Dynamic Service Selection &
Analyze
Weina
Ma
June 6
th
, 2013
Paper 1
•
“Web Service Discovery with Implicit
QoS
Filtering”
•
Problem
–
Traditional WS discovery supported by WSDL and
UDDI API is insufficient
–
UDDI API is keyword
-
based query
•
This paper proposed a framework for WS
selection based on
QoS
properties
collected
by a distributed
agent
-
based
system.
Framework
•
Personal Agent (PA) accepts requests from client and send goal to Register.
•
Matching Agent provides list of candidate services which satisfy client’s
goal. It keeps history of requests and provides information searched for
the similar service before.
•
Service Mediator (SM) collects statistics about WS invocations.
•
PA
ranks the services and invokes the best one.
Conclusion
•
Agent
-
based technology is extremely suitable
for WS performance evaluation of cloud
environment.
•
Matching Agent can learn from experience.
Paper 2
•
“Web Service Competition: A New Approach to
Service Selection”
•
Problem
–
Service description is expressed inaccurate, globally
and statically, no depending on client’s needs and
contexts
•
This paper proposes a service selection approach,
using generic service representative technology,
to compare services based on their performance
in a specific client context
.
Methodology
Methodology Continue
Conclusion
•
Security and privacy challenges between
service provider and representative.
•
Increase network traffic.
•
Centralized competition desk fits comparing
performance of algorism, but not real
computing and traffic performance because of
the difference between WS running
environment.
Paper 3
•
“A Simple Approach for Testing Web Services
Based Applications”
•
Problem
–
A Web Application might invoke multiple web services
located on different servers with no design, source
code, or interface available.
•
This paper presents how to test web services
when building composited web application.
–
Two
-
level abstraction model to represent a web
application.
–
Three sets of test cases are generated automatically.
Web Application Representation
•
Task Precedence Graph (TPG)
•
Each
node represents a web service, like Main Component (MC), Hotel Reservation (HR), Car
Reservation (CR) and Weather Prediction (WP).
•
An
edge means the flow of actions (transitions)
•
Each
edge is labeled with an action and its timing constrain.
Single Web Service Representation
•
Time
d Labeled Transition System (TLTS)
•
TLTS represents
transitions from one state to another.
•
Node
means a state
•
Each edge is labeled with an action and its timing constrain.
Test Cases Generation
•
The first set of test cases are generated based
on boundary value testing analysis of WSDL
•
The second set of test cases are all possible
actions in each individual service, by
traversing all paths going from initial state of
TLTS to be fulfilled.
•
The third set of test cases are generated by
traversing all paths going from the initial state
of the TPG.
Web Service Testing Framework
Conclusion
•
Web service testing at stage of building
composited web application rather than
during invocation time.
•
Full
-
coverage test cases generated
automatically.
Paper 4
•
“Runtime Monitoring of Web Service Conversations”
•
This paper proposes to use
runtime monitoring
of
conversations
between partners as a means of
checking behavioral correctness
of the entire web
application.
•
Describe a specification language,
UML 2.0 Sequence
Diagrams (SDs)
, for dynamic analysis of web services.
•
Focus on monitoring finitely terminating behaviors and
capturing safety and
liveness
properties.
Sequence Diagrams
•
Sequence Diagrams (SDs) is to model
behavioral scenarios by describing sequences
of messages communicated between different
objects over time.
•
BasicSD
, par, alt, strict
seq
, weak
seq
, loop,
consider and ignore are terminal symbols.
•
E is a set of SD messages.
Formalizing Sequence Diagrams
•
NFA (Nondeterministic Finite Automaton) is a
finite state machine where from each state and a
given input symbol the automaton may jump into
several possible next states.
•
DFA (deterministic finite automaton) is a finite
that accepts/rejects finite strings of symbols and
only produces a unique computation (or run) of
the automaton for each input string.
•
An NFA A receive a trace of sequence diagram as
input and changes its current state according to
its transition relation
Architecture of Framework
•
User create UML SDs with help
of
PropertyM
.
•
Monitoring
M
converts NFA to DFA.
•
Message
M obtains interaction events from SCAM and directs to
MonitoringM
, in turn, update the state of every active monitor automaton,
until an error has been found or all partners terminate.
Conclusion
•
Not require any code instrument
•
Not significantly affect the performance of
monitored system
•
Requiring a distributed monitoring framework
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