  interacted with the service in the past.

• RIP

• RRP

• RCP

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The Reputation Rating Phase

• Rating the Availability of a service.
• A user sends a service request to invoke a
  particular service.

service
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The Reputation Rating Phase

• Rating the Reliability of a service.
• A user sends a service request to invoke a
  particular service.

SLA
Invoking the service based on SLA
Service
Negotiate SLA
SLA established
SLA Violation
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The Reputation Rating Phase (cont..)

• Rating the Reliability of a service (cont..).
• A service user rates service behaviour by
  examining the terms in the SLA with his
  observation during service execution.
• As users cannot monitor the service execution
  directly, users compute the estimated execution
  time test.

?t tgen - test
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The Reputation Rating Phase (cont..)

• Rating the Reliability of a service (cont..).
• The user evaluates his perception abut the value
  of t and sends a rating to RMS.
• Rating must be a natural number between -2, 2.

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The Reputation Computation Phase

• Two types of service are supported
• Atomic executed by a single service provider.
• Composite combined response from multiple
  providers.
• Generating reputation metrics for atomic services
• RMS receives a reputation interrogation about a
  particular list of services.
• The request message contains the context in which
  the user is interested.
• The reputation score of a service within a
  particular context is computed as the average
  rating of the ratings

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The Reputation Computation Phase (cont..)

• The reputation score of a service within multiple
  contexts is computed as the weighted sum of the
  reputation score of each context

Reputation of service s within all contexts
The weight attached to a particular context

• The weight of each context reflects its
  importance to a particular set of users.
• Each time a user interrogate the reputation of a
  service within a particular
• context, the weight of that context is
  increased.

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The Reputation Computation Phase (cont..)

• The Decay Function
• The reputation is associated with a service
  decays with time.
• A damping function is introduced.
• To compute the decay function R(s,c)new , we
  evaluate how long ago a particular rating was
  generated

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The Reputation Computation Phase (cont..)

• Generating reputation metrics for composite
  services.
• CS composes services if the MSS is unable to
  retrieve a matching service.
• The composite service is constructed from several
  services with different reputation scores.
• Four different structures to compose services.

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The Reputation Computation Phase (cont..)

• Four different structure to compose services

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The Reputation Computation Phase (cont..)

• Four different structure to compose services

Lemma If the reputation of A within context c is
rv(a,c) and the reputation of B within context c
is rv(b,c), and the reputation of A is
independent of the reputation of B, and the
composite service C A B is composed as a
sequence structure, then the reputation for the
composite service C is defined by rv(a,c)
rv(b,c)
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Agenda

• Motivating Example
• The Research Problem
• The Traditional Approaches
• A better Approach

• Framework
• Framework Overview
• Matchmaker and Service Composer
• Reputation Management

• Conclusions
• Future Studies

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Future work

• The content of the SLA.
• Trusted Monitoring Service. (Third Party).
• Identify the relationship between the reputation
  and QoS.
• Implementation of the future approach.

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We Hereby Reach The End Of Our Presentation
Clearing Any Doubts Is Our Next Mission
We Welcome Your Questions
We Appreciate Your Attention